From f0372593024b7fcff0e58ed704a92c176fdf1116 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Tue, 12 Aug 2025 15:38:09 +1000 Subject: [PATCH 01/70] adding main logic --- assets/samplesheet.csv | 6 +- assets/schema_input.json | 27 ++- conf/test_gadi.config | 65 ++++++ main.nf | 22 +- modules/local/collect_confidence.nf | 82 ++++++++ modules/local/mmseqs_colabfoldsearch/main.nf | 53 +++++ modules/local/prepare_interactions.nf | 81 ++++++++ modules/local/run_boltz/main.nf | 49 +++++ nextflow.config | 3 +- .../local/utils_nfcore_wisps_pipeline/main.nf | 37 ++-- workflows/interactions.nf | 138 +++++++++++++ workflows/wisps.nf | 193 ++++++++++++------ 12 files changed, 657 insertions(+), 99 deletions(-) create mode 100644 conf/test_gadi.config create mode 100644 modules/local/collect_confidence.nf create mode 100644 modules/local/mmseqs_colabfoldsearch/main.nf create mode 100644 modules/local/prepare_interactions.nf create mode 100644 modules/local/run_boltz/main.nf create mode 100644 workflows/interactions.nf diff --git a/assets/samplesheet.csv b/assets/samplesheet.csv index 5f653ab..8e79bde 100644 --- a/assets/samplesheet.csv +++ b/assets/samplesheet.csv @@ -1,3 +1,3 @@ -sample,fastq_1,fastq_2 -SAMPLE_PAIRED_END,/path/to/fastq/files/AEG588A1_S1_L002_R1_001.fastq.gz,/path/to/fastq/files/AEG588A1_S1_L002_R2_001.fastq.gz -SAMPLE_SINGLE_END,/path/to/fastq/files/AEG588A4_S4_L003_R1_001.fastq.gz, +id,fasta,type,group +T1024,https://raw.githubusercontent.com/nf-core/test-datasets/proteinfold/testdata/sequences/T1024.fasta,protein,G1 +T1026,https://raw.githubusercontent.com/nf-core/test-datasets/proteinfold/testdata/sequences/T1026.fasta,protein,G1 diff --git a/assets/schema_input.json b/assets/schema_input.json index e78c383..bcc9839 100644 --- a/assets/schema_input.json +++ b/assets/schema_input.json @@ -7,27 +7,32 @@ "items": { "type": "object", "properties": { - "sample": { + "id": { "type": "string", "pattern": "^\\S+$", - "errorMessage": "Sample name must be provided and cannot contain spaces", + "errorMessage": "Sequence name must be provided and cannot contain spaces", "meta": ["id"] }, - "fastq_1": { + "fasta": { "type": "string", "format": "file-path", "exists": true, - "pattern": "^\\S+\\.f(ast)?q\\.gz$", - "errorMessage": "FastQ file for reads 1 must be provided, cannot contain spaces and must have extension '.fq.gz' or '.fastq.gz'" + "pattern": "^\\S+\\.fa(sta)?$", + "errorMessage": "Fasta file must be provided, cannot contain spaces and must have extension '.fa' or '.fasta'" }, - "fastq_2": { + "type": { "type": "string", - "format": "file-path", - "exists": true, - "pattern": "^\\S+\\.f(ast)?q\\.gz$", - "errorMessage": "FastQ file for reads 2 cannot contain spaces and must have extension '.fq.gz' or '.fastq.gz'" + "pattern": "^\\S+$", + "meta": ["type"], + "default": "protein" + }, + "group": { + "type": "string", + "pattern": "^\\S+$", + "meta": ["group"], + "default": "all" } }, - "required": ["sample", "fastq_1"] + "required": ["id", "fasta"] } } diff --git a/conf/test_gadi.config b/conf/test_gadi.config new file mode 100644 index 0000000..df1edfb --- /dev/null +++ b/conf/test_gadi.config @@ -0,0 +1,65 @@ +/* +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + Nextflow config file for running minimal tests +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + Defines input files and everything required to run a fast and simple pipeline test. + + Use as follows: + nextflow run nf-core/wisps -profile test, --outdir + +---------------------------------------------------------------------------------------- +*/ +includeConfig 'https://raw.githubusercontent.com/nf-core/configs/master/conf/nci_gadi.config' + +singularity.cacheDir = "/g/data/if89/singularity_cache/" +singularity.autoMounts = true +singularity.enabled = true +if (params.use_gpu) { singularity.runOptions = '--nv' } + +params { + config_profile_name = 'Test profile' + config_profile_description = 'Minimal test dataset to check pipeline function' + + // Input data + outdir = "out-test" + input = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" + samplesheet2 = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" + + boltz_ccd = "/g/data/if89/proteinfold_dbs/boltz_dbs/ccd.pkl" + boltz_model = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz1_conf.ckpt" + colabfold_db = "/g/data/if89/proteinfold_dbs/miniature_databases/colabfold_envdb_202108/" + uniref30 = "/g/data/if89/proteinfold_dbs/miniature_databases/uniref30_2302/" + use_gpu = true + project = "ll61" + use_dgxa100 = false +} + +process { + //executor = "local" + storage = "gdata/if89+scratch/${params.project}+gdata/${params.project}" + + withName: 'MMSEQS_COLABFOLDSEARCH' { + memory = 300.GB + time = 16.h + } + withName: 'RUN_BOLTZ' { + cpus = 12 + queue = "gpuvolta" + time = 10.h + memory = 24.GB + cpus = 12 + gpus = 1 + } + resourceLimits = [ + cpus: 1, + memory: '5.GB', + time: '1.h' + ] + resourceLimits = [ + cpus: 1000, + memory: '2000.GB', + time: '24.h' + ] + +} + diff --git a/main.nf b/main.nf index efef31d..bf91b45 100644 --- a/main.nf +++ b/main.nf @@ -16,6 +16,7 @@ */ include { WISPS } from './workflows/wisps' + include { PIPELINE_INITIALISATION } from './subworkflows/local/utils_nfcore_wisps_pipeline' include { PIPELINE_COMPLETION } from './subworkflows/local/utils_nfcore_wisps_pipeline' /* @@ -33,15 +34,26 @@ workflow NFCORE_WISPS { samplesheet // channel: samplesheet read in from --input main: - + ch_samplesheet = samplesheet + ch_multiqc = Channel.empty() + ch_versions = Channel.empty() + multiqc_report = Channel.empty() // // WORKFLOW: Run pipeline // - WISPS ( - samplesheet - ) + WISPS ( + ch_samplesheet, + params.mode, + ch_versions, + params.boltz_ccd, + params.boltz_model, + params.colabfold_db, + params.uniref30 + ) + ch_versions = ch_versions.mix(WISPS.out.versions) + emit: - multiqc_report = WISPS.out.multiqc_report // channel: /path/to/multiqc_report.html + multiqc_report //= WISPS.out.multiqc_report // channel: /path/to/multiqc_report.html } /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ diff --git a/modules/local/collect_confidence.nf b/modules/local/collect_confidence.nf new file mode 100644 index 0000000..77881ac --- /dev/null +++ b/modules/local/collect_confidence.nf @@ -0,0 +1,82 @@ +process COLLECT_CONFIDENCE { + tag "$meta.id" + label 'process_single' + + conda "${moduleDir}/environment.yml" + container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? + 'https://depot.galaxyproject.org/singularity/python:3.8.3' : + 'quay.io/biocontainers/python:3.8.3' }" + + input: + tuple val(meta), val(samples) + path(json_files) + output: + tuple val(meta), path ("confidence_scores_full.csv"), emit: confidence + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + + """ + #!/usr/bin/env python3 + + import os, sys + import json + import csv + + # Folder containing the JSON files + output_csv = "confidence_scores_full.csv" + + # Collect all JSON files + json_files = ["${json_files.join('", "')}"] + samples = ["${samples.join('", "')}"] + + # Store all rows here + rows = [] + all_keys = ["confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde", "chains_ptm"] + writing_keys = ["id", "confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde"] + # First pass: read and collect keys + cntr = 0 + for file in json_files: + with open(file) as f: + data = json.load(f) + flat_data = {"id" : samples[cntr]} + cntr += 1 + for key, value in data.items(): + if key not in all_keys: + continue + if isinstance(value, dict): + for sub_key, sub_value in value.items(): + flat_data[f"{key}_{sub_key}"] = sub_value + writing_keys.append(f"{key}_{sub_key}") + else: + flat_data[key] = value + rows.append(flat_data) + + # Write to CSV + with open(output_csv, "w", newline="") as f: + writer = csv.DictWriter(f, fieldnames=writing_keys) + writer.writeheader() + for row in rows: + writer.writerow({key: row.get(key, "") for key in writing_keys}) + + print(f"CSV file created at: {output_csv}") + + with open ("versions.yml", "w") as version_file: + version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) + """ + + stub: + """ + touch "confidence_scores_full.csv" + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + generate_comparison_report.py: \$(python3 --version) + END_VERSIONS + """ +} diff --git a/modules/local/mmseqs_colabfoldsearch/main.nf b/modules/local/mmseqs_colabfoldsearch/main.nf new file mode 100644 index 0000000..68d2d2c --- /dev/null +++ b/modules/local/mmseqs_colabfoldsearch/main.nf @@ -0,0 +1,53 @@ +process MMSEQS_COLABFOLDSEARCH { + tag "$meta.id" + label 'process_high_memory' + + container "nf-core/proteinfold_colabfold:dev" + + input: + tuple val(meta), path(fasta) + path ('db/*') + path ('db/*') + + output: + tuple val(meta), path("**.a3m"), emit: a3m + path "versions.yml", emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + // Exit if running this module with -profile conda / -profile mamba + if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) { + error("Local MMSEQS_COLABFOLDSEARCH module does not support Conda. Please use Docker / Singularity / Podman instead.") + } + def args = task.ext.args ?: '' + + """ + colabfold_search \\ + $args \\ + --threads $task.cpus ${fasta} \\ + ./db \\ + "result/" + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + colabfold_search: \$(conda run -n colabfold pip list | grep "^colabfold" | awk '{print \$2}') + alphafold_colabfold: \$(conda run -n colabfold pip list | grep "^alphafold-colabfold" | awk '{print \$2}') + mmseqs: \$(mmseqs version) + END_VERSIONS + """ + + stub: + """ + mkdir results + touch results/${meta.id}.a3m + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + colabfold_search: \$(conda run -n colabfold pip list | grep "^colabfold" | awk '{print \$2}') + alphafold_colabfold: \$(conda run -n colabfold pip list | grep "^alphafold-colabfold" | awk '{print \$2}') + mmseqs: \$(mmseqs version) + END_VERSIONS + """ +} \ No newline at end of file diff --git a/modules/local/prepare_interactions.nf b/modules/local/prepare_interactions.nf new file mode 100644 index 0000000..2eb0a49 --- /dev/null +++ b/modules/local/prepare_interactions.nf @@ -0,0 +1,81 @@ +process PREPARE_INTERACTIONS { + tag "$meta.id" + label 'process_single' + + conda "${moduleDir}/environment.yml" + container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? + 'https://depot.galaxyproject.org/singularity/python:3.8.3' : + 'quay.io/biocontainers/python:3.8.3' }" + + input: + tuple val(meta), val(fasta) + tuple val(meta), val(a3m) + tuple val(meta), val(types) + path(files) + output: + tuple val(meta), path ("*.fasta"), emit: fasta + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + + """ + #!/usr/bin/env python3 + import os, sys + import string + + #single_letters = list(string.ascii_uppercase) + #two_letter_combinations = [''.join(p) for p in product(string.ascii_uppercase, repeat=2)] + #all_combinations = single_letters + two_letter_combinations + all_combinations = list(string.ascii_uppercase) + list(string.ascii_lowercase) + [str(x) for x in range(0, 10)] + fasta_files = ["${fasta.join('", "')}"] + a3m_files = ["${a3m.join('", "')}"] + seq_types = ["${types.join('", "')}"] + for seq_type in seq_types: + if seq_type not in {"protein", "dna", "rna", "smiles", "ccd"}: + print(f'seqeuence type should be ["protein", "dna", "rna", "smiles", "ccd"], found {seq_type}!') + exit (1) + output_file = "${meta.id}_boltz_interaction_input.fasta" + counter = 0 + with open(output_file, "w") as outfile: + for seq_itr in range(len(seq_types)): + fasta = fasta_files[seq_itr] + a3m = a3m_files[seq_itr] + seq_type = seq_types[seq_itr] + + with open(fasta, "r") as f: + lines = f.readlines() + + if not lines: + continue # Skip empty FASTA files + + #header = lines[0].strip() + body = lines[1:] + header = f">{all_combinations[counter]}|{seq_type}" + counter += 1 + if seq_type == "protein": + header += f"|{os.path.basename(a3m)}\\n" + else: + header += "\\n" + + outfile.write(header) + outfile.writelines(body) + + with open ("versions.yml", "w") as version_file: + version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) + """ + + stub: + """ + touch "${meta.id}_boltz_interaction_input.fasta" + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + generate_comparison_report.py: \$(python3 --version) + END_VERSIONS + """ +} diff --git a/modules/local/run_boltz/main.nf b/modules/local/run_boltz/main.nf new file mode 100644 index 0000000..b513437 --- /dev/null +++ b/modules/local/run_boltz/main.nf @@ -0,0 +1,49 @@ +/* + * Run Boltz + */ +process RUN_BOLTZ { + tag "$meta.id" + label 'process_medium' + + container "fastfold/boltz-1:latest" + + input: + tuple val(meta), path(fasta) + path (files) + path ('boltz1_conf.ckpt') + path ('ccd.pkl') + + output: + tuple val(meta), path ("boltz_results_*/processed/msa/*.npz"), emit: msa + tuple val(meta), path ("boltz_results_*/processed/structures/*.npz"), emit: structures + tuple val(meta), path ("boltz_results_*/predictions/*/confidence*.json"), emit: confidence + tuple val(meta), path ("*"), emit: plddt + tuple val(meta), path ("boltz_results_*/predictions/*/*.pdb"), emit: pdb + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + + """ + boltz predict --output_format pdb ${args} "${fasta}" --cache ./ + """ + stub: + """ + mkdir -p boltz_results_${meta.id}/processed/msa/ + mkdir -p boltz_results_${meta.id}/processed/structures/ + mkdir -p boltz_results_${meta.id}/predictions/${meta.id}/ + + touch boltz_results_${meta.id}/processed/msa/${meta.id}.npz + touch boltz_results_${meta.id}/processed/structures/${meta.id}.npz + touch boltz_results_${meta.id}/predictions/${meta.id}/confidence_${meta.id}.json + touch boltz_results_${meta.id}/predictions/${meta.id}/${meta.id}.pdb + + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + END_VERSIONS + """ +} diff --git a/nextflow.config b/nextflow.config index d89986c..1b1bf29 100644 --- a/nextflow.config +++ b/nextflow.config @@ -12,7 +12,7 @@ params { // TODO nf-core: Specify your pipeline's command line flags // Input options input = null - + mode = "all-all" // MultiQC options @@ -153,6 +153,7 @@ profiles { } test { includeConfig 'conf/test.config' } test_full { includeConfig 'conf/test_full.config' } + test_gadi { includeConfig 'conf/test_gadi.config' } } // Load nf-core custom profiles from different Institutions diff --git a/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf b/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf index 410549e..c113275 100644 --- a/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf +++ b/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf @@ -67,25 +67,26 @@ workflow PIPELINE_INITIALISATION { // Create channel from input file provided through params.input // - Channel - .fromList(samplesheetToList(params.input, "${projectDir}/assets/schema_input.json")) - .map { - meta, fastq_1, fastq_2 -> - if (!fastq_2) { - return [ meta.id, meta + [ single_end:true ], [ fastq_1 ] ] - } else { - return [ meta.id, meta + [ single_end:false ], [ fastq_1, fastq_2 ] ] - } + ch_samplesheet = Channel.fromList(samplesheetToList(params.input, "assets/schema_input.json")) + if (params.split_fasta) { + // TODO: here we have to validate that the ids are unique and valid as an extra step + // since it is not done with the samplesheet schema (they are all in the same file) + ch_samplesheet.map { meta, fasta -> + validateFasta(fasta) } - .groupTuple() - .map { samplesheet -> - validateInputSamplesheet(samplesheet) - } - .map { - meta, fastqs -> - return [ meta, fastqs.flatten() ] - } - .set { ch_samplesheet } + + // Split the fasta file into individual files for each sequence + ch_samplesheet + .map { meta,fasta -> fasta } + .splitFasta( record: [header: true, sequence: true] ) + .collectFile { item -> + [ "${cleanHeader(item["header"])}.fa", ">" + cleanHeader(item["header"]) + '\n' +item["sequence"] ] + } + .map { + file -> [[id: file.baseName], file] + } + .set { ch_samplesheet } + } emit: samplesheet = ch_samplesheet diff --git a/workflows/interactions.nf b/workflows/interactions.nf new file mode 100644 index 0000000..6542a68 --- /dev/null +++ b/workflows/interactions.nf @@ -0,0 +1,138 @@ +/* +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + IMPORT LOCAL MODULES/SUBWORKFLOWS +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +*/ + +// +// MODULE: Loaded from modules/local/ +// + +/* +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + IMPORT NF-CORE MODULES/SUBWORKFLOWS +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +*/ + +// +// MODULE: Installed directly from nf-core/modules +// +include { MULTIQC } from '../modules/nf-core/multiqc/main' +include { CREATE_SAMPLESHEET_YAML } from '../modules/local/create_samplesheet' +include { MMSEQS_COLABFOLDSEARCH } from '../modules/local/mmseqs_colabfoldsearch' +include { PREPARE_INTERACTIONS } from '../modules/local/prepare_interactions' +include { COLLECT_CONFIDENCE } from '../modules/local/collect_confidence' +// +// SUBWORKFLOW: Consisting entirely of nf-core/modules +// +include { paramsSummaryMap } from 'plugin/nf-schema' +include { paramsSummaryMultiqc } from '../subworkflows/nf-core/utils_nfcore_pipeline' +include { softwareVersionsToYAML } from '../subworkflows/nf-core/utils_nfcore_pipeline' +include { methodsDescriptionText } from '../subworkflows/local/utils_nfcore_proteinfold_pipeline' + +// +// MODULE: Boltz +// +include { RUN_BOLTZ } from '../modules/local/run_boltz' + +/* +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + RUN MAIN WORKFLOW +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +*/ + +workflow INTERACTIONS { + + take: + ch_samplesheet_1 // channel: samplesheet read from --input + samplesheet_2 // channel: samplesheet read from --input + ch_versions // channel: [ path(versions.yml) ] + ch_boltz_ccd // channel: [ path(boltz_ccd) ] + ch_boltz_model // channel: [ path(model) ] + ch_colabfold_params // channel: [ path(colabfold_params) ] + ch_colabfold_db // channel: [ path(colabfold_db) ] + ch_uniref30 // channel: [ path(uniref30) ] + + main: + ch_multiqc_files = Channel.empty() + + Channel.fromPath(samplesheet_2) + .splitCsv(header: true) + .map{row -> [["id": row.id, "type": row.type ?: "protein"], file(row.fasta, checkIfExists: true)]} + .set{ch_samplesheet_2} + + ch_samplesheet_1.map{it[0]}.combine(ch_samplesheet_2.map{it[0]}).map{["id": [it[0]["id"], it[1]["id"]].min() + "-" + [it[0]["id"], it[1]["id"]].max()]}.unique().set{ch_unique_pairs} + + + MMSEQS_COLABFOLDSEARCH ( + ch_samplesheet_1.map{it[0].type = "protein"; it}.mix(ch_samplesheet_2).unique().filter{it[0].type == "protein"}, + ch_colabfold_params, + ch_colabfold_db, + ch_uniref30 + ) + ch_versions = ch_versions.mix(MMSEQS_COLABFOLDSEARCH.out.versions) + + ch_left_list = ch_samplesheet_1.join(MMSEQS_COLABFOLDSEARCH.out.a3m, remainder: true) + ch_right_list = ch_samplesheet_2.join(MMSEQS_COLABFOLDSEARCH.out.a3m, remainder: true) + + //ch_samplesheet_1.view() + //ch_samplesheet_2.view() + //MMSEQS_COLABFOLDSEARCH.out.a3m.view() + + //ch_left_list.combine(ch_right_list).view() + + ch_left_list + .combine(ch_right_list) + .map{[ + ["id": [it[0]["id"], it[3]["id"]].min() + "-" + [it[0]["id"], it[3]["id"]].max()], + [it[1].name, it[4].name], + [it[2] ? it[2].name : "", it[5] ? it[5].name : ""], + [it[0]["type"], it[3]["type"]], + [it[1], it[2], it[4], it[5]].findAll{it}.unique{it.toUriString()}, + + ]}.set{ch_pairs} + + ch_pairs + .join(ch_unique_pairs) + .set{ch_interaction_input} + + PREPARE_INTERACTIONS( + ch_interaction_input.map{[it[0], it[1]]}, + ch_interaction_input.map{[it[0], it[2]]}, + ch_interaction_input.map{[it[0], it[3]]}, + ch_interaction_input.map{it[4]} + ) + + PREPARE_INTERACTIONS.out.fasta + .join(ch_interaction_input) + .set{ch_boltz_input} + + RUN_BOLTZ( + ch_boltz_input.map{[it[0], it[1]]}, + ch_boltz_input.map{it[5].findAll { it.name.endsWith(".a3m") }}, + ch_boltz_model, + ch_boltz_ccd + ) + RUN_BOLTZ.out.confidence.toSortedList().multiMap{json_list -> + ids: json_list.collect{it[0].id} + json: json_list.collect{it[1]} + }.set{ch_confidence_scores} + + COLLECT_CONFIDENCE( + ch_confidence_scores.ids.map{[["id": "full_run"], it]}, + ch_confidence_scores.json + ) + + //ch_confidence_scores.ids.view() + //ch_confidence_scores.json.view() + + emit: + versions = ch_versions + msa = RUN_BOLTZ.out.msa + structures = RUN_BOLTZ.out.structures + confidence = RUN_BOLTZ.out.confidence + run_confidence = COLLECT_CONFIDENCE.out.confidence + plddt = RUN_BOLTZ.out.plddt + pdb = RUN_BOLTZ.out.pdb + +} diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 787c124..f4710c1 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -1,14 +1,37 @@ /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - IMPORT MODULES / SUBWORKFLOWS / FUNCTIONS + IMPORT LOCAL MODULES/SUBWORKFLOWS ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ -include { MULTIQC } from '../modules/nf-core/multiqc/main' +// +// MODULE: Loaded from modules/local/ +// + +/* +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + IMPORT NF-CORE MODULES/SUBWORKFLOWS +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +*/ + +// +// MODULE: Installed directly from nf-core/modules +// +include { MULTIQC } from '../modules/nf-core/multiqc/main' +include { MMSEQS_COLABFOLDSEARCH } from '../modules/local/mmseqs_colabfoldsearch' +include { PREPARE_INTERACTIONS } from '../modules/local/prepare_interactions' +include { COLLECT_CONFIDENCE } from '../modules/local/collect_confidence' +// +// SUBWORKFLOW: Consisting entirely of nf-core/modules +// include { paramsSummaryMap } from 'plugin/nf-schema' include { paramsSummaryMultiqc } from '../subworkflows/nf-core/utils_nfcore_pipeline' include { softwareVersionsToYAML } from '../subworkflows/nf-core/utils_nfcore_pipeline' -include { methodsDescriptionText } from '../subworkflows/local/utils_nfcore_wisps_pipeline' + +// +// MODULE: Boltz +// +include { RUN_BOLTZ } from '../modules/local/run_boltz' /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @@ -17,73 +40,121 @@ include { methodsDescriptionText } from '../subworkflows/local/utils_nfcore_wisp */ workflow WISPS { - + take: - ch_samplesheet // channel: samplesheet read in from --input - main: + ch_samplesheet // channel: samplesheet read from --input + mode + ch_versions // channel: [ path(versions.yml) ] + ch_boltz_ccd // channel: [ path(boltz_ccd) ] + ch_boltz_model // channel: [ path(model) ] + ch_colabfold_db // channel: [ path(colabfold_db) ] + ch_uniref30 // channel: [ path(uniref30) ] - ch_versions = Channel.empty() + main: ch_multiqc_files = Channel.empty() + + interaction_mode = mode.split(",").collect { pair -> + pair.split('-').sort().join('-') + } + + if ("all-all" in interaction_mode) { + interaction_mode = ["all-all"] + }else{ + required = interaction_mode.collect{it.split("-")}.flatten().unique() + ch_samplesheet + .map{it[0].group} + .unique() + .toList() + .subscribe{ + emitted -> { + if (required - emitted){ + log.error "The groups ${required - emitted} is not in the sample sheet!" + exit 1 + } + } + } + } - // - // Collate and save software versions - // - softwareVersionsToYAML(ch_versions) - .collectFile( - storeDir: "${params.outdir}/pipeline_info", - name: 'nf_core_' + 'pipeline_software_' + 'mqc_' + 'versions.yml', - sort: true, - newLine: true - ).set { ch_collated_versions } - + log.info "Used Interactions (Sorted): ${interaction_mode.join(',')}" + + ch_samplesheet.map{it[0]} + .combine(ch_samplesheet.map{it[0]}) + .map{[ + "id": [it[0]["id"], it[1]["id"]].min() + "-" + [it[0]["id"], it[1]["id"]].max(), + "group": [it[0]["group"], it[1]["group"]].min() + "-" + [it[0]["group"], it[1]["group"]].max(), + ]} + .filter{ it["group"] in interaction_mode || interaction_mode[0] == "all-all"} + .unique() + .set{ch_unique_pairs} - // - // MODULE: MultiQC - // - ch_multiqc_config = Channel.fromPath( - "$projectDir/assets/multiqc_config.yml", checkIfExists: true) - ch_multiqc_custom_config = params.multiqc_config ? - Channel.fromPath(params.multiqc_config, checkIfExists: true) : - Channel.empty() - ch_multiqc_logo = params.multiqc_logo ? - Channel.fromPath(params.multiqc_logo, checkIfExists: true) : - Channel.empty() + MMSEQS_COLABFOLDSEARCH ( + ch_samplesheet.filter{it[0].type == "protein"}, + ch_colabfold_db, + ch_uniref30 + ) + ch_versions = ch_versions.mix(MMSEQS_COLABFOLDSEARCH.out.versions) + + ch_input_aligned = ch_samplesheet.join(MMSEQS_COLABFOLDSEARCH.out.a3m, remainder: true) + + ch_input_aligned + .combine(ch_input_aligned) + .map{[ + [ + "id": [it[0]["id"], it[3]["id"]].min() + "-" + [it[0]["id"], it[3]["id"]].max(), + "group": [it[0]["group"], it[3]["group"]].min() + "-" + [it[0]["group"], it[3]["group"]].max(), + ], + [it[1].name, it[4].name], + [it[2] ? it[2].name : "", it[5] ? it[5].name : ""], + [it[0]["type"], it[3]["type"]], + [it[1], it[2], it[4], it[5]].findAll{it}.unique{it.toUriString()}, - summary_params = paramsSummaryMap( - workflow, parameters_schema: "nextflow_schema.json") - ch_workflow_summary = Channel.value(paramsSummaryMultiqc(summary_params)) - ch_multiqc_files = ch_multiqc_files.mix( - ch_workflow_summary.collectFile(name: 'workflow_summary_mqc.yaml')) - ch_multiqc_custom_methods_description = params.multiqc_methods_description ? - file(params.multiqc_methods_description, checkIfExists: true) : - file("$projectDir/assets/methods_description_template.yml", checkIfExists: true) - ch_methods_description = Channel.value( - methodsDescriptionText(ch_multiqc_custom_methods_description)) + ]}.set{ch_pairs} + + //ch_pairs.view() + + ch_pairs + .join(ch_unique_pairs) + .set{ch_interaction_input} + + //ch_interaction_input.view() - ch_multiqc_files = ch_multiqc_files.mix(ch_collated_versions) - ch_multiqc_files = ch_multiqc_files.mix( - ch_methods_description.collectFile( - name: 'methods_description_mqc.yaml', - sort: true - ) + PREPARE_INTERACTIONS( + ch_interaction_input.map{[it[0], it[1]]}, + ch_interaction_input.map{[it[0], it[2]]}, + ch_interaction_input.map{[it[0], it[3]]}, + ch_interaction_input.map{it[4]} ) - - MULTIQC ( - ch_multiqc_files.collect(), - ch_multiqc_config.toList(), - ch_multiqc_custom_config.toList(), - ch_multiqc_logo.toList(), - [], - [] + + PREPARE_INTERACTIONS.out.fasta + .join(ch_interaction_input) + .set{ch_boltz_input} + + RUN_BOLTZ( + ch_boltz_input.map{[it[0], it[1]]}, + ch_boltz_input.map{it[5].findAll { it.name.endsWith(".a3m") }}, + ch_boltz_model, + ch_boltz_ccd ) + RUN_BOLTZ.out.confidence.toSortedList().multiMap{json_list -> + ids: json_list.collect{it[0].id} + json: json_list.collect{it[1]} + }.set{ch_confidence_scores} - emit:multiqc_report = MULTIQC.out.report.toList() // channel: /path/to/multiqc_report.html - versions = ch_versions // channel: [ path(versions.yml) ] + COLLECT_CONFIDENCE( + ch_confidence_scores.ids.map{[["id": "full_run"], it]}, + ch_confidence_scores.json + ) + + //ch_confidence_scores.ids.view() + //ch_confidence_scores.json.view() -} + emit: + versions = ch_versions + msa = RUN_BOLTZ.out.msa + structures = RUN_BOLTZ.out.structures + confidence = RUN_BOLTZ.out.confidence + run_confidence = COLLECT_CONFIDENCE.out.confidence + plddt = RUN_BOLTZ.out.plddt + pdb = RUN_BOLTZ.out.pdb -/* -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - THE END -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -*/ +} From cf01fbf437fb27d58219200ec0ad62dbf6a98581 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Wed, 3 Sep 2025 14:26:38 +1000 Subject: [PATCH 02/70] adding batch mmseq --- conf/test_gadi.config | 2 +- main.nf | 3 +- modules/local/mmseqs_colabfoldsearch/main.nf | 21 ++- nextflow.config | 18 +- subworkflows/local/msa.nf | 156 ++++++++++++++++++ .../local/utils_nfcore_wisps_pipeline/main.nf | 1 - workflows/wisps.nf | 51 ++++-- 7 files changed, 229 insertions(+), 23 deletions(-) create mode 100644 subworkflows/local/msa.nf diff --git a/conf/test_gadi.config b/conf/test_gadi.config index df1edfb..ca8ca36 100644 --- a/conf/test_gadi.config +++ b/conf/test_gadi.config @@ -52,7 +52,7 @@ process { } resourceLimits = [ cpus: 1, - memory: '5.GB', + memory: '4.GB', time: '1.h' ] resourceLimits = [ diff --git a/main.nf b/main.nf index bf91b45..a1c8c4c 100644 --- a/main.nf +++ b/main.nf @@ -48,7 +48,8 @@ workflow NFCORE_WISPS { params.boltz_ccd, params.boltz_model, params.colabfold_db, - params.uniref30 + params.uniref30, + params.mmseq_batch_size ) ch_versions = ch_versions.mix(WISPS.out.versions) diff --git a/modules/local/mmseqs_colabfoldsearch/main.nf b/modules/local/mmseqs_colabfoldsearch/main.nf index 68d2d2c..a3e53ea 100644 --- a/modules/local/mmseqs_colabfoldsearch/main.nf +++ b/modules/local/mmseqs_colabfoldsearch/main.nf @@ -41,8 +41,27 @@ process MMSEQS_COLABFOLDSEARCH { stub: """ mkdir results - touch results/${meta.id}.a3m + if [[ "$fasta" == *.csv ]]; then + line_num=0 + while IFS=, read -r firstcol rest; do + line_num=\$((line_num + 1)) + # Skip the first line (header) + if [ "\$line_num" -eq 1 ]; then + continue + fi + # Skip empty first column + [ -z "\$firstcol" ] && continue + + # Clean filename (letters, numbers, dash, underscore) + safe_name=\$(echo "\$firstcol" | tr -cd '[:alnum:]_-') + + touch "results/\${safe_name}.a3m" + done < "$fasta" + else + touch results/${meta.id}.a3m + fi + cat <<-END_VERSIONS > versions.yml "${task.process}": colabfold_search: \$(conda run -n colabfold pip list | grep "^colabfold" | awk '{print \$2}') diff --git a/nextflow.config b/nextflow.config index 1b1bf29..dcfccf8 100644 --- a/nextflow.config +++ b/nextflow.config @@ -13,7 +13,7 @@ params { // Input options input = null mode = "all-all" - + mmseq_batch_size = 10 // MultiQC options multiqc_config = null @@ -186,14 +186,14 @@ env { } // Set bash options -process.shell = """\ -bash - -set -e # Exit if a tool returns a non-zero status/exit code -set -u # Treat unset variables and parameters as an error -set -o pipefail # Returns the status of the last command to exit with a non-zero status or zero if all successfully execute -set -C # No clobber - prevent output redirection from overwriting files. -""" +process.shell = [ + "bash", + "-C", // No clobber - prevent output redirection from overwriting files. + "-e", // Exit if a tool returns a non-zero status/exit code + "-u", // Treat unset variables and parameters as an error + "-o", // Returns the status of the last command to exit.. + "pipefail" // ..with a non-zero status or zero if all successfully execute +] // Disable process selector warnings by default. Use debug profile to enable warnings. nextflow.enable.configProcessNamesValidation = false diff --git a/subworkflows/local/msa.nf b/subworkflows/local/msa.nf new file mode 100644 index 0000000..e30b989 --- /dev/null +++ b/subworkflows/local/msa.nf @@ -0,0 +1,156 @@ +// +// Post processing analysis for the predicted structures +// + +// +// SUBWORKFLOW: Consisting entirely of nf-core/modules +// +include { MMSEQS_COLABFOLDSEARCH } from '../../modules/local/mmseqs_colabfoldsearch' + +workflow MSA { + + take: + ch_samplesheet + ch_colabfold_db // channel: path(colabfold_db) + ch_uniref30 // channel: path(uniref30) + mmseq_batch_size + + main: + ch_versions = Channel.empty() + ch_a3m = Channel.empty() + + ch_samplesheet + .branch { + fasta: it[1].extension == "fasta" || it[1].extension == "fa" + yaml: it[1].extension == "yaml" || it[1].extension == ".yml" + json: it[1].extension == "json" + } + .set{ch_input} + + ch_input.yaml + .map{ + [it[0], "${it[0].id},${getYamlSequences(it[1].text).collect { it.sequence }.join(':')}"] + } + .set{ch_yaml_seqs} + + if (mmseq_batch_size > 1){ + def batch_itr = 0 + + ch_input.fasta + .map{ + "${it[0].id},${getFastaSequences(it[1].text).collect { it.sequence }.join(':')}" + } + .mix( + ch_yaml_seqs.map{it[1]} + ) + .buffer( size: mmseq_batch_size, remainder: true ) + .collectFile { + batch_itr += 1; + [ "input_seqs_${batch_itr}.csv", "id,sequence\n" + it.join("\n") + '\n' ] + } + .map{[["id": it.baseName], it]} + .set {ch_input_seqs} + }else{ + ch_input.fasta + .mix( + ch_yaml_seqs + .collectFile { + [ "${it[0].id}.csv", "id,sequence\n" + it[1].join("\n") + '\n' ] + } + .map{[["id": it.baseName], it]} + .join( + ch_yaml_seqs.map{[it[0].id, it[0]]} + ) + .map{[it[2], it[1]]} + ).set{ch_input_seqs} + } + ch_input_seqs.view() + + MMSEQS_COLABFOLDSEARCH ( + ch_input_seqs, + ch_colabfold_db, + ch_uniref30 + ) + ch_versions = ch_versions.mix(MMSEQS_COLABFOLDSEARCH.out.versions) + + ch_a3m = ch_a3m.mix( + ch_input.fasta.mix(ch_input.yaml) + .map{[it[1].baseName, it[0]]} + .combine( + MMSEQS_COLABFOLDSEARCH.out.a3m + .map{it[1]} + .flatten() + .map {[it.baseName, it]}, + by:0 + ) + .map{[it[1], it[2]]} + ) + //MMSEQS_COLABFOLDSEARCH.out.a3m.view() + //ch_a3m.view() + + emit: + formated_input = ch_input.fasta.mix(ch_input.yaml) + a3m = ch_a3m + versions = ch_versions +} + +def getYamlSequences(yamlData) { + List enrichedEntries = [] + Map currentEntry = [:] + inSequences = false + yamlData.split("\n").each { line -> + def trimmed = line.trim() + + // Detect start of sequences section + if (trimmed == 'sequences:') { + inSequences = true + return + } + if (inSequences && !line.startsWith(' ') && !trimmed.isEmpty()) { + inSequences = false + return + } + if (!inSequences){ + return + } + + + if (trimmed.startsWith('-') && trimmed.endsWith(':')) { + if (!currentEntry.isEmpty()) { + enrichedEntries << currentEntry + } + currentEntry = ['type': trimmed[1..-2]] + }else{ + def (key, value) = trimmed.split(':', 2)*.trim() + currentEntry[key] = value + } + } + if (!currentEntry.isEmpty()) { + enrichedEntries << currentEntry + } + return enrichedEntries +} + +def getFastaSequences(fastaData) { + List fastaEntries = [] + String currentId = null + StringBuilder currentSeq = new StringBuilder() + + fastaData.split("\n").each { line -> + if (line.startsWith(">")) { + if (currentId) { + fastaEntries << [id: currentId, sequence: currentSeq.toString()] + } + currentId = line[1..-1].trim() // Remove '>' and trim + currentSeq = new StringBuilder() + } else { + currentSeq.append(line.trim()) + } + } + + if (currentId) { + fastaEntries << [id: currentId, sequence: currentSeq.toString()] + } + + return fastaEntries +} \ No newline at end of file diff --git a/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf b/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf index c113275..784c656 100644 --- a/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf +++ b/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf @@ -225,4 +225,3 @@ def methodsDescriptionText(mqc_methods_yaml) { return description_html.toString() } - diff --git a/workflows/wisps.nf b/workflows/wisps.nf index f4710c1..23364ca 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -18,7 +18,6 @@ // MODULE: Installed directly from nf-core/modules // include { MULTIQC } from '../modules/nf-core/multiqc/main' -include { MMSEQS_COLABFOLDSEARCH } from '../modules/local/mmseqs_colabfoldsearch' include { PREPARE_INTERACTIONS } from '../modules/local/prepare_interactions' include { COLLECT_CONFIDENCE } from '../modules/local/collect_confidence' // @@ -27,12 +26,20 @@ include { COLLECT_CONFIDENCE } from '../modules/local/collect_confidence' include { paramsSummaryMap } from 'plugin/nf-schema' include { paramsSummaryMultiqc } from '../subworkflows/nf-core/utils_nfcore_pipeline' include { softwareVersionsToYAML } from '../subworkflows/nf-core/utils_nfcore_pipeline' +include { MSA } from '../subworkflows/local/msa' // // MODULE: Boltz // include { RUN_BOLTZ } from '../modules/local/run_boltz' +// +// FUNCTIONS +// +include { getFastaSequences } from '../subworkflows/local/msa' +include { getYamlSequences } from '../subworkflows/local/msa' + + /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ RUN MAIN WORKFLOW @@ -49,6 +56,7 @@ workflow WISPS { ch_boltz_model // channel: [ path(model) ] ch_colabfold_db // channel: [ path(colabfold_db) ] ch_uniref30 // channel: [ path(uniref30) ] + mmseq_batch_size // number main: ch_multiqc_files = Channel.empty() @@ -56,7 +64,6 @@ workflow WISPS { interaction_mode = mode.split(",").collect { pair -> pair.split('-').sort().join('-') } - if ("all-all" in interaction_mode) { interaction_mode = ["all-all"] }else{ @@ -74,9 +81,7 @@ workflow WISPS { } } } - log.info "Used Interactions (Sorted): ${interaction_mode.join(',')}" - ch_samplesheet.map{it[0]} .combine(ch_samplesheet.map{it[0]}) .map{[ @@ -87,15 +92,41 @@ workflow WISPS { .unique() .set{ch_unique_pairs} - MMSEQS_COLABFOLDSEARCH ( - ch_samplesheet.filter{it[0].type == "protein"}, + ch_samplesheet + .branch { + fasta: it[1].extension == "fasta" || it[1].extension == "fa" + it[0].cnt = getFastaSequences(it[1].text).size() + return it + yaml: it[1].extension == "yaml" || it[1].extension == ".yml" + it[0].cnt = getYamlSequences(it[1].text).size() + return it + json: it[1].extension == "json" + } + .set{ch_input} + + + MSA ( + ch_input.fasta + .mix(ch_input.json) + .mix(ch_input.yaml) + .filter{it[0].type == "protein"}, ch_colabfold_db, - ch_uniref30 + ch_uniref30, + mmseq_batch_size ) - ch_versions = ch_versions.mix(MMSEQS_COLABFOLDSEARCH.out.versions) - - ch_input_aligned = ch_samplesheet.join(MMSEQS_COLABFOLDSEARCH.out.a3m, remainder: true) + ch_versions = ch_versions.mix(MSA.out.versions) + ch_input.fasta + .mix(ch_input.json) + .mix(ch_input.yaml) + .map{[it[0].id, it]} + .join( + MSA.out.a3m.map{[it[0].id, it]} + , remainder: true + ) + .map{[it[2][0], it[1][1], it[2][1]]} + .set{ch_input_aligned} + ch_input_aligned .combine(ch_input_aligned) .map{[ From a617b2b27ce962ffd5c6cd594c4f266eb9465049 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Fri, 26 Sep 2025 22:41:58 +1000 Subject: [PATCH 03/70] major updates --- bin/extract_metrics.py | 462 +++++++++ bin/ipsae.py | 971 ++++++++++++++++++ bin/latest.py | 787 ++++++++++++++ bin/msa_manager.py | 125 +++ bin/utils.py | 112 ++ bin/zt-search.py | 802 +++++++++++++++ conf/gadi.config | 68 ++ conf/modules.config | 28 +- conf/test_gadi.config | 54 +- main.nf | 27 +- modules/local/colabfold_batch/Dockerfile | 5 + modules/local/colabfold_batch/main.nf | 81 ++ .../local/data_convertor/boltz_fasta/main.nf | 129 +++ .../local/data_convertor/fasta2json/main.nf | 74 ++ .../local/data_convertor/fasta2yaml/main.nf | 72 ++ modules/local/ipsae/main.nf | 46 + modules/local/mmseqs_colabfoldsearch/main.nf | 11 +- modules/local/msa_manager/split_msa.nf | 42 + modules/local/prepare_interactions.nf | 1 + modules/local/run_alphafold3/Dockerfile | 59 ++ modules/local/run_alphafold3/main.nf | 95 ++ modules/local/run_boltz/Dockerfile | 25 + modules/local/run_boltz/main.nf | 93 +- nextflow.config | 13 +- nextflow_schema.json | 89 ++ subworkflows/local/msa.nf | 22 +- .../local/utils_nfcore_wisps_pipeline/main.nf | 21 +- workflows/interactions.nf | 138 --- workflows/wisps.nf | 293 ++++-- 29 files changed, 4486 insertions(+), 259 deletions(-) create mode 100755 bin/extract_metrics.py create mode 100755 bin/ipsae.py create mode 100644 bin/latest.py create mode 100755 bin/msa_manager.py create mode 100755 bin/utils.py create mode 100755 bin/zt-search.py create mode 100644 conf/gadi.config create mode 100644 modules/local/colabfold_batch/Dockerfile create mode 100644 modules/local/colabfold_batch/main.nf create mode 100644 modules/local/data_convertor/boltz_fasta/main.nf create mode 100644 modules/local/data_convertor/fasta2json/main.nf create mode 100644 modules/local/data_convertor/fasta2yaml/main.nf create mode 100644 modules/local/ipsae/main.nf create mode 100644 modules/local/msa_manager/split_msa.nf create mode 100644 modules/local/run_alphafold3/Dockerfile create mode 100644 modules/local/run_alphafold3/main.nf create mode 100644 modules/local/run_boltz/Dockerfile delete mode 100644 workflows/interactions.nf diff --git a/bin/extract_metrics.py b/bin/extract_metrics.py new file mode 100755 index 0000000..c8db726 --- /dev/null +++ b/bin/extract_metrics.py @@ -0,0 +1,462 @@ +#!/usr/bin/env python +import pickle +import os +import argparse +import json +#import torch moved to a conditional import since too bulky import if not used +import numpy as np +import csv +import string +from utils import plddt_from_struct_b_factor, get_chain_ids + +# TODO: Issue #309, make into a poper separate process, it its own module so that dependencies can be managed better +# TODO: Need a sense of ranking, so that metrics can be traced back to correct model structure, even if they're not in sequential order. The enumerates() here are not sufficient. +# Needs to be program-dependent, (see item below). +# TODO: look into have a --prog argument that could set filenames etc, logically seperate it? +# {name}_{prog}_{metric}.tsv might be easier for MultiQC to parse a complex workdir, than without the .prog +# TODO: read --prog from ${meta.model} in the NextFlow pipes. This also allows case switching in a proper EXTRACT_METRICS process. +# E.g. in main.nf of EXTACT_METRICS process, we could have: +# match ${meta.mode}: +# case 'alphafold2': +# ... +# case 'rosettafold_all_atom': +# ... +#... +# ^ overwrought with duplication, but can catch program specific weirdness, and lower barrier to adding new programs in the future. + +# TODO: Chain-wise iPTM since the relevant interface might not always be the average of all. +# Would complete Issue #308 +# Proposed format is pair-interfaces in rows, structure inference number in cols: https://github.com/nf-core/proteinfold/pull/312#issuecomment-2917709432 +# KR - changed to have both sides of the matrix, because it's not symmetrical (see comment in Issue #306) + +# Mapping of characters to integers for MSA parsing. +# 20 is for unknown characters, and 21 is for gaps. +AA_to_int = { + "A": 0, "C": 1, "D": 2, "E": 3, "F": 4, "G": 5, "H": 6, "I": 7, "K": 8, "L": 9, + "M": 10, "N": 11, "P": 12, "Q": 13, "R": 14, "S": 15, "T": 16, "V": 17, "W": 18, "Y": 19, + ".": 20, "-": 21 +} + +def a3m_to_int(a3m_file): + """ + Convert an A3M MSA representation into an integer representation (0-21). + """ + with open(a3m_file, "r") as f: + msa = f.read() + + # Convert each sequence in the MSA + int_sequences = [] + for idx, line in enumerate(msa.splitlines()): + if idx == 0 and not line.startswith(">"): # If there's an additional header (non-FASTA) skip it. E.g ColabFold + continue + + if not line.startswith(">"): # Ignore header lines + filtered_line = ''.join(char for char in line if not char.islower()) # Remove inserts (lower-case chars) in a3m + int_sequence = [AA_to_int.get(char.upper(), 20) for char in filtered_line] + int_sequences.append(int_sequence) + + int_sequences_array = np.array(int_sequences, dtype=object) + return int_sequences_array + +def format_msa_rows(msa_data): + return [[str(x) for x in val] for val in msa_data] + +def format_pae_rows(pae_data): + return [[f"{num:.4f}" for num in row] for row in pae_data] + +def format_iptm_rows(chain_pair_entries, chain_ids=None): + """ + Format iPTM data into a list of rows for writing to a TSV file. + Each row contains: the chain-pair in uppercase, e.g. "A:B", "B:A", A:C", etc. and then the iPTM value formatted to 4 decimal places. + """ + def idx_to_letter(idx): + """ Convert the index integer of the matrix to a letter representation that wraps to double representation, e.g. 0 -> A, 1 -> B, ..., 25 -> Z, 26 -> AA, 27 -> AB, etc. + This is somewhat compatible with how protein structure chain names are numbered by biochemists. + But we should move away from fixed-format PDB files -- we have nothing to lose but our chains.""" + result = "" + while idx >= 0: + result = string.ascii_uppercase[idx % 26] + result + idx = idx // 26 - 1 + if idx < 0: + break + return result + + if chain_ids: + #would be better with some model_id sorting + iptm_rows = [[""]+[f"{chain_ids[idx[0]]}:{chain_ids[idx[1]]}" for idx, val in next(iter(chain_pair_entries.values()))]] + else: + iptm_rows = [[""]+[f"{idx_to_letter(idx[0])}:{idx_to_letter(idx[1])}" for idx, val in next(iter(chain_pair_entries.values()))]] + + for model_idx, chain_pair_entries_values in chain_pair_entries.items(): + iptm_rows.append([model_idx]+[f"{val:.4f}" for idx, val in chain_pair_entries_values]) + + return [list(row) for row in zip(*iptm_rows)] + + +def chain_iptm_matrix_to_pairs(iptm_matrix): + """ + Convert a chain-wise iPTM matrix to pair values by taking off-diagonal elements. + """ + # From AlphaFold3 output docs: + # 'chain_pair_iptm': An [num_chains, num_chains] array. + # Off-diagonal element (i, j) of the array contains the ipTM restricted to tokens from chains i and j. + # Diagonal element (i, i) contains the pTM restricted to chain i. + return [(idx, val) for idx, val in np.ndenumerate(iptm_matrix) if idx[0] != idx[1]] + +def chainwise_iptm_matrix_to_ptms(iptm_matrix): + return [(idx, val) for idx, val in np.ndenumerate(iptm_matrix) if idx[0] == idx[1]] + +def write_tsv(file_path, rows): + with open(file_path, 'w') as out_f: + writer = csv.writer(out_f, delimiter='\t') + writer.writerows(rows) + +def extract_structs_plddt_to_tsv(name, structures): + """ + Write out a tsv file contain pLDDTs for reading by MultiQC in nf-core/proteinfold + Uses utils function with BioPython PDB package to extract residue pLDDT values from the b-factor column. + """ + plddt_cols = [plddt_from_struct_b_factor(structure) for structure in structures] + res_counts = [len(plddt_col) for plddt_col in plddt_cols] + + if len(set(res_counts)) != 1: + raise ValueError("Not all structures have the same number of residues!") + + rank_names = [f"rank_{i}" for i in range(len(structures))] + # Create header as the first row + plddt_rows = [["Positions"] + rank_names] + res_id_col = list(range(len(plddt_cols[0]))) + plddt_rows.extend(zip(res_id_col, *plddt_cols)) # Combine lists column-wise to make rows + write_tsv(f"{name}_plddt.tsv", plddt_rows) + +def read_pkl(name, pkl_files): + """ + Adapted from the Galaxy AlphaFold tool (https://github.com/usegalaxy-au/tools-au/blob/de94df520c8dc7b8652aedb92e90f6ebb312f95f/tools/alphafold/scripts/outputs.py), originally authored by @neoformit and @graceahall and funded by Australian Biocommons and QCIF Australia. + """ + ptm_data = {} + iptm_data = {} + for pkl_file in pkl_files: + print(f"Processing {pkl_file}") + data = pickle.load(open(pkl_file, "rb")) + + # Process MSA data + if pkl_file.endswith("final_features.pkl"): # HelixFold3 - This one must be first + write_tsv(f"{name}_msa.tsv", format_msa_rows(data["feat"]["msa"])) + elif pkl_file.endswith("features.pkl"): # AlphaFold2.3 + # TODO: AlphaFold2.3 fills end rows with 0s in AlpahFold muliter for an alanine nf-core/proteinfold Issue #300 + write_tsv(f"{name}_msa.tsv", format_msa_rows(data["msa"])) + # AlphaFold2.3 non-summary, for each pkl. TODO: Need to either read in ranking_debug.json to get the ranking order, or do it later in the workflow. + else: + model_info = os.path.basename(pkl_file).replace("result_", "").replace(".pkl", "") + #TODO: Make this explicit input + with open(os.path.join(os.path.dirname(pkl_file),"ranking_debug.json")) as f: + ranking_data = json.load(f)['order'] + model_id = ranking_data.index(model_info) + if 'predicted_aligned_error' not in data.keys(): + print(f"No PAE output in {pkl_file}, it was likely a monomer calculation") + else: + write_tsv(f"{name}_{model_id}_pae.tsv", format_pae_rows(data["predicted_aligned_error"])) + + if 'ptm' not in data.keys(): + print(f"No pTM/iPTM output in {pkl_file}, it was likely a monomer calculation") + else: + #with open(f"{name}_{model_id}_ptm.tsv", 'w') as f: + # f.write(f"{np.round(data['ptm'],3)}\n") + #with open(f"{name}_{model_id}_iptm.tsv", 'w') as f: + # f.write(f"{np.round(data['iptm'],3)}\n") + ptm_data[f"{model_id}"] = f"{np.round(data['ptm'],3)}\n" + iptm_data[f"{model_id}"] = f"{np.round(data.get('iptm',0.),3)}\n" + if ptm_data: + ptm_rows = [[k, v.strip()] for k, v in ptm_data.items()] + write_tsv(f"{name}_ptm.tsv", ptm_rows) + + if iptm_data: + iptm_rows = [[k, v.strip()] for k, v in iptm_data.items()] + write_tsv(f"{name}_iptm.tsv", iptm_rows) + + + +def read_a3m(name, a3m_files): + # RosettaFold-All-Atom + #TODO: DRY with unpaired below for Boltz + msa_rows = {} + for a3m_file in a3m_files: #Should already be alphabetical by chain + msa_rows[a3m_file] = a3m_to_int(a3m_file) + + final_rows = [] + temp_row = [] + for a3m_file in a3m_files: + temp_row.extend(msa_rows[a3m_file][0]) + final_rows.append(temp_row) + + # Un-paired TODO: get pairing code from RF-AA source + # https://github.com/baker-laboratory/RoseTTAFold-All-Atom/blob/main/rf2aa/data/parsers.py#L405 + msa_widths = [len(msa_rows[chain][0]) for chain in a3m_files] + msa_heights = [len(msa_rows[chain]) for chain in a3m_files] + + cum_total_rows = np.cumsum(msa_heights) + for row_idx in range(cum_total_rows[-1]): + temp_row = [] + + for i, chain in enumerate(a3m_files): + msa = msa_rows[chain] + width = msa_widths[i] + if i == 0: + minrow = 0 + else: + minrow = cum_total_rows[i-1] + maxrow = cum_total_rows[i] + + if minrow <= row_idx < maxrow: + msa_row_idx = row_idx - minrow + temp_row.extend(msa[msa_row_idx]) + else: + temp_row.extend(["21"] * width) #gap + final_rows.append(temp_row) + + write_tsv(f"{name}_msa.tsv", format_msa_rows(final_rows)) + +def read_npz(name, npz_files): + for idx, npz_file in enumerate(npz_files): + data = np.load(npz_file) + #Boltz PAE files if --write_full_pae is used + if npz_file.split('/')[-1].startswith('pae') and npz_file.endswith('.npz'): + model_id = os.path.basename(npz_file).split('_model_')[-1].split('.npz')[0] + write_tsv(f"{name}_{model_id}_pae.tsv", format_pae_rows(data["pae"])) + +# Boltz MSA processing +def read_csv(name, csv_files): + if not os.path.isfile(csv_files[0]): return #TODO: Fix temporary workaround + msa_rows = {} + unpaired_msa_rows = {} + for csv_file in sorted(csv_files, key=lambda x: int(x.split('_')[-1].split('.csv')[0])): + msa_lines = [] + unpaired_msa_lines = [] + with open(csv_file) as f: + f.readline() + for line in f: + if line.split(',')[0] == '-1' and len(csv_files)>1: #Server MSA appears as un-paired + unpaired_msa_lines.append(''.join(c for c in line.strip('\n').split(',')[1] if not c.islower())) + else: + msa_lines.append(''.join(c for c in line.strip('\n').split(',')[1] if not c.islower())) + msa_rows[csv_file.split('_')[-1].split('.csv')[0]] = [[str(AA_to_int.get(residue, 20)) for residue in line] for line in msa_lines] + unpaired_msa_rows[csv_file.split('_')[-1].split('.csv')[0]] = [[str(AA_to_int.get(residue, 20)) for residue in line] for line in unpaired_msa_lines] + + # Get Chain to MSA mapping (ie non-redundant for homomers) + # TODO: Make this explicit input + with open(f'boltz_results_{name}/processed/manifest.json') as f: + manifest = json.load(f) + + final_rows = [] + # Paired + for i in range(len(msa_rows["0"])): #The number of paired lines is common to all MSAs + temp_row = [] + #This needs to be fixed if inference is batched in future. + for chain in manifest["records"][0]["chains"]: + j = chain["msa_id"].split("_")[-1] + temp_row.extend(msa_rows[j][i]) + final_rows.append(temp_row) + + # Un-paired + msa_widths = [len(msa_rows[chain["msa_id"].split("_")[-1]][0]) for chain in manifest["records"][0]["chains"]] + msa_heights = [len(unpaired_msa_rows[chain["msa_id"].split("_")[-1]]) for chain in manifest["records"][0]["chains"]] + + cum_total_rows = np.cumsum(msa_heights) + + for row_idx in range(cum_total_rows[-1]): + temp_row = [] + + for i, chain in enumerate(manifest["records"][0]["chains"]): + msa = unpaired_msa_rows[chain["msa_id"].split("_")[-1]] + width = msa_widths[i] + if i == 0: + minrow = 0 + else: + minrow = cum_total_rows[i-1] + maxrow = cum_total_rows[i] + + if minrow <= row_idx < maxrow: + msa_row_idx = row_idx - minrow + temp_row.extend(msa[msa_row_idx]) + else: + temp_row.extend(["21"] * width) #gap + final_rows.append(temp_row) + + write_tsv(f"{name}_msa.tsv", final_rows) + +def read_json(name, json_files): + ptm_data = {} + iptm_data = {} + chain_pair_iptm_data = {} # For iPTM data to be converted into formatted pairs with non-self elements + chain_pair_entries = {} + chainwise_ptms = {} + chain_ids = [] + + for idx, json_file in enumerate(json_files): + with open(json_file, 'r') as f: + data = json.load(f) + if json_file.endswith("_data.json"): #AF3 output with MSA info + # Can't just used format_msa_rows since there's FASTA headers in the json content + paired_msa_rows = [] + unpaired_msa_rows = [] + for chain in data['sequences']: + unpaired_MSA = chain['protein']['unpairedMsa'] + unpaired_msa_lines = [''.join(c for c in line if not c.islower()) for line in unpaired_MSA.split("\n") if line.strip() and not line.startswith(">")] + unpaired_msa_rows.append([[str(AA_to_int.get(residue, 20)) for residue in line] for line in unpaired_msa_lines]) + paired_MSA = chain['protein']['pairedMsa'] + paired_msa_lines = [''.join(c for c in line if not c.islower()) for line in paired_MSA.split("\n") if line.strip() and not line.startswith(">")] + paired_msa_rows.append([[str(AA_to_int.get(residue, 20)) for residue in line] for line in paired_msa_lines]) + + chains = len(data['sequences']) + final_rows = [] + # Paired + for i in range(len(paired_msa_rows[0])): #The number of paired lines is common to all MSAs + temp_row = [] + #This needs to be fixed if inference is batched in future. + for j in range(chains): + temp_row.extend(paired_msa_rows[j][i]) + final_rows.append(temp_row) + + # Un-paired + msa_widths = [len(paired_msa_rows[chain][0]) for chain in range(chains)] + msa_heights = [len(unpaired_msa_rows[chain]) for chain in range(chains)] + + cum_total_rows = np.cumsum(msa_heights) + + for row_idx in range(cum_total_rows[-1]): + temp_row = [] + + for i in range(chains): + msa = unpaired_msa_rows[i] + width = msa_widths[i] + if i == 0: + minrow = 0 + else: + minrow = cum_total_rows[i-1] + maxrow = cum_total_rows[i] + if minrow <= row_idx < maxrow: + msa_row_idx = row_idx - minrow + temp_row.extend(msa[msa_row_idx]) + else: + temp_row.extend(["21"] * width) #gap + final_rows.append(temp_row) + write_tsv(f"{name}_msa.tsv", final_rows) + #AF3 output with PAE info, or HF3 PAE data. TODO: Need to make sure the workflow points to [protein]/[protein]_rank1/all_results.json + + # TODO: I think I need to capture model_id and inference_id -- MUST FIX since this is so fragile and will be different for different programs. + #if '_alphafold2_ptm_model_' in json_file: # ColabFold, multimer or monomer + ## Might want to cut more if I just want ${meta.id}_[metric].tsv + # model_id = os.path.basename(json_file) + # print(model_id) + if 'all_results' in json_file: # Individual predictions in HF3 + model_id = int(os.path.dirname(json_file).split('-rank')[-1]) #Use re-ranked output + if 'predictions' in json_file: # Boltz-1 confidences in predictions/[protein]/confidence_[protein]_model_*.json + # TODO: haven't tested this for multiple models with --diffusion_samples + model_id = os.path.basename(json_file).split('_model_')[-1].split('.json')[0] + #TODO: Fix this for AF3 - the top-ranked files are in the top-level directory + if 'confidences' in json_file: #Prevent crash when model_id is not defined + #model_id = os.path.basename(json_file).split('confidences_')[-1].split('.json')[0] + model_id = 0 + + if "pae" not in data.keys(): + print(f"No PAE output in {json_file}, it was likely a monomer calculation") + else: + write_tsv(f"{name}_{model_id}_pae.tsv", format_pae_rows(data["pae"])) + + if 'ptm' not in data.keys(): + print(f"No pTM/iPTM output in {json_file}, it was likely a monomer calculation") + #This message should change - currently called on boltz files not expected to contain ptm + else: + ptm_data[model_id] = f"{np.round(data['ptm'],3)}\n" + + if 'iptm' not in data.keys(): + print(f"No pTM/iPTM output in {json_file}, it was likely a monomer calculation") + else: + if data['iptm']: #ie not null + iptm_data[model_id] = f"{np.round(data['iptm'],3)}\n" + + if 'chain_pair_iptm' not in data.keys() and 'pair_chains_iptm' not in data.keys(): + print(f"No chain-wise iPTM output in {json_file}, it was likely a monomer calculation") + else: + if 'chain_pair_iptm' in data.keys(): + chain_pair_iptm_data = data['chain_pair_iptm'] + chain_iptm_matrix = np.array(chain_pair_iptm_data) + elif 'pair_chains_iptm' in data.keys(): #Boltz key + chain_pair_iptm_data = data['pair_chains_iptm'] + # casting to int works for sorting boltz - need to carefully check other modes + chain_iptm_matrix = np.array([[chain_pair_iptm_data[row][col] for col in sorted(chain_pair_iptm_data[row], key=int)] for row in sorted(chain_pair_iptm_data, key=int)]) + basename = os.path.basename(json_file) + dirname = os.path.dirname(json_file) + pdb_name = ".".join(basename[11:].split('.')[:-1])+'.pdb' #TODO: Fix magic number + chain_ids = get_chain_ids(os.path.join(dirname,pdb_name)) + else: + raise ValueError("No chain-wise iPTM data found in the JSON file.") + + chain_pair_entries[model_id] = chain_iptm_matrix_to_pairs(chain_iptm_matrix) + chainwise_ptms[model_id] = chainwise_iptm_matrix_to_ptms(chain_iptm_matrix) + + if chainwise_ptms: + write_tsv(f"{name}_chainwise_ptm.tsv", format_iptm_rows(chainwise_ptms, chain_ids=chain_ids)) + + if chain_pair_entries: + write_tsv(f"{name}_chainwise_iptm.tsv", format_iptm_rows(chain_pair_entries, chain_ids=chain_ids)) + + if ptm_data: + ptm_rows = [[k, v.strip()] for k, v in sorted(ptm_data.items(), key=lambda x: x[0])] + write_tsv(f"{name}_ptm.tsv", ptm_rows) + + if iptm_data: + iptm_rows = [[k, v.strip()] for k, v in sorted(iptm_data.items(), key=lambda x: x[0])] + write_tsv(f"{name}_iptm.tsv", iptm_rows) + + +def read_pt(name, pt_files): + import torch # moved to a conditional import since too bulky import if not used + #TODO: Handle this better when refactored - Is this just RFAA?? + for pt_file in pt_files: + with open(pt_file, 'rb') as f: # TODO: point to [protein]_aux.pt + data = torch.load(f, map_location="cpu") + if 'pae' in data: + # The pt file contains a tensor that needs to be cast as an array + # Squeeze leading dimension (batch?) + write_tsv(f"{name}_0_pae.tsv", format_pae_rows(np.squeeze(data["pae"].numpy()))) + break + +def read_colabfold_paes(name, colabfold_pae_fn): + with open(colabfold_pae_fn) as f: + data = json.load(f) + pae = data["predicted_aligned_error"] + write_tsv(f"{name}_0_pae.tsv", format_pae_rows(pae)) + +def main(): + parser = argparse.ArgumentParser() + parser.add_argument("--pkls", dest="pkls", required=False, nargs="+") # For reading both HelixFold3 and AlphaFold2 MSA formats + parser.add_argument("--npzs", dest="npzs", required=False, nargs="+") # For reading the Boltz-1 PAE formats. TODO: Boltz-1 MSA not implemented (go straight to .a3m file), implement + parser.add_argument("--a3ms", dest="a3ms", required=False, nargs="+") # For reading the RosettaFold-All-Atom, ColabFold MSA formats + parser.add_argument("--csvs", dest="csvs", required=False, nargs="+") # For reading boltz csvs + parser.add_argument("--jsons", dest="jsons", required=False, nargs="+") # For reading the AF3 MSA & PAE, HF3 PAE + parser.add_argument("--colabfold_pae_fn", required=False) + parser.add_argument("--pts", dest="pts", required=False, nargs="+") # For read RFAA pytorch model to get PAE data + parser.add_argument("--structs", dest="structs", required=False, nargs="+") + parser.add_argument("--name", default="untitled", dest="name") # might need a --name $meta.id + args = parser.parse_args() + + if args.pkls: + read_pkl(args.name, args.pkls) + if args.a3ms: + read_a3m(args.name, args.a3ms) + if args.csvs: + read_csv(args.name, args.csvs) + if args.npzs: + read_npz(args.name, args.npzs) + if args.jsons: + read_json(args.name, args.jsons) + if args.pts: + read_pt(args.name, args.pts) + if args.structs: + extract_structs_plddt_to_tsv(args.name, args.structs) + if args.colabfold_pae_fn: + read_colabfold_paes(args.name, args.colabfold_pae_fn) + +if __name__ == "__main__": + main() diff --git a/bin/ipsae.py b/bin/ipsae.py new file mode 100755 index 0000000..bca9b42 --- /dev/null +++ b/bin/ipsae.py @@ -0,0 +1,971 @@ +#!/usr/bin/env python +# ipsae.py +# script for calculating the ipSAE score for scoring pairwise protein-protein interactions in AlphaFold2 and AlphaFold3 models +# https://www.biorxiv.org/content/10.1101/2025.02.10.637595v1 + +# Also calculates: +# pDockQ: Bryant, Pozotti, and Eloffson. https://www.nature.com/articles/s41467-022-28865-w +# pDockQ2: Zhu, Shenoy, Kundrotas, Elofsson. https://academic.oup.com/bioinformatics/article/39/7/btad424/7219714 +# LIS: Kim, Hu, Comjean, Rodiger, Mohr, Perrimon. https://www.biorxiv.org/content/10.1101/2024.02.19.580970v1 + +# Roland Dunbrack +# Fox Chase Cancer Center +# version 3 +# April 6, 2025 +# MIT license: script can be modified and redistributed for non-commercial and commercial use, as long as this information is reproduced. + +# includes support for Boltz1 structures and structures with nucleic acids + +# It may be necessary to install numpy with the following command: +# pip install numpy + +# Usage: + +# python ipsae.py +# python ipsae.py +# python ipsae.py +# +# All output files will be in same path/folder as cif or pdb file + +import sys, os, math +import json +import numpy as np +np.set_printoptions(threshold=np.inf) # for printing out full numpy arrays for debugging + + +# Input and output files and parameters + +# Ensure correct usage +if len(sys.argv) < 5: + print("Usage for AF2:") + print(" python ipsae.py ") + print(" python ipsae.py RAF1_KSR1_scores_rank_001_alphafold2_multimer_v3_model_4_seed_003.json RAF1_KSR1_unrelaxed_rank_001_alphafold2_multimer_v3_model_4_seed_003.pdb 10 10") + print("") + print("Usage for AF3:") + print(" python ipsae.py ") + print(" python ipsae.py fold_aurka_tpx2_full_data_0.json fold_aurka_tpx2_model_0.cif 10 10") + print("") + print("Usage for Boltz1:") + print(" python ipsae.py ") + print(" python ipsae.py pae_AURKA_TPX2_model_0.npz AURKA_TPX2_model_0.cif 10 10") + sys.exit(1) + +pae_file_path = sys.argv[1] +pdb_path = sys.argv[2] +pae_cutoff = float(sys.argv[3]) +dist_cutoff = float(sys.argv[4]) +pae_string = str(int(pae_cutoff)) +if pae_cutoff<10: pae_string="0"+pae_string +dist_string = str(int(dist_cutoff)) +if dist_cutoff<10: dist_string="0"+dist_string + +#pae_AURKA_TPX2_model_0.npz + +if ".pdb" in pdb_path: + pdb_stem=pdb_path.replace(".pdb","") + path_stem = f'{pdb_path.replace(".pdb","")}_{pae_string}_{dist_string}' + af2 = True + af3 = False + boltz1 = False + cif = False +elif ".cif" in pdb_path and pae_file_path.endswith(".json"): + pdb_stem=pdb_path.replace(".cif","") + path_stem = f'{pdb_path.replace(".cif","")}_{pae_string}_{dist_string}' + af2 = False + af3 = True + boltz1 = False + cif = True +elif ".cif" in pdb_path and pae_file_path.endswith(".npz"): + pdb_stem=pdb_path.replace(".cif","") + path_stem = f'{pdb_path.replace(".cif","")}_{pae_string}_{dist_string}' + af2 = False + af3 = False + boltz1 = True + cif = True +else: + print("Wrong PDB or PAE file type ", pdb_path) + sys.exit() + +file_path = path_stem + ".txt" +file2_path = path_stem + "_byres.txt" +pml_path = path_stem + ".pml" +OUT = open(file_path,'w') +PML = open(pml_path,'w') +OUT2 = open(file2_path,'w') + + + +# Define the ptm and d0 functions +def ptm_func(x,d0): + return 1.0/(1+(x/d0)**2.0) +ptm_func_vec=np.vectorize(ptm_func) # vector version + +# Define the d0 functions for numbers and arrays; minimum value = 1.0; from Yang and Skolnick, PROTEINS: Structure, Function, and Bioinformatics 57:702–710 (2004) +def calc_d0(L,pair_type): + L=float(L) + if L<27: L=27 + min_value=1.0 + if pair_type=='nucleic_acid': min_value=2.0 + d0=1.24*(L-15)**(1.0/3.0) - 1.8 + return max(min_value, d0) + +def calc_d0_array(L,pair_type): + # Convert L to a NumPy array if it isn't already one (enables flexibility in input types) + L = np.array(L, dtype=float) + L = np.maximum(27,L) + min_value=1.0 + + if pair_type=='nucleic_acid': min_value=2.0 + + # Calculate d0 using the vectorized operation + return np.maximum(min_value, 1.24 * (L - 15) ** (1.0/3.0) - 1.8) + + +# Define the parse_atom_line function for PDB lines (by column) and mmCIF lines (split by white_space) +# parsed_line = parse_atom_line(line) +# line = "ATOM 123 CA ALA A 15 11.111 22.222 33.333 1.00 20.00 C" +def parse_pdb_atom_line(line): + atom_num = line[6:11].strip() + atom_name = line[12:16].strip() + residue_name = line[17:20].strip() + chain_id = line[21].strip() + residue_seq_num = line[22:26].strip() + x = line[30:38].strip() + y = line[38:46].strip() + z = line[46:54].strip() + + # Convert string numbers to integers or floats as appropriate + atom_num = int(atom_num) + residue_seq_num = int(residue_seq_num) + x = float(x) + y = float(y) + z = float(z) + + return { + 'atom_num': atom_num, + 'atom_name': atom_name, + 'residue_name': residue_name, + 'chain_id': chain_id, + 'residue_seq_num': residue_seq_num, + 'x': x, + 'y': y, + 'z': z + } + +def parse_cif_atom_line(line,fielddict): + # for parsing AF3 and Boltz1 mmCIF files + # ligands do not have residue numbers but modified residues do. Return "None" for ligand. + # AF3 mmcif lines + # 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 + #ATOM 1294 N N . ARG A 1 159 ? 5.141 -14.096 10.526 1.00 95.62 159 A 1 + #ATOM 1295 C CA . ARG A 1 159 ? 4.186 -13.376 11.366 1.00 96.27 159 A 1 + #ATOM 1296 C C . ARG A 1 159 ? 2.976 -14.235 11.697 1.00 96.42 159 A 1 + #ATOM 1297 O O . ARG A 1 159 ? 2.654 -15.174 10.969 1.00 95.46 159 A 1 + # ... + #HETATM 1305 N N . TPO A 1 160 ? 2.328 -13.853 12.742 1.00 96.42 160 A 1 + #HETATM 1306 C CA . TPO A 1 160 ? 1.081 -14.560 13.218 1.00 96.78 160 A 1 + #HETATM 1307 C C . TPO A 1 160 ? -2.115 -11.668 12.263 1.00 96.19 160 A 1 + #HETATM 1308 O O . TPO A 1 160 ? -1.790 -11.556 11.113 1.00 95.75 160 A 1 + # ... + #HETATM 2608 P PG . ATP C 3 . ? -6.858 4.182 10.275 1.00 84.94 1 C 1 + #HETATM 2609 O O1G . ATP C 3 . ? -6.178 5.238 11.074 1.00 75.56 1 C 1 + #HETATM 2610 O O2G . ATP C 3 . ? -5.889 3.166 9.748 1.00 75.15 1 C 1 + # ... + #HETATM 2639 MG MG . MG D 4 . ? -7.262 2.709 4.825 1.00 91.47 1 D 1 + #HETATM 2640 MG MG . MG E 5 . ? -4.994 2.251 8.755 1.00 85.96 1 E 1 + + + # Boltz1 mmcif files (in non-standard order)) + #_atom_site.group_PDB + #_atom_site.id + #_atom_site.type_symbol + #_atom_site.label_atom_id + #_atom_site.label_alt_id + #_atom_site.label_comp_id + #_atom_site.label_seq_id + #_atom_site.auth_seq_id + #_atom_site.pdbx_PDB_ins_code + #_atom_site.label_asym_id + #_atom_site.Cartn_x + #_atom_site.Cartn_y + #_atom_site.Cartn_z + #_atom_site.occupancy + #_atom_site.label_entity_id + #_atom_site.auth_asym_id + #_atom_site.auth_comp_id + #_atom_site.B_iso_or_equiv + #_atom_site.pdbx_PDB_model_num + # 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 + #ATOM 2652 N N . ASN 43 43 ? B 10.83538 6.06359 18.45139 1 2 B ASN 1 1 + #ATOM 2653 C CA . ASN 43 43 ? B 10.76295 5.07366 19.53232 1 2 B ASN 1 1 + #ATOM 2654 C C . ASN 43 43 ? B 11.21770 5.64437 20.88774 1 2 B ASN 1 1 + #ATOM 2655 O O . ASN 43 43 ? B 12.06730 6.51688 20.91168 1 2 B ASN 1 1 + #ATOM 2656 C CB . ASN 43 43 ? B 11.60137 3.84778 19.19481 1 2 B ASN 1 1 + #ATOM 2657 C CG . ASN 43 43 ? B 10.96208 3.03997 18.07013 1 2 B ASN 1 1 + #ATOM 2658 O OD1 . ASN 43 43 ? B 9.79094 3.17033 17.81165 1 2 B ASN 1 1 + #ATOM 2659 N ND2 . ASN 43 43 ? B 11.77101 2.23791 17.39764 1 2 B ASN 1 1 + #HETATM 2660 P PG . ATP . 1 ? C -8.79525 6.04621 -4.99212 1 3 C ATP 1 1 + #HETATM 2661 O O1G . ATP . 1 ? C -10.01901 6.83468 -5.24825 1 3 C ATP 1 1 + #HETATM 2662 O O2G . ATP . 1 ? C -9.03047 4.56941 -4.85246 1 3 C ATP 1 1 + #HETATM 2663 O O3G . ATP . 1 ? C -7.97335 6.60305 -3.86656 1 3 C ATP 1 1 + #HETATM 2664 P PB . ATP . 1 ? C -6.63618 7.04315 -6.56073 1 3 C ATP 1 1 + #HETATM 2665 O O1B . ATP . 1 ? C -7.04640 8.36577 -7.14326 1 3 C ATP 1 1 + #HETATM 2666 O O2B . ATP . 1 ? C -5.79036 7.13926 -5.33995 1 3 C ATP 1 1 + + + linelist = line.split() + atom_num = linelist[ fielddict['id'] ] + atom_name = linelist[ fielddict['label_atom_id'] ] + residue_name = linelist[ fielddict['label_comp_id'] ] + chain_id = linelist[ fielddict['label_asym_id'] ] + residue_seq_num = linelist[ fielddict['label_seq_id'] ] + x = linelist[ fielddict['Cartn_x'] ] + y = linelist[ fielddict['Cartn_y'] ] + z = linelist[ fielddict['Cartn_z'] ] + + if residue_seq_num == ".": return None # ligand atom + + # Convert string numbers to integers or floats as appropriate + atom_num = int(atom_num) + residue_seq_num = int(residue_seq_num) + x = float(x) + y = float(y) + z = float(z) + + return { + 'atom_num': atom_num, + 'atom_name': atom_name, + 'residue_name': residue_name, + 'chain_id': chain_id, + 'residue_seq_num': residue_seq_num, + 'x': x, + 'y': y, + 'z': z + } + + + +# Function for printing out residue numbers in PyMOL scripts +def contiguous_ranges(numbers): + if not numbers: # Check if the set is empty + return + + sorted_numbers = sorted(numbers) # Sort the numbers + start = sorted_numbers[0] + end = start + ranges = [] # List to store ranges + + def format_range(start, end): + if start == end: + return f"{start}" + else: + return f"{start}-{end}" + + for number in sorted_numbers[1:]: + if number == end + 1: + end = number + else: + ranges.append(format_range(start, end)) + start = end = number + + # Append the last range after the loop + ranges.append(format_range(start, end)) + + # Join all ranges with a plus sign and print the result + string='+'.join(ranges) + return(string) + +# Initializes a nested dictionary with all values set to 0 +def init_chainpairdict_zeros(chainlist): + return {chain1: {chain2: 0 for chain2 in chainlist if chain1 != chain2} for chain1 in chainlist} + +# Initializes a nested dictionary with NumPy arrays of zeros of a specified size +def init_chainpairdict_npzeros(chainlist, arraysize): + return {chain1: {chain2: np.zeros(arraysize) for chain2 in chainlist if chain1 != chain2} for chain1 in chainlist} + +# Initializes a nested dictionary with empty sets. +def init_chainpairdict_set(chainlist): + return {chain1: {chain2: set() for chain2 in chainlist if chain1 != chain2} for chain1 in chainlist} + + +def classify_chains(chains, residue_types): + nuc_residue_set = {"DA", "DC", "DT", "DG", "A", "C", "U", "G"} + chain_types = {} + + # Get unique chains and iterate over them + unique_chains = np.unique(chains) + for chain in unique_chains: + # Find indices where the current chain is located + indices = np.where(chains == chain)[0] + # Get the residues for these indices + chain_residues = residue_types[indices] + # Count nucleic acid residues + nuc_count = sum(residue in nuc_residue_set for residue in chain_residues) + + # Determine if the chain is a nucleic acid or protein + chain_types[chain] = 'nucleic_acid' if nuc_count > 0 else 'protein' + + return chain_types + + +# Load residues from AlphaFold PDB or mmCIF file into lists; each residue is a dictionary +# Read PDB file to get CA coordinates, chainids, and residue numbers +# Convert to np arrays, and calculate distances +residues = [] +cb_residues = [] +chains = [] +atomsitefield_num=0 +atomsitefield_dict={} # contains order of atom_site fields in mmCIF files; handles any mmCIF field order + +# For af3 and boltz1: need mask to identify CA atom tokens in plddt vector and pae matrix; +# Skip ligand atom tokens and non-CA-atom tokens in PTMs (those not in residue_set) +token_mask=list() +residue_set= {"ALA", "ARG", "ASN", "ASP", "CYS", + "GLN", "GLU", "GLY", "HIS", "ILE", + "LEU", "LYS", "MET", "PHE", "PRO", + "SER", "THR", "TRP", "TYR", "VAL", + "DA", "DC", "DT", "DG", "A", "C", "U", "G"} + +nuc_residue_set = {"DA", "DC", "DT", "DG", "A", "C", "U", "G"} + +with open(pdb_path, 'r') as PDB: + for line in PDB: + + if line.startswith("_atom_site."): + line=line.strip() + (atomsite,fieldname)=line.split(".") + atomsitefield_dict[fieldname]=atomsitefield_num + atomsitefield_num += 1 + + if line.startswith("ATOM") or line.startswith("HETATM"): + if cif: + atom=parse_cif_atom_line(line, atomsitefield_dict) + else: + atom=parse_pdb_atom_line(line) + if atom is None: # ligand atom + token_mask.append(0) + continue + + if atom['atom_name'] == "CA" or "C1" in atom['atom_name']: + token_mask.append(1) + residues.append({ + 'atom_num': atom['atom_num'], + 'coor': np.array([atom['x'], atom['y'], atom['z']]), + 'res': atom['residue_name'], + 'chainid': atom['chain_id'], + 'resnum': atom['residue_seq_num'], + 'residue': f"{atom['residue_name']:3} {atom['chain_id']:3} {atom['residue_seq_num']:4}" + }) + chains.append(atom['chain_id']) + + if atom['atom_name'] == "CB" or "C3" in atom['atom_name'] or (atom['residue_name']=="GLY" and atom['atom_name']=="CA"): + cb_residues.append({ + 'atom_num': atom['atom_num'], + 'coor': np.array([atom['x'], atom['y'], atom['z']]), + 'res': atom['residue_name'], + 'chainid': atom['chain_id'], + 'resnum': atom['residue_seq_num'], + 'residue': f"{atom['residue_name']:3} {atom['chain_id']:3} {atom['residue_seq_num']:4}" + }) + + # add nucleic acids and non-CA atoms in PTM residues to tokens (as 0), whether labeled as "HETATM" (af3) or as "ATOM" (boltz1) + if atom['atom_name'] != "CA" and "C1" not in atom['atom_name'] and atom['residue_name'] not in residue_set: + token_mask.append(0) + +# Convert structure information to numpy arrays +numres = len(residues) +CA_atom_num= np.array([res['atom_num']-1 for res in residues]) # for AF3 atom indexing from 0 +CB_atom_num= np.array([res['atom_num']-1 for res in cb_residues]) # for AF3 atom indexing from 0 +coordinates = np.array([res['coor'] for res in cb_residues]) +chains = np.array(chains) +unique_chains = np.unique(chains) +token_array=np.array(token_mask) +ntokens=np.sum(token_array) +residue_types=np.array([res['res'] for res in residues]) + +# chain types (nucleic acid (NA) or protein) and chain_pair_types ('nucleic_acid' if either chain is NA) for d0 calculation +# arbitrarily setting d0 to 2.0 for NA/protein or NA/NA chain pairs (approximately 21 base pairs) +d0_nucleic_acid=2.0 +chain_dict = classify_chains(chains, residue_types) +chain_pair_type = init_chainpairdict_zeros(unique_chains) +for chain1 in unique_chains: + for chain2 in unique_chains: + if chain1==chain2: continue + if chain_dict[chain1] == 'nucleic_acid' or chain_dict[chain2] == 'nucleic_acid': + chain_pair_type[chain1][chain2]='nucleic_acid' + else: + chain_pair_type[chain1][chain2]='protein' + +# Calculate distance matrix using NumPy broadcasting +distances = np.sqrt(((coordinates[:, np.newaxis, :] - coordinates[np.newaxis, :, :])**2).sum(axis=2)) + +# Load AF2, AF3, or BOLTZ1 data and extract plddt and pae_matrix (and ptm_matrix if available) +if af2: + + + if os.path.exists(pae_file_path): + if pae_file_path.endswith('.pkl'): + data = np.load(pae_file_path, allow_pickle=True) + else: + with open(pae_file_path, 'r') as file: + data = json.load(file) + + if 'iptm' in data: iptm_af2 = float(data['iptm']) + else: iptm_af2=-1.0 + if 'ptm' in data: ptm_af2 = float(data['ptm']) + else: ptm_af2=-1.0 + + if 'plddt' in data: + plddt = np.array(data['plddt']) + cb_plddt = np.array(data['plddt']) # for pDockQ + else: + plddt = np.zeros(numres) + cb_plddt = np.zeros(numres) + + if 'pae' in data: + pae_matrix = np.array(data['pae']) + elif 'predicted_aligned_error' in data: + pae_matrix=np.array(data['predicted_aligned_error']) + + else: + print("AF2 PAE file does not exist: ", pae_file_path) + sys.exit() + +if boltz1: + # Boltz1 filenames: + # AURKA_TPX2_model_0.cif + # confidence_AURKA_TPX2_model_0.json + # pae_AURKA_TPX2_model_0.npz + # plddt_AURKA_TPX2_model_0.npz + + + plddt_file_path=pae_file_path.replace("pae","plddt") + if os.path.exists(plddt_file_path): + data_plddt=np.load(plddt_file_path) + plddt_boltz1=np.array(100.0*data_plddt['plddt']) + plddt = plddt_boltz1[np.ix_(token_array.astype(bool))] + cb_plddt = plddt_boltz1[np.ix_(token_array.astype(bool))] + else: + plddt = np.zeros(ntokens) + cb_plddt = np.zeros(ntokens) + + if os.path.exists(pae_file_path): + data_pae = np.load(pae_file_path) + pae_matrix_boltz1=np.array(data_pae['pae']) + pae_matrix = pae_matrix_boltz1[np.ix_(token_array.astype(bool), token_array.astype(bool))] + + else: + print("Boltz1 PAE file does not exist: ", pae_file_path) + sys.exit() + + summary_file_path=pae_file_path.replace("pae","confidence") + summary_file_path=summary_file_path.replace(".npz",".json") + iptm_boltz1= {chain1: {chain2: 0 for chain2 in unique_chains if chain1 != chain2} for chain1 in unique_chains} + if os.path.exists(summary_file_path): + with open(summary_file_path, 'r') as file: + data_summary = json.load(file) + + boltz1_chain_pair_iptm_data=data_summary['pair_chains_iptm'] + for chain1 in unique_chains: + nchain1= ord(chain1) - ord('A') # map A,B,C... to 0,1,2... + for chain2 in unique_chains: + if chain1 == chain2: continue + nchain2=ord(chain2) - ord('A') + iptm_boltz1[chain1][chain2]=boltz1_chain_pair_iptm_data[str(nchain1)][str(nchain2)] + else: + print("Boltz1 summary file does not exist: ", summary_file_path) + +if af3: + # Example Alphafold3 server filenames + # fold_aurka_0_tpx2_0_full_data_0.json + # fold_aurka_0_tpx2_0_summary_confidences_0.json + # fold_aurka_0_tpx2_0_model_0.cif + # Example AlphaFold3 downloadable code filenames + # confidences.json + # summary_confidences.json + # model1.cif + if os.path.exists(pae_file_path): + with open(pae_file_path, 'r') as file: + data = json.load(file) + else: + print("AF3 PAE file does not exist: ", pae_file_path) + sys.exit() + + atom_plddts=np.array(data['atom_plddts']) + plddt=atom_plddts[CA_atom_num] # pull out residue plddts from Calpha atoms + cb_plddt=atom_plddts[CB_atom_num] # pull out residue plddts from Cbeta atoms for pDockQ + + # Get pairwise residue PAE matrix by identifying one token per protein residue. + # Modified residues have separate tokens for each atom, so need to pull out Calpha atom as token + # Skip ligands + if 'pae' in data: + pae_matrix_af3 = np.array(data['pae']) + else: + print("no PAE data in AF3 json file; quitting") + sys.exit() + + # Set pae_matrix for AF3 from subset of full PAE matrix from json file + token_array=np.array(token_mask) + pae_matrix = pae_matrix_af3[np.ix_(token_array.astype(bool), token_array.astype(bool))] + # Get iptm matrix from AF3 summary_confidences file + iptm_af3= {chain1: {chain2: 0 for chain2 in unique_chains if chain1 != chain2} for chain1 in unique_chains} + + summary_file_path = None + if "confidences" in pae_file_path: + summary_file_path = pae_file_path.replace("confidences", "summary_confidences") + elif "full_data" in pae_file_path: + summary_file_path = pae_file_path.replace("full_data", "summary_confidences") + + if summary_file_path is not None and os.path.exists(summary_file_path): + with open(summary_file_path,'r') as file: + data_summary=json.load(file) + af3_chain_pair_iptm_data=data_summary['chain_pair_iptm'] + for chain1 in unique_chains: + nchain1= ord(chain1) - ord('A') # map A,B,C... to 0,1,2... + for chain2 in unique_chains: + if chain1 == chain2: continue + nchain2=ord(chain2) - ord('A') + iptm_af3[chain1][chain2]=af3_chain_pair_iptm_data[nchain1][nchain2] + else: + print("AF3 summary file does not exist: ", summary_file_path) + + +# Compute chain-pair-specific interchain PTM and PAE, count valid pairs, and count unique residues +# First, create dictionaries of appropriate size: top keys are chain1 and chain2 where chain1 != chain2 +# Nomenclature: +# iptm_d0chn = calculate iptm from PAEs with no PAE cutoff; d0 = numres in chain pair = len(chain1) + len(chain2) +# ipsae_d0chn = calculate ipsae from PAEs with PAE cutoff; d0 = numres in chain pair = len(chain1) + len(chain2) +# ipsae_d0dom = calculate ipsae from PAEs with PAE cutoff; d0 from number of residues in chain1 and chain2 that have interchain PAEB is different from B->A) +# ipsae_d0res_max = maximum of A->B and B->A value +# ipsae_d0res_asymres = identify of residue that provides each asym maximum +# ipsae_d0res_maxres = identify of residue that provides each maximum over both chains +# +# n0num = number of residues in whole complex provided by AF2 model +# n0chn = number of residues in chain pair = len(chain1) + len(chain2) +# n0dom = number of residues in chain pair that have good PAE values (0: + nres=len(list(pDockQ_unique_residues[chain1][chain2])) + mean_plddt= cb_plddt[ list(pDockQ_unique_residues[chain1][chain2])].mean() + x=mean_plddt*math.log10(npairs) + pDockQ[chain1][chain2]= 0.724 / (1 + math.exp(-0.052*(x-152.611)))+0.018 + else: + mean_plddt=0.0 + x=0.0 + pDockQ[chain1][chain2]=0.0 + nres=0 + +# pDockQ2 + +for chain1 in unique_chains: + for chain2 in unique_chains: + if chain1 == chain2: + continue + npairs=0 + sum=0.0 + for i in range(numres): + if chains[i] != chain1: + continue + valid_pairs = (chains==chain2) & (distances[i] <= pDockQ_cutoff) + if valid_pairs.any(): + npairs += np.sum(valid_pairs) + pae_list=pae_matrix[i][valid_pairs] + pae_list_ptm=ptm_func_vec(pae_list,10.0) + sum += pae_list_ptm.sum() + + if npairs>0: + nres=len(list(pDockQ_unique_residues[chain1][chain2])) + mean_plddt= cb_plddt[ list(pDockQ_unique_residues[chain1][chain2])].mean() + mean_ptm = sum/npairs + x=mean_plddt*mean_ptm + pDockQ2[chain1][chain2]= 1.31 / (1 + math.exp(-0.075*(x-84.733)))+0.005 + else: + mean_plddt=0.0 + x=0.0 + nres=0 + pDockQ2[chain1][chain2]=0.0 + +# LIS + +for chain1 in unique_chains: + for chain2 in unique_chains: + if chain1==chain2: continue + + mask = (chains[:, None] == chain1) & (chains[None, :] == chain2) # Select residues for (chain1, chain2) + selected_pae = pae_matrix[mask] # Get PAE values for this pair + + if selected_pae.size > 0: # Ensure we have values + valid_pae = selected_pae[selected_pae <= 12] # Apply the threshold + if valid_pae.size > 0: + scores = (12 - valid_pae) / 12 # Compute scores + avg_score = np.mean(scores) # Average score for (chain1, chain2) + LIS[chain1][chain2] = avg_score + else: + LIS[chain1][chain2] = 0.0 # No valid values + else: + LIS[chain1][chain2]=0.0 + + + +# calculate ipTM/ipSAE with and without PAE cutoff + +for chain1 in unique_chains: + for chain2 in unique_chains: + if chain1 == chain2: + continue + + n0chn[chain1][chain2]=np.sum( chains==chain1) + np.sum(chains==chain2) # total number of residues in chain1 and chain2 + d0chn[chain1][chain2]=calc_d0(n0chn[chain1][chain2], chain_pair_type[chain1][chain2]) + ptm_matrix_d0chn=np.zeros((numres,numres)) + ptm_matrix_d0chn=ptm_func_vec(pae_matrix,d0chn[chain1][chain2]) + + valid_pairs_iptm = (chains == chain2) + valid_pairs_matrix = (chains == chain2) & (pae_matrix < pae_cutoff) + + for i in range(numres): + + + if chains[i] != chain1: + continue + + valid_pairs_ipsae = valid_pairs_matrix[i] # row for residue i of chain1 + iptm_d0chn_byres[chain1][chain2][i] = ptm_matrix_d0chn[i, valid_pairs_iptm].mean() if valid_pairs_iptm.any() else 0.0 + ipsae_d0chn_byres[chain1][chain2][i] = ptm_matrix_d0chn[i, valid_pairs_ipsae].mean() if valid_pairs_ipsae.any() else 0.0 + + # Track unique residues contributing to the IPSAE for chain1,chain2 + valid_pair_counts[chain1][chain2] += np.sum(valid_pairs_ipsae) + if valid_pairs_ipsae.any(): + iresnum=residues[i]['resnum'] + unique_residues_chain1[chain1][chain2].add(iresnum) + for j in np.where(valid_pairs_ipsae)[0]: + jresnum=residues[j]['resnum'] + unique_residues_chain2[chain1][chain2].add(jresnum) + + # Track unique residues contributing to iptm in interface + valid_pairs = (chains == chain2) & (pae_matrix[i] < pae_cutoff) & (distances[i] < dist_cutoff) + dist_valid_pair_counts[chain1][chain2] += np.sum(valid_pairs) + + # Track unique residues contributing to the IPTM + if valid_pairs.any(): + iresnum=residues[i]['resnum'] + dist_unique_residues_chain1[chain1][chain2].add(iresnum) + for j in np.where(valid_pairs)[0]: + jresnum=residues[j]['resnum'] + dist_unique_residues_chain2[chain1][chain2].add(jresnum) + +OUT2.write("i AlignChn ScoredChain AlignResNum AlignResType AlignRespLDDT n0chn n0dom n0res d0chn d0dom d0res ipTM_pae ipSAE_d0chn ipSAE_d0dom ipSAE \n") +for chain1 in unique_chains: + for chain2 in unique_chains: + if chain1 == chain2: + continue + residues_1 = len(unique_residues_chain1[chain1][chain2]) + residues_2 = len(unique_residues_chain2[chain1][chain2]) + n0dom[chain1][chain2] = residues_1+residues_2 + d0dom[chain1][chain2] = calc_d0(n0dom[chain1][chain2], chain_pair_type[chain1][chain2]) + + ptm_matrix_d0dom = np.zeros((numres,numres)) + ptm_matrix_d0dom = ptm_func_vec(pae_matrix,d0dom[chain1][chain2]) + + valid_pairs_matrix = (chains == chain2) & (pae_matrix < pae_cutoff) + + # Assuming valid_pairs_matrix is already defined + n0res_byres_all = np.sum(valid_pairs_matrix, axis=1) + d0res_byres_all = calc_d0_array(n0res_byres_all, chain_pair_type[chain1][chain2]) + + n0res_byres[chain1][chain2] = n0res_byres_all + d0res_byres[chain1][chain2] = d0res_byres_all + + for i in range(numres): + if chains[i] != chain1: + continue + valid_pairs = valid_pairs_matrix[i] + ipsae_d0dom_byres[chain1][chain2][i] = ptm_matrix_d0dom[i, valid_pairs].mean() if valid_pairs.any() else 0.0 + + ptm_row_d0res=np.zeros((numres)) + ptm_row_d0res=ptm_func_vec(pae_matrix[i], d0res_byres[chain1][chain2][i]) + ipsae_d0res_byres[chain1][chain2][i] = ptm_row_d0res[valid_pairs].mean() if valid_pairs.any() else 0.0 + + outstring = f'{i+1:<4d} ' + ( + f'{chain1:4} ' + f'{chain2:4} ' + f'{residues[i]["resnum"]:4d} ' + f'{residues[i]["res"]:3} ' + f'{plddt[i]:8.2f} ' + f'{int(n0chn[chain1][chain2]):5d} ' + f'{int(n0dom[chain1][chain2]):5d} ' + f'{int(n0res_byres[chain1][chain2][i]):5d} ' + f'{d0chn[chain1][chain2]:8.3f} ' + f'{d0dom[chain1][chain2]:8.3f} ' + f'{d0res_byres[chain1][chain2][i]:8.3f} ' + f'{iptm_d0chn_byres[chain1][chain2][i]:8.4f} ' + f'{ipsae_d0chn_byres[chain1][chain2][i]:8.4f} ' + f'{ipsae_d0dom_byres[chain1][chain2][i]:8.4f} ' + f'{ipsae_d0res_byres[chain1][chain2][i]:8.4f}\n' + ) + OUT2.write(outstring) + +# Compute interchain ipTM and ipSAE for each chain pair +for chain1 in unique_chains: + for chain2 in unique_chains: + if chain1 == chain2: + continue + + interchain_values = iptm_d0chn_byres[chain1][chain2] + max_index = np.argmax(interchain_values) + iptm_d0chn_asym[chain1][chain2] = interchain_values[max_index] + iptm_d0chn_asymres[chain1][chain2] = residues[max_index]['residue'] if max_index is not None else "None" + + interchain_values = ipsae_d0chn_byres[chain1][chain2] + max_index = np.argmax(interchain_values) + ipsae_d0chn_asym[chain1][chain2] = interchain_values[max_index] + ipsae_d0chn_asymres[chain1][chain2] = residues[max_index]['residue'] if max_index is not None else "None" + + interchain_values = ipsae_d0dom_byres[chain1][chain2] + max_index = np.argmax(interchain_values) + ipsae_d0dom_asym[chain1][chain2] = interchain_values[max_index] + ipsae_d0dom_asymres[chain1][chain2] = residues[max_index]['residue'] if max_index is not None else "None" + + interchain_values = ipsae_d0res_byres[chain1][chain2] + max_index = np.argmax(interchain_values) + ipsae_d0res_asym[chain1][chain2] = interchain_values[max_index] + ipsae_d0res_asymres[chain1][chain2] = residues[max_index]['residue'] if max_index is not None else "None" + n0res[chain1][chain2]=n0res_byres[chain1][chain2][max_index] + d0res[chain1][chain2]=d0res_byres[chain1][chain2][max_index] + + # pick maximum value for each chain pair for each iptm/ipsae type + if chain1 > chain2: + maxvalue=max(iptm_d0chn_asym[chain1][chain2], iptm_d0chn_asym[chain2][chain1]) + if maxvalue==iptm_d0chn_asym[chain1][chain2]: maxres=iptm_d0chn_asymres[chain1][chain2] + else: maxres=iptm_d0chn_asymres[chain2][chain1] + iptm_d0chn_max[chain1][chain2]=maxvalue + iptm_d0chn_maxres[chain1][chain2]=maxres + iptm_d0chn_max[chain2][chain1]=maxvalue + iptm_d0chn_maxres[chain2][chain1]=maxres + + maxvalue=max(ipsae_d0chn_asym[chain1][chain2], ipsae_d0chn_asym[chain2][chain1]) + if maxvalue==ipsae_d0chn_asym[chain1][chain2]: maxres=ipsae_d0chn_asymres[chain1][chain2] + else: maxres=ipsae_d0chn_asymres[chain2][chain1] + ipsae_d0chn_max[chain1][chain2]=maxvalue + ipsae_d0chn_maxres[chain1][chain2]=maxres + ipsae_d0chn_max[chain2][chain1]=maxvalue + ipsae_d0chn_maxres[chain2][chain1]=maxres + + maxvalue=max(ipsae_d0dom_asym[chain1][chain2], ipsae_d0dom_asym[chain2][chain1]) + if maxvalue==ipsae_d0dom_asym[chain1][chain2]: + maxres=ipsae_d0dom_asymres[chain1][chain2] + maxn0=n0dom[chain1][chain2] + maxd0=d0dom[chain1][chain2] + else: + maxres=ipsae_d0dom_asymres[chain2][chain1] + maxn0=n0dom[chain2][chain1] + maxd0=d0dom[chain2][chain1] + ipsae_d0dom_max[chain1][chain2]=maxvalue + ipsae_d0dom_maxres[chain1][chain2]=maxres + ipsae_d0dom_max[chain2][chain1]=maxvalue + ipsae_d0dom_maxres[chain2][chain1]=maxres + n0dom_max[chain1][chain2]=maxn0 + n0dom_max[chain2][chain1]=maxn0 + d0dom_max[chain1][chain2]=maxd0 + d0dom_max[chain2][chain1]=maxd0 + + maxvalue=max(ipsae_d0res_asym[chain1][chain2], ipsae_d0res_asym[chain2][chain1]) + if maxvalue==ipsae_d0res_asym[chain1][chain2]: + maxres=ipsae_d0res_asymres[chain1][chain2] + maxn0=n0res[chain1][chain2] + maxd0=d0res[chain1][chain2] + else: + maxres=ipsae_d0res_asymres[chain2][chain1] + maxn0=n0res[chain2][chain1] + maxd0=d0res[chain2][chain1] + ipsae_d0res_max[chain1][chain2]=maxvalue + ipsae_d0res_maxres[chain1][chain2]=maxres + ipsae_d0res_max[chain2][chain1]=maxvalue + ipsae_d0res_maxres[chain2][chain1]=maxres + n0res_max[chain1][chain2]=maxn0 + n0res_max[chain2][chain1]=maxn0 + d0res_max[chain1][chain2]=maxd0 + d0res_max[chain2][chain1]=maxd0 + + +chaincolor={'A':'magenta', 'B':'marine', 'C':'lime', 'D':'orange', + 'E':'yellow', 'F':'cyan', 'G':'lightorange', 'H':'pink', + 'I':'deepteal', 'J':'forest', 'K':'lightblue', 'L':'slate', + 'M':'violet', 'N':'arsenic', 'O':'iodine', 'P':'silver', + 'Q':'red', 'R':'sulfur', 'S':'purple', 'T':'olive', + 'U':'palegreen', 'V':'green', 'W':'blue', 'X':'palecyan', + 'Y':'limon', 'Z':'chocolate'} + +chainpairs=set() +for chain1 in unique_chains: + for chain2 in unique_chains: + if chain1 >= chain2: continue + chainpairs.add(chain1 + "-" + chain2) + +OUT.write("\nChn1 Chn2 PAE Dist Type ipSAE ipSAE_d0chn ipSAE_d0dom ipTM_af ipTM_d0chn pDockQ pDockQ2 LIS n0res n0chn n0dom d0res d0chn d0dom nres1 nres2 dist1 dist2 Model\n") +PML.write("# Chn1 Chn2 PAE Dist Type ipSAE ipSAE_d0chn ipSAE_d0dom ipTM_af ipTM_d0chn pDockQ pDockQ2 LIS n0res n0chn n0dom d0res d0chn d0dom nres1 nres2 dist1 dist2 Model\n") +for pair in sorted(chainpairs): + (chain_a, chain_b) = pair.split("-") + pair1 = (chain_a, chain_b) + pair2 = (chain_b, chain_a) + for pair in (pair1, pair2): + chain1=pair[0] + chain2=pair[1] + + if chain1 in chaincolor: + color1=chaincolor[chain1] + else: + color1='magenta' + + if chain2 in chaincolor: + color2=chaincolor[chain2] + else: + color2='marine' + + residues_1 = len(unique_residues_chain1[chain1][chain2]) + residues_2 = len(unique_residues_chain2[chain1][chain2]) + dist_residues_1 = len(dist_unique_residues_chain1[chain1][chain2]) + dist_residues_2 = len(dist_unique_residues_chain2[chain1][chain2]) + pairs = valid_pair_counts[chain1][chain2] + dist_pairs = dist_valid_pair_counts[chain1][chain2] + if af2: iptm_af = iptm_af2 # same for all chain pairs in entry + if af3: iptm_af = iptm_af3[chain1][chain2] # symmetric value for each chain pair + if boltz1: iptm_af=iptm_boltz1[chain1][chain2] + + outstring=f'{chain1} {chain2} {pae_string:3} {dist_string:3} {"asym":5} ' + ( + f'{ipsae_d0res_asym[chain1][chain2]:8.6f} ' + f'{ipsae_d0chn_asym[chain1][chain2]:8.6f} ' + f'{ipsae_d0dom_asym[chain1][chain2]:8.6f} ' + f'{iptm_af:5.3f} ' + f'{iptm_d0chn_asym[chain1][chain2]:8.6f} ' + f'{pDockQ[chain1][chain2]:8.4f} ' + f'{pDockQ2[chain1][chain2]:8.4f} ' + f'{LIS[chain1][chain2]:8.4f} ' + f'{int(n0res[chain1][chain2]):5d} ' + f'{int(n0chn[chain1][chain2]):5d} ' + f'{int(n0dom[chain1][chain2]):5d} ' + f'{d0res[chain1][chain2]:6.2f} ' + f'{d0chn[chain1][chain2]:6.2f} ' + f'{d0dom[chain1][chain2]:6.2f} ' + f'{residues_1:5d} ' + f'{residues_2:5d} ' + f'{dist_residues_1:5d} ' + f'{dist_residues_2:5d} ' + f'{pdb_stem}\n') + OUT.write(outstring) + PML.write("# " + outstring) + if chain1 > chain2: + residues_1 = max(len(unique_residues_chain2[chain1][chain2]), len(unique_residues_chain1[chain2][chain1])) + residues_2 = max(len(unique_residues_chain1[chain1][chain2]), len(unique_residues_chain2[chain2][chain1])) + dist_residues_1 = max(len(dist_unique_residues_chain2[chain1][chain2]), len(dist_unique_residues_chain1[chain2][chain1])) + dist_residues_2 = max(len(dist_unique_residues_chain1[chain1][chain2]), len(dist_unique_residues_chain2[chain2][chain1])) + + iptm_af_value=iptm_af + pDockQ2_value=max(pDockQ2[chain1][chain2], pDockQ2[chain2][chain1]) + if boltz1: + iptm_af_value=max(iptm_boltz1[chain1][chain2], iptm_boltz1[chain2][chain1]) + + + LIS_Score=(LIS[chain1][chain2]+LIS[chain2][chain1])/2.0 + outstring=f'{chain2} {chain1} {pae_string:3} {dist_string:3} {"max":5} ' + ( + f'{ipsae_d0res_max[chain1][chain2]:8.6f} ' + f'{ipsae_d0chn_max[chain1][chain2]:8.6f} ' + f'{ipsae_d0dom_max[chain1][chain2]:8.6f} ' + f'{iptm_af_value:5.3f} ' + f'{iptm_d0chn_max[chain1][chain2]:8.6f} ' + f'{pDockQ[chain1][chain2]:8.4f} ' + f'{pDockQ2_value:8.4f} ' + f'{LIS_Score:8.4f} ' + f'{int(n0res_max[chain1][chain2]):5d} ' + f'{int(n0chn[chain1][chain2]):5d} ' + f'{int(n0dom_max[chain1][chain2]):5d} ' + f'{d0res_max[chain1][chain2]:6.2f} ' + f'{d0chn[chain1][chain2]:6.2f} ' + f'{d0dom_max[chain1][chain2]:6.2f} ' + f'{residues_1:5d} ' + f'{residues_2:5d} ' + f'{dist_residues_1:5d} ' + f'{dist_residues_2:5d} ' + f'{pdb_stem}\n') + OUT.write(outstring) + PML.write("# " + outstring) + + chain_pair= f'color_{chain1}_{chain2}' + chain1_residues = f'chain {chain1} and resi {contiguous_ranges(unique_residues_chain1[chain1][chain2])}' + chain2_residues = f'chain {chain2} and resi {contiguous_ranges(unique_residues_chain2[chain1][chain2])}' + PML.write(f'alias {chain_pair}, color gray80, all; color {color1}, {chain1_residues}; color {color2}, {chain2_residues}\n\n') + OUT.write("\n") diff --git a/bin/latest.py b/bin/latest.py new file mode 100644 index 0000000..d2b4651 --- /dev/null +++ b/bin/latest.py @@ -0,0 +1,787 @@ +#!/opt/miniforge/bin/python3 +""" +#!/usr/local/bin/python3 + +Functionality for running mmseqs locally. Takes in a fasta file, outputs final.a3m +""" +import logging +import math +import os +import shutil +import subprocess +import json +from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter +from pathlib import Path +from typing import List, Optional, Tuple, Union, Dict +import random + +from input import get_queries, msa_to_str, safe_filename +from utils import AF3Utils + + +logger = logging.getLogger(__name__) + +MODULE_OUTPUT_POS = { + "align": 4, + "convertalis": 4, + "expandaln": 5, + "filterresult": 4, + "lndb": 2, + "mergedbs": 2, + "mvdb": 2, + "pairaln": 4, + "result2msa": 4, + "search": 3, +} + +def rename_output(queries_unique, ext, base): + for job_number, (raw_jobname, query_sequences, query_seqs_cardinality, other_molecules) in enumerate(queries_unique): + os.rename( + base.joinpath(f"{job_number}.{ext}"), + base.joinpath(f"{safe_filename(raw_jobname)}.{ext}"), + ) + +def expand_db(db_path, seq_map, overwrite=True): + index_data = [] + with open(f"{db_path}.index", "r") as in_f: + for line in in_f: + index_data.append([int(x) for x in line.strip().split()]) + + new_index = "" + offset = 0 + seq_itr = 0 + with open(f"{db_path}-tmp", "wb") as out_file: + for seqs in seq_map: + for seq_index in seqs: + start_byte = index_data[seq_index][1] + byte_cnt = index_data[seq_index][2] + with open(f"{db_path}", "rb") as f: + f.seek(start_byte) + out_file.write(f.read(byte_cnt)) + new_index += f"{seq_itr}\t{offset}\t{byte_cnt}\n" + offset += byte_cnt + seq_itr += 1 + + with open(f"{db_path}-tmp.index", "w") as out_f: + out_f.write(new_index) + + if overwrite: + os.rename(f"{db_path}-tmp.index", f"{db_path}.index") + os.rename(f"{db_path}-tmp", f"{db_path}") + +def run_mmseqs(mmseqs: Path, params: List[Union[str, Path]]): + module = params[0] + if module in MODULE_OUTPUT_POS: + output_pos = MODULE_OUTPUT_POS[module] + output_path = Path(params[output_pos]).with_suffix('.dbtype') + if output_path.exists(): + logger.info(f"Skipping {module} because {output_path} already exists") + return + + params_log = " ".join(str(i) for i in params) + logger.info(f"Running {mmseqs} {params_log}") + # hide MMseqs2 verbose paramters list that clogs up the log + os.environ["MMSEQS_CALL_DEPTH"] = "1" + os.environ["MMSEQS_FORCE_MERGE"] = "True" + subprocess.check_call([mmseqs] + params) + + +def mmseqs_search_monomer( + dbbase: Path, + base: Path, + uniref_db: Path = Path("uniref30_2302_db"), + template_db: Path = Path(""), # Unused by default + metagenomic_db: Path = Path("colabfold_envdb_202108_db"), + mmseqs: Path = Path("mmseqs"), + use_env: bool = True, + use_templates: bool = False, + filter: bool = True, + expand_eval: float = math.inf, + align_eval: int = 10, + diff: int = 3000, + qsc: float = -20.0, + max_accept: int = 1000000, + prefilter_mode: int = 0, + s: float = 8, + db_load_mode: int = 2, + threads: int = 32, + gpu: int = 0, + gpu_server: int = 0, + unpack: bool = True, +): + """Run mmseqs with a local colabfold database set + + db1: uniprot db (UniRef30) + db2: Template (unused by default) + db3: metagenomic db (colabfold_envdb_202108 or bfd_mgy_colabfold, the former is preferred) + """ + if filter: + # 0.1 was not used in benchmarks due to POSIX shell bug in line above + # EXPAND_EVAL=0.1 + align_eval = 10 + qsc = 0.8 + max_accept = 100000 + + used_dbs = [uniref_db] + if use_templates: + used_dbs.append(template_db) + if use_env: + used_dbs.append(metagenomic_db) + + for db in used_dbs: + if not dbbase.joinpath(f"{db}.dbtype").is_file(): + raise FileNotFoundError(f"Database {db} does not exist") + if ( + ( + not dbbase.joinpath(f"{db}.idx").is_file() + and not dbbase.joinpath(f"{db}.idx.index").is_file() + ) + or os.environ.get("MMSEQS_IGNORE_INDEX", False) + ): + logger.info("Search does not use index") + db_load_mode = 0 + dbSuffix1 = "_seq" + dbSuffix2 = "_aln" + dbSuffix3 = "" + else: + dbSuffix1 = ".idx" + dbSuffix2 = ".idx" + dbSuffix3 = ".idx" + + search_param = ["--num-iterations", "3", "--db-load-mode", str(db_load_mode), "-a", "-e", "0.1", "--max-seqs", "10000"] + template_search_param = [] + if gpu: + search_param += ["--gpu", str(gpu), "--prefilter-mode", "1"] # gpu version only supports ungapped prefilter currently + template_search_param += ["--gpu", str(gpu), "--prefilter-mode", "1"] + else: + search_param += ["--prefilter-mode", str(prefilter_mode)] + template_search_param += ["-s", "7.5", "--prefilter-mode", str(prefilter_mode)] + if s is not None: # sensitivy can only be set for non-gpu version, gpu version runs at max sensitivity + search_param += ["-s", "{:.1f}".format(s)] + else: + search_param += ["--k-score", "'seq:96,prof:80'"] + if gpu_server: + search_param += ["--gpu-server", str(gpu_server)] + + filter_param = ["--filter-msa", str(filter), "--filter-min-enable", "1000", "--diff", str(diff), "--qid", "0.0,0.2,0.4,0.6,0.8,1.0", "--qsc", "0", "--max-seq-id", "0.95",] + expand_param = ["--expansion-mode", "0", "-e", str(expand_eval), "--expand-filter-clusters", str(filter), "--max-seq-id", "0.95",] + + if not base.joinpath("uniref.a3m").with_suffix('.a3m.dbtype').exists(): + run_mmseqs(mmseqs, ["search", base.joinpath("qdb"), dbbase.joinpath(uniref_db), base.joinpath("res"), base.joinpath("tmp"), "--threads", str(threads)] + search_param) + os.mkdir(base.joinpath("kept_data")) + run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/profile_1"), base.joinpath("prof_res")]) + run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/aln_1"), base.joinpath("kept_data/aln_1")]) + run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/aln_0"), base.joinpath("kept_data/aln_0")]) + #run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/profile_0"), base.joinpath("kept_data/profile_0")]) + #exit() + run_mmseqs(mmseqs, ["lndb", base.joinpath("qdb_h"), base.joinpath("prof_res_h")]) + + run_mmseqs(mmseqs, ["expandaln", base.joinpath("qdb"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), base.joinpath("res"), dbbase.joinpath(f"{uniref_db}{dbSuffix2}"), base.joinpath("res_exp"), "--db-load-mode", str(db_load_mode), "--threads", str(threads)] + expand_param) + run_mmseqs(mmseqs, ["align", base.joinpath("prof_res"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), base.joinpath("res_exp"), base.joinpath("res_exp_realign"), "--db-load-mode", str(db_load_mode), "-e", str(align_eval), "--max-accept", str(max_accept), "--threads", str(threads), "--alt-ali", "10", "-a"]) + run_mmseqs(mmseqs, ["filterresult", base.joinpath("qdb"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), + base.joinpath("res_exp_realign"), base.joinpath("res_exp_realign_filter"), "--db-load-mode", + str(db_load_mode), "--qid", "0", "--qsc", str(qsc), "--diff", "0", "--threads", + str(threads), "--max-seq-id", "1.0", "--filter-min-enable", "100"]) + run_mmseqs(mmseqs, ["result2msa", base.joinpath("qdb"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), + base.joinpath("res_exp_realign_filter"), base.joinpath("uniref.a3m"), "--msa-format-mode", + "6", "--db-load-mode", str(db_load_mode), "--threads", str(threads)] + filter_param) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign_filter")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp")]) + #run_mmseqs(mmseqs, ["rmdb", base.joinpath("res")]) + + else: + logger.info(f"Skipping {uniref_db} search because uniref.a3m already exists") + + if use_env and not base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m").with_suffix('.a3m.dbtype').exists(): + run_mmseqs(mmseqs, ["search", base.joinpath("prof_res"), dbbase.joinpath(metagenomic_db), base.joinpath("res_env"), + base.joinpath("tmp3"), "--threads", str(threads)] + search_param) + run_mmseqs(mmseqs, ["expandaln", base.joinpath("prof_res"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), base.joinpath("res_env"), + dbbase.joinpath(f"{metagenomic_db}{dbSuffix2}"), base.joinpath("res_env_exp"), "-e", str(expand_eval), + "--expansion-mode", "0", "--db-load-mode", str(db_load_mode), "--threads", str(threads)]) + run_mmseqs(mmseqs, ["align", base.joinpath("tmp3/latest/profile_1"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), + base.joinpath("res_env_exp"), base.joinpath("res_env_exp_realign"), "--db-load-mode", + str(db_load_mode), "-e", str(align_eval), "--max-accept", str(max_accept), "--threads", + str(threads), "--alt-ali", "10", "-a"]) + run_mmseqs(mmseqs, ["filterresult", base.joinpath("qdb"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), + base.joinpath("res_env_exp_realign"), base.joinpath("res_env_exp_realign_filter"), + "--db-load-mode", str(db_load_mode), "--qid", "0", "--qsc", str(qsc), "--diff", "0", + "--max-seq-id", "1.0", "--threads", str(threads), "--filter-min-enable", "100"]) + run_mmseqs(mmseqs, ["result2msa", base.joinpath("qdb"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), + base.joinpath("res_env_exp_realign_filter"), + base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m"), "--msa-format-mode", "6", + "--db-load-mode", str(db_load_mode), "--threads", str(threads)] + filter_param) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env_exp_realign_filter")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env_exp_realign")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env_exp")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env")]) + elif use_env: + logger.info(f"Skipping {metagenomic_db} search because bfd.mgnify30.metaeuk30.smag30.a3m already exists") + + if use_templates and not base.joinpath(f"{template_db}.m8").with_suffix('.m8.dbtype').exists(): + run_mmseqs(mmseqs, ["search", base.joinpath("prof_res"), dbbase.joinpath(template_db), base.joinpath("res_pdb"), + base.joinpath("tmp2"), "--db-load-mode", str(db_load_mode), "--threads", str(threads), "-a", "-e", "0.1"] + template_search_param) + run_mmseqs(mmseqs, ["convertalis", base.joinpath("prof_res"), dbbase.joinpath(f"{template_db}{dbSuffix3}"), base.joinpath("res_pdb"), + base.joinpath(f"{template_db}"), "--format-output", + "query,target,fident,alnlen,mismatch,gapopen,qstart,qend,tstart,tend,evalue,bits,cigar", + "--db-output", "1", + "--db-load-mode", str(db_load_mode), "--threads", str(threads)]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_pdb")]) + elif use_templates: + logger.info(f"Skipping {template_db} search because {template_db}.m8 already exists") + + if use_env: + run_mmseqs(mmseqs, ["mergedbs", base.joinpath("qdb"), base.joinpath("final.a3m"), base.joinpath("uniref.a3m"), base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("uniref.a3m")]) + else: + run_mmseqs(mmseqs, ["mvdb", base.joinpath("uniref.a3m"), base.joinpath("final.a3m")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("uniref.a3m")]) + + if unpack: + run_mmseqs(mmseqs, ["unpackdb", base.joinpath("final.a3m"), base.joinpath("."), "--unpack-name-mode", "0", "--unpack-suffix", ".a3m"]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("final.a3m")]) + + if use_templates: + run_mmseqs(mmseqs, ["unpackdb", base.joinpath(f"{template_db}"), base.joinpath("."), "--unpack-name-mode", "0", "--unpack-suffix", ".m8"]) + if base.joinpath(f"{template_db}").exists(): + run_mmseqs(mmseqs, ["rmdb", base.joinpath(f"{template_db}")]) + + #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) + #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) + shutil.rmtree(base.joinpath("tmp")) + if use_templates: + shutil.rmtree(base.joinpath("tmp2")) + if use_env: + shutil.rmtree(base.joinpath("tmp3")) + +def mmseqs_search_pair( + dbbase: Path, + base: Path, + uniref_db: Path = Path("uniref30_2302_db"), + spire_db: Path = Path("spire_ctg10_2401_db"), + mmseqs: Path = Path("mmseqs"), + pair_env: bool = True, + prefilter_mode: int = 0, + s: float = 8, + threads: int = 64, + gpu: bool = False, + gpu_server: bool = False, + db_load_mode: int = 2, + pairing_strategy: int = 0, + unpack: bool = True, + seq_map: list=[], +): + if not dbbase.joinpath(f"{uniref_db}.dbtype").is_file(): + raise FileNotFoundError(f"Database {uniref_db} does not exist") + if ( + ( + not dbbase.joinpath(f"{uniref_db}.idx").is_file() + and not dbbase.joinpath(f"{uniref_db}.idx.index").is_file() + ) + or os.environ.get("MMSEQS_IGNORE_INDEX", False) + ): + logger.info("Search does not use index") + db_load_mode = 0 + dbSuffix1 = "_seq" + dbSuffix2 = "_aln" + else: + dbSuffix1 = ".idx" + dbSuffix2 = ".idx" + + if pair_env: + db = spire_db + output = ".env.paired.a3m" + else: + db = uniref_db + output = ".paired.a3m" + + # fmt: off + # @formatter:off + search_param = ["--num-iterations", "3", "--db-load-mode", str(db_load_mode), "-a", "-e", "0.1", "--max-seqs", "10000",] + if gpu: + search_param += ["--gpu", str(gpu), "--prefilter-mode", "1"] # gpu version only supports ungapped prefilter currently + else: + search_param += ["--prefilter-mode", str(prefilter_mode)] + if s is not None: # sensitivy can only be set for non-gpu version, gpu version runs at max sensitivity + search_param += ["-s", "{:.1f}".format(s)] + else: + search_param += ["--k-score", "'seq:96,prof:80'"] + if gpu_server: + search_param += ["--gpu-server", str(gpu_server)] + expand_param = ["--expansion-mode", "0", "-e", "inf", "--expand-filter-clusters", "0", "--max-seq-id", "0.95",] + + if db != uniref_db: + # cleaning + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) + + run_mmseqs(mmseqs, ["search", base.joinpath("qdb"), dbbase.joinpath(db), base.joinpath("res"), base.joinpath("tmp"), "--threads", str(threads),] + search_param,) + run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/profile_1"), base.joinpath("prof_res")]) + run_mmseqs(mmseqs, ["lndb", base.joinpath("qdb_h"), base.joinpath("prof_res_h")]) + else: + os.makedirs(base.joinpath("tmp/latest")) + run_mmseqs(mmseqs, ["mvdb", base.joinpath("kept_data/aln_0"), base.joinpath("tmp/latest/aln_0")]) + run_mmseqs(mmseqs, ["mvdb", base.joinpath("kept_data/aln_1"), base.joinpath("tmp/latest/aln_1")]) + #run_mmseqs(mmseqs, ["mvdb", base.joinpath("kept_data/profile_0"), base.joinpath("tmp/latest/profile_0")]) + shutil.rmtree(base.joinpath("kept_data")) + + run_mmseqs(mmseqs, ["expandaln", base.joinpath("qdb"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res"), dbbase.joinpath(f"{db}{dbSuffix2}"), base.joinpath("res_exp"), "--db-load-mode", str(db_load_mode), "--threads", str(threads),] + expand_param,) + run_mmseqs(mmseqs, ["align", base.joinpath("prof_res"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res_exp"), base.joinpath("res_exp_realign"), "--db-load-mode", str(db_load_mode), "-e", "0.001", "--max-accept", "1000000", "--threads", str(threads),],) + + # Added by Ziad + #shutil.copy(base.joinpath("res_exp_realign"), base.joinpath("res_exp_realign-minimal")) + #shutil.copy(base.joinpath("res_exp_realign.index"), base.joinpath("res_exp_realign-minimal.index")) + #exit() + run_mmseqs(mmseqs, ["cpdb", base.joinpath("qdb"), base.joinpath("qdb-minimal")]) + + for merged_db in [base.joinpath("res_exp_realign"), base.joinpath("tmp/latest/aln_0"), base.joinpath("tmp/latest/aln_1")]: + print(f"merging {merged_db}") + expand_db(merged_db, seq_map, True) + + os.rename(base.joinpath("original-query.fas"), base.joinpath("query.fas")) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("qdb")]) + query_file = base.joinpath("query.fas") + run_mmseqs( + mmseqs, + ["createdb", query_file, base.joinpath("qdb"), "--shuffle", "0", "--dbtype", "1"], + ) + shutil.copy(base.joinpath("org-qdb.lookup"), base.joinpath("qdb.lookup")) + + + # create profile + prof_param = f"--sub-mat aa:blosum62.out,nucl:nucleotide.out -e 0.1 --mask-profile 1 --e-profile 0.1 --comp-bias-corr 1 --comp-bias-corr-scale 1 --wg 0 --allow-deletion 0 --filter-msa 1 --filter-min-enable 0 --max-seq-id 0.9 --qid 0.0 --qsc -20 --cov 0 --diff 1000 --pseudo-cnt-mode 0 --pca substitution:1.100,context:1.400 --pcb substitution:4.100,context:5.800 --db-load-mode 0 --gap-open aa:11,nucl:5 --gap-extend aa:1,nucl:2 --threads {threads} --compressed 0 -v 3 --profile-output-mode 0" + run_mmseqs( + mmseqs, + ["result2profile", base.joinpath("qdb"), dbbase.joinpath(db), + base.joinpath("tmp/latest/aln_0"), base.joinpath("tmp/latest/profile_0")] + prof_param.split(), + ) + run_mmseqs( + mmseqs, + ["result2profile", base.joinpath("tmp/latest/profile_0"), dbbase.joinpath(db), + base.joinpath("tmp/latest/aln_1"), base.joinpath("prof_res")] + prof_param.split(), + ) + + ### + + run_mmseqs(mmseqs, ["pairaln", base.joinpath("qdb"), dbbase.joinpath(f"{db}"), base.joinpath("res_exp_realign"), base.joinpath("res_exp_realign_pair"), "--db-load-mode", str(db_load_mode), "--pairing-mode", str(pairing_strategy), "--pairing-dummy-mode", "0", "--threads", str(threads), ],) + + run_mmseqs(mmseqs, ["align", base.joinpath("prof_res"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res_exp_realign_pair"), base.joinpath("res_exp_realign_pair_bt"), "--db-load-mode", str(db_load_mode), "-e", "inf", "-a", "--threads", str(threads), ],) + run_mmseqs(mmseqs, ["pairaln", base.joinpath("qdb"), dbbase.joinpath(f"{db}"), base.joinpath("res_exp_realign_pair_bt"), base.joinpath("res_final"), "--db-load-mode", str(db_load_mode), "--pairing-mode", str(pairing_strategy), "--pairing-dummy-mode", "1", "--threads", str(threads),],) + run_mmseqs(mmseqs, ["result2msa", base.joinpath("qdb"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res_final"), base.joinpath("pair.a3m"), "--db-load-mode", str(db_load_mode), "--msa-format-mode", "5", "--threads", str(threads),],) + + if unpack: + run_mmseqs(mmseqs, ["unpackdb", base.joinpath("pair.a3m"), base.joinpath("."), "--unpack-name-mode", "0", "--unpack-suffix", output,],) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("pair.a3m")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign_pair")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign_pair_bt")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_final")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) + shutil.rmtree(base.joinpath("tmp")) + # @formatter:on + # fmt: on + +def main(): + parser = ArgumentParser(formatter_class=ArgumentDefaultsHelpFormatter) + parser.add_argument( + "query", + type=Path, + help="fasta files with the queries.", + ) + parser.add_argument( + "dbbase", + type=Path, + help="The path to the database and indices you downloaded and created with setup_databases.sh", + ) + parser.add_argument( + "base", type=Path, help="Directory for the results (and intermediate files)" + ) + parser.add_argument( + "--prefilter-mode", + type=int, + default=0, + choices=[0, 1, 2], + help="Prefiltering algorithm to use: 0: k-mer (high-mem), 1: ungapped (high-cpu), 2: exhaustive (no prefilter, very slow). See wiki for more details: https://github.com/sokrypton/ColabFold/wiki#colabfold_search", + ) + parser.add_argument( + "-s", + type=float, + default=None, + help="MMseqs2 sensitivity. Lowering this will result in a much faster search but possibly sparser MSAs. By default, the k-mer threshold is directly set to the same one of the server, which corresponds to a sensitivity of ~8.", + ) + # dbs are uniref, templates and environmental + # We normally don't use templates + parser.add_argument( + "--db1", type=Path, default=Path("uniref30_2302_db"), help="UniRef database" + ) + parser.add_argument("--db2", type=Path, default=Path(""), help="Templates database") + parser.add_argument( + "--db3", + type=Path, + default=Path("colabfold_envdb_202108_db"), + help="Environmental database", + ) + parser.add_argument("--db4", type=Path, default=Path("spire_ctg10_2401_db"), help="Environmental pairing database") + + # poor man's boolean arguments + parser.add_argument( + "--use-env", type=int, default=1, choices=[0, 1], help="Use --db3" + ) + parser.add_argument( + "--use-env-pairing", type=int, default=0, choices=[0, 1], help="Use --db4" + ) + parser.add_argument( + "--use-templates", type=int, default=0, choices=[0, 1], help="Use --db2" + ) + parser.add_argument( + "--filter", + type=int, + default=1, + choices=[0, 1], + help="Filter the MSA by pre-defined align_eval, qsc, max_accept", + ) + + # mmseqs params + parser.add_argument( + "--mmseqs", + type=Path, + default=Path("mmseqs"), + help="Location of the mmseqs binary.", + ) + parser.add_argument( + "--expand-eval", + type=float, + default=math.inf, + help="e-val threshold for 'expandaln'.", + ) + parser.add_argument( + "--align-eval", type=int, default=10, help="e-val threshold for 'align'." + ) + parser.add_argument( + "--diff", + type=int, + default=3000, + help="filterresult - Keep at least this many seqs in each MSA block.", + ) + parser.add_argument( + "--qsc", + type=float, + default=-20.0, + help="filterresult - reduce diversity of output MSAs using min score thresh.", + ) + parser.add_argument( + "--max-accept", + type=int, + default=1000000, + help="align - Maximum accepted alignments before alignment calculation for a query is stopped.", + ) + parser.add_argument( + "--pairing_strategy", type=int, default=0, help="pairaln - Pairing strategy." + ) + parser.add_argument( + "--db-load-mode", + type=int, + default=0, + help="Database preload mode 0: auto, 1: fread, 2: mmap, 3: mmap+touch", + ) + parser.add_argument( + "--unpack", type=int, default=1, choices=[0, 1], help="Unpack results to loose files or keep MMseqs2 databases." + ) + parser.add_argument( + "--threads", type=int, default=64, help="Number of threads to use." + ) + parser.add_argument( + "--gpu", type=int, default=0, choices=[0, 1], help="Whether to use GPU (1) or not (0). Control number of GPUs with CUDA_VISIBLE_DEVICES env var." + ) + parser.add_argument( + "--gpu-server", type=int, default=0, choices=[0, 1], help="Whether to use GPU server (1) or not (0)" + ) + + # AlphaFold3 relevant params + parser.add_argument( + "--af3-json", action="store_true", help="Generate input JSON for AlphaFold3 from the provided FASTA/A3M file." + ) + parser.add_argument( + "--af3-msa-as-path", action="store_true", help="Save MSA as a file path instead of a string in the JSON." + ) + args = parser.parse_args() + + logging.basicConfig(level = logging.INFO) + + queries, is_complex = get_queries(args.query, None) + + monomor_seqs = set() + multimer_seqs = set() + queries_unique = [] + overall_unique_seqs = [] + seq_map = [] + for job_number, (raw_jobname, query_sequences, a3m_lines, other_molecules) in enumerate(queries): + # remove duplicates before searching + query_sequences = ( + [query_sequences] if isinstance(query_sequences, str) else query_sequences + ) + if len(query_sequences) == 1: + monomor_seqs.add(query_sequences[0]) + else: + multimer_seqs.update(query_sequences) + + query_seqs_unique = [] + for x in query_sequences: + if x not in query_seqs_unique: + query_seqs_unique.append(x) + + if x not in overall_unique_seqs: + overall_unique_seqs.append(x) + + + query_seqs_cardinality = [0] * len(query_seqs_unique) + for seq in query_sequences: + seq_idx = query_seqs_unique.index(seq) + query_seqs_cardinality[seq_idx] += 1 + + queries_unique.append([raw_jobname, query_seqs_unique, query_seqs_cardinality, other_molecules]) + # Ziad added + + monomor_seqs = monomor_seqs.difference(multimer_seqs) + + for job_number, (raw_jobname, query_sequences, a3m_lines, other_molecules) in enumerate(queries): + seq_map.append([]) + query_seqs_unique = [] + query_sequences = ( + [query_sequences] if isinstance(query_sequences, str) else query_sequences + ) + for x in query_sequences: + if x not in query_seqs_unique: + query_seqs_unique.append(x) + seq_map[job_number].append(overall_unique_seqs.index(x)) + + args.base.mkdir(exist_ok=True, parents=True) + + query_file = args.base.joinpath("original-query.fas") + with query_file.open("w") as f: + for job_number, ( + raw_jobname, + query_sequences, + query_seqs_cardinality, + _ + ) in enumerate(queries_unique): + for j, seq in enumerate(query_sequences): + # The header of first sequence set as 101 + query_seq_headername = 101 + j + f.write(f">{query_seq_headername}\n{seq}\n") + + query_file = args.base.joinpath("query.fas") + with query_file.open("w") as f: + for j, seq in enumerate(overall_unique_seqs): + # The header of first sequence set as 101 + query_seq_headername = 101 + j + f.write(f">{query_seq_headername}\n{seq}\n") + + run_mmseqs( + args.mmseqs, + ["createdb", query_file, args.base.joinpath("qdb"), "--shuffle", "0", "--dbtype", "1"], + ) + with args.base.joinpath("qdb.lookup").open("w") as f: + id = 0 + file_number = 0 + for job_number, ( + raw_jobname, + query_sequences, + query_seqs_cardinality, + _ + ) in enumerate(queries_unique): + for seq in query_sequences: + raw_jobname_first = raw_jobname.split()[0] + f.write(f"{id}\t{raw_jobname_first}\t{file_number}\n") + id += 1 + file_number += 1 + shutil.copy(args.base.joinpath("qdb.lookup"), args.base.joinpath("org-qdb.lookup")) + + mmseqs_search_monomer( + mmseqs=args.mmseqs, + dbbase=args.dbbase, + base=args.base, + uniref_db=args.db1, + template_db=args.db2, + metagenomic_db=args.db3, + use_env=args.use_env, + use_templates=args.use_templates, + filter=args.filter, + expand_eval=args.expand_eval, + align_eval=args.align_eval, + diff=args.diff, + qsc=args.qsc, + max_accept=args.max_accept, + prefilter_mode=args.prefilter_mode, + s=args.s, + db_load_mode=args.db_load_mode, + threads=args.threads, + gpu=args.gpu, + gpu_server=args.gpu_server, + unpack=args.unpack, + ) + ## + #exit() + for seq_id in range(len(overall_unique_seqs)): + shutil.copy(args.base.joinpath(f"{seq_id}.a3m"), args.base.joinpath(f"u-{seq_id}.a3m")) + seq_itr = 0 + for seqs in seq_map: + for j, seq_index in enumerate(seqs): + #if seq_index == seq_id: + a3m_content = open(args.base.joinpath(f"u-{seq_index}.a3m"), "r").readlines() + header = a3m_content[0] + new_header = f">{101 + j}\n" + with open(args.base.joinpath(f"{seq_itr}.a3m"), "w") as out_f: + for line in a3m_content: + out_f.write(line.replace(header, new_header)) + seq_itr += 1 + + #exit() + for seq_id in range(len(overall_unique_seqs)): + os.remove(args.base.joinpath(f"u-{seq_id}.a3m")) + ## finish monomors and keep going for hybrid batch + ## + if is_complex is True: + mmseqs_search_pair( + mmseqs=args.mmseqs, + dbbase=args.dbbase, + base=args.base, + uniref_db=args.db1, + prefilter_mode=args.prefilter_mode, + s=args.s, + db_load_mode=args.db_load_mode, + threads=args.threads, + gpu=args.gpu, + gpu_server=args.gpu_server, + pairing_strategy=args.pairing_strategy, + pair_env=False, + unpack=args.unpack, + seq_map=seq_map + ) + #exit() + if args.use_env_pairing: + mmseqs_search_pair( + mmseqs=args.mmseqs, + dbbase=args.dbbase, + base=args.base, + uniref_db=args.db1, + spire_db=args.db4, + prefilter_mode=args.prefilter_mode, + s=args.s, + db_load_mode=args.db_load_mode, + threads=args.threads, + gpu=args.gpu, + gpu_server=args.gpu_server, + pairing_strategy=args.pairing_strategy, + pair_env=True, + unpack=args.unpack, + ) + #exit() + if args.unpack or args.af3_json: + id = 0 + for job_number, ( + raw_jobname, + query_sequences, + query_seqs_cardinality, + other_molecules, + ) in enumerate(queries_unique): + unpaired_msa = [] + paired_msa = None + if len(query_seqs_cardinality) > 1: + paired_msa = [] + for seq in query_sequences: + with args.base.joinpath(f"{id}.a3m").open("r") as f: + unpaired_msa.append(f.read()) + if args.af3_json: + args.base.joinpath(f"{id}.a3m").unlink() + + if args.use_env_pairing: + with open(args.base.joinpath(f"{id}.paired.a3m"), 'a') as file_pair: + with open(args.base.joinpath(f"{id}.env.paired.a3m"), 'r') as file_pair_env: + while chunk := file_pair_env.read(10 * 1024 * 1024): + file_pair.write(chunk) + if args.unpack: + args.base.joinpath(f"{id}.env.paired.a3m").unlink() + + if len(query_seqs_cardinality) > 1: + with args.base.joinpath(f"{id}.paired.a3m").open("r") as f: + paired_msa.append(f.read()) + if args.unpack: + args.base.joinpath(f"{id}.paired.a3m").unlink() + #os.remove(args.base.joinpath(f"{id}.a3m")) + id += 1 + + if args.af3_json: + af3 = AF3Utils(raw_jobname, query_sequences, query_seqs_cardinality, unpaired_msa, paired_msa, other_molecules) + with open(args.base.joinpath(f"{job_number}.json"), 'w') as f: + f.write(json.dumps(af3.content, indent=4)) + + if args.unpack: + msa = msa_to_str( + unpaired_msa, paired_msa, query_sequences, query_seqs_cardinality + ) + args.base.joinpath(f"{job_number}.a3m").write_text(msa) + #exit() + #os.remove(args.base.joinpath("res_exp_realign-minimal.index")) + #os.remove(args.base.joinpath("res_exp_realign-minimal")) + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("res_exp_realign-minimal")]) + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb-minimal")]) + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb-minimal_h")]) + + + + else: + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("res")]) + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("prof_res")]) + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("prof_res_h")]) + os.remove(args.base.joinpath("original-query.fas")) + + if args.af3_json: + id = 0 + for job_number, (raw_jobname, query_sequences, query_seqs_cardinality, other_molecules) in enumerate(queries_unique): + unpaired_msa = [] + for seq in query_sequences: + with args.base.joinpath(f"{id}.a3m").open("r") as f: + unpaired_msa.append(f.read()) + os.remove(args.base.joinpath(f"{id}.a3m")) + id += 1 + + # Create AF3Utils object and write JSON + af3 = AF3Utils(raw_jobname, query_sequences, query_seqs_cardinality, unpaired_msa, None, other_molecules) + with open(args.base.joinpath(f"{job_number}.json"), 'w') as f: + f.write(json.dumps(af3.content, indent=4)) + + if args.unpack: + # rename a3m files + rename_output(queries_unique, "a3m", args.base) + + # rename m8 files + if args.use_templates: + id = 0 + for raw_jobname, query_sequences, query_seqs_cardinality, _ in queries_unique: + with args.base.joinpath(f"{safe_filename(raw_jobname)}_{args.db2}.m8").open( + "w" + ) as f: + for _ in range(len(query_seqs_cardinality)): + with args.base.joinpath(f"{id}.m8").open("r") as g: + f.write(g.read()) + os.remove(args.base.joinpath(f"{id}.m8")) + id += 1 + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb")]) + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb_h")]) + + if args.af3_json: + # rename json files + rename_output(queries_unique, "json", args.base) + + query_file.unlink() + os.remove(args.base.joinpath("org-qdb.lookup")) + + +if __name__ == "__main__": + main() diff --git a/bin/msa_manager.py b/bin/msa_manager.py new file mode 100755 index 0000000..242f0a9 --- /dev/null +++ b/bin/msa_manager.py @@ -0,0 +1,125 @@ +#!/usr/bin/env python3 +import os +import string +import argparse + + +MAX_MSA_SEQS = 16384 +MAX_PAIRED_SEQS = 8192 +ID_CHARS = list(string.ascii_uppercase) + list(string.ascii_lowercase) + [str(x) for x in range(10)] + + +def get_sub_sequences(seq_lengths, whole_seq): + out_seqs = [] + curr_seq = "" + curr_seq_itr = 0 + total_letters = 0 + for letter in whole_seq: + curr_seq += letter + if letter.isupper() or letter == "-": + total_letters += 1 + if total_letters == seq_lengths[curr_seq_itr]: + out_seqs.append(curr_seq) + curr_seq = "" + curr_seq_itr += 1 + total_letters = 0 + + if len(out_seqs) != len(seq_lengths): + print("Something wrong in the input file, could not generate the required number of sequences") + exit(1) + + return out_seqs + + +def parse_msa(msa_path, output_dir, meta_id): + os.makedirs(output_dir, exist_ok=True) + homolog = "" + section_index = 0 + + with open(msa_path, "r") as file: + first_line = file.readline() + if not first_line.startswith("#"): + homologs_lengths = [len(file.readline().strip('\n'))] + sequence_groups = [[[],[]]] + is_multimer = False + else: + homologs_lengths = [int(x.strip()) for x in first_line.replace('#',"").split()[0].split(",")] + sequence_groups = [[[], []] for _ in range(len(homologs_lengths))] + is_multimer = True + + with open(msa_path, "r") as file: + if is_multimer: + file.readline() + header_line = file.readline().strip()[1:] + expected_section_headers = [x.strip() for x in header_line.split()] + current_header = header_line + first_seq = False + for line in file: + line = line.strip() + if line.startswith(">"): + if homolog: + if first_seq and section_index > 0: + first_seq = False + else: + sub_sequences = get_sub_sequences(homologs_lengths, homolog) + for seq_index in range(len(homologs_lengths)): + if section_index == 0: + if len(sequence_groups[seq_index][0]) < MAX_PAIRED_SEQS: + sequence_groups[seq_index][0].append(sub_sequences[seq_index]) + else: + if seq_index == section_index - 1: + if len(sequence_groups[seq_index][1]) + len(sequence_groups[seq_index][0]) < MAX_MSA_SEQS: + sequence_groups[seq_index][1].append(sub_sequences[seq_index]) + + homolog = "" + current_header = line[1:].strip() + + if section_index < len(homologs_lengths) and current_header == expected_section_headers[section_index]: + section_index += 1 + first_seq = True + else: + homolog += line + if homolog: + if first_seq and section_index > 0: + first_seq = False + else: + sub_sequences = get_sub_sequences(homologs_lengths, homolog) + for seq_index in range(len(homologs_lengths)): + if section_index == 0: + if len(sequence_groups[seq_index][0]) < MAX_PAIRED_SEQS: + sequence_groups[seq_index][0].append(sub_sequences[seq_index]) + else: + if seq_index == section_index - 1: + if len(sequence_groups[seq_index][1]) + len(sequence_groups[seq_index][0]) < MAX_MSA_SEQS: + sequence_groups[seq_index][1].append(sub_sequences[seq_index]) + + for seq_index in range(len(homologs_lengths)): + filename = os.path.join(output_dir, f"{meta_id}_{seq_index}.csv") + with open(filename, "w") as out_file: + out_file.write("key,sequence\n") + if len(homologs_lengths)==1: #Homo-oligomer: all sequences are paired + paired_sequences = sequence_groups[seq_index][0]+sequence_groups[seq_index][1] + for i, seq in enumerate(paired_sequences): + out_file.write(f"{i},{seq}\n") + else: + paired_sequences = sequence_groups[seq_index][0] + for i, seq in enumerate(paired_sequences, start=1): + out_file.write(f"{i},{seq}\n") + + unpaired_sequences = sequence_groups[seq_index][1] + for seq in unpaired_sequences: + out_file.write(f"-1,{seq}\n") + + +def main(): + parser = argparse.ArgumentParser(description="Split multi-A3M file into CSV sequences per section.") + parser.add_argument("msa_path", help="Path to input .a3m file") + parser.add_argument("-o", "--output_dir", default="output_msa", help="Directory to write output CSVs") + parser.add_argument("--meta_id", default="default", help="Prefix for MSA files") + + args = parser.parse_args() + parse_msa(args.msa_path, args.output_dir, args.meta_id) + + +if __name__ == "__main__": + main() diff --git a/bin/utils.py b/bin/utils.py new file mode 100755 index 0000000..60f2f1c --- /dev/null +++ b/bin/utils.py @@ -0,0 +1,112 @@ +import importlib.util +import numpy as np +bio_is_installed = importlib.util.find_spec("Bio") is not None + +def _convert_plddt_to_100(res_plddt): + if (res_plddt < 1): # Converting to a [0,100] range + res_plddt *= 100 + return res_plddt + + +def plddt_from_struct_b_factor_adhoc(struct_file): + """ + Uses ad hoc PDB parser to extract residue pLDDT values from the b-factor column. Iterates over PDB objects rather than processes raw file + """ + #NOTE: this is a temporary hack which is not robust as a general parser. + #Should be temporary - need to check with non-protein entities + if not str(struct_file).endswith(".pdb"): + raise ValueError(f"{struct_file} must be a PDB file!") + + res_plddts = [] + resid_prev = -1 + atom_plddt_list = [] + + with open(struct_file) as f: + for line in f: + if not line.startswith('ATOM'): continue + resid = int(line[23:26].strip()) + if resid == resid_prev: + atom_plddt_list.append(float(line[61:66].strip())) + else: + if resid_prev == -1: + resid_prev = resid + continue + res_plddt = sum(atom_plddt_list)/len(atom_plddt_list) + res_plddt = _convert_plddt_to_100(res_plddt) + res_plddts.append(res_plddt) + resid_prev = resid + + # Reset atom tracking + atom_plddt_list = [] + atom_plddt_list.append(float(line[61:66].strip())) + + res_plddt = sum(atom_plddt_list)/len(atom_plddt_list) + res_plddt = _convert_plddt_to_100(res_plddt) + res_plddts.append(res_plddt) + + res_plddts = np.array(res_plddts) + res_plddts = np.round(res_plddts, 2) + + return res_plddts + +def get_chain_ids(struct_file): + from Bio import PDB + if str(struct_file).endswith(".pdb"): + parser = PDB.PDBParser(QUIET=True) + structure = parser.get_structure(id=id, file=struct_file) + elif str(struct_file).endswith(".cif"): + parser = PDB.MMCIFParser(QUIET=True) + structure = parser.get_structure(structure_id=id, filename=struct_file) + else: + raise ValueError(f"{struct_file} is neither a PDB or mmCIF file!") + + return [chain.id for chain in structure.get_chains()] + + +def plddt_from_struct_b_factor_biopython(struct_file): + """ + Uses the BioPython PDB package to extract residue pLDDT values from the b-factor column. Iterates over PDB objects rather than processes raw file + """ + from Bio import PDB + if str(struct_file).endswith(".pdb"): + parser = PDB.PDBParser(QUIET=True) + structure = parser.get_structure(id=id, file=struct_file) + elif str(struct_file).endswith(".cif"): + parser = PDB.MMCIFParser(QUIET=True) + structure = parser.get_structure(structure_id=id, filename=struct_file) + else: + raise ValueError(f"{struct_file} is neither a PDB or mmCIF file!") + +# res_list = [] + res_plddts = [] +# plddt_tot = 0 + + for model in structure: + for chain in model: + chain_res_list = chain.get_unpacked_list() +# res_list.extend(chain_res_list) + for residue in chain: + atom_list = residue.get_unpacked_list() + atom_plddt_tot = 0 + for atom in residue: # ESMFold and others have separate atom-wise values, so doing atom-wise to cover that and residue-wise + atom_plddt = atom.get_bfactor() + atom_plddt_tot += atom_plddt + + res_plddt = float(atom_plddt_tot / len(atom_list)) + + if (res_plddt < 1): # RFAA the multiplication of mean isn't failing. Anyway covering to a [0,100] range for any structure file1 + res_plddt *= 100 + res_plddt = _convert_plddt_to_100(res_plddt) + + res_plddts.append(res_plddt) +# plddt_tot += res_plddt + + res_plddts = np.array(res_plddts) + res_plddts = np.round(res_plddts, 2) + + return res_plddts + +if bio_is_installed: + plddt_from_struct_b_factor = plddt_from_struct_b_factor_biopython +else: + plddt_from_struct_b_factor = plddt_from_struct_b_factor_adhoc diff --git a/bin/zt-search.py b/bin/zt-search.py new file mode 100755 index 0000000..5026066 --- /dev/null +++ b/bin/zt-search.py @@ -0,0 +1,802 @@ +#!/opt/miniforge/bin/python3 +""" +#!/usr/local/bin/python3 + +Functionality for running mmseqs locally. Takes in a fasta file, outputs final.a3m +""" +import logging +import math +import os +import shutil +import subprocess +import json +from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter +from pathlib import Path +from typing import List, Optional, Tuple, Union, Dict +import random + +from input import get_queries, msa_to_str, safe_filename +from utils import AF3Utils + + +logger = logging.getLogger(__name__) + +MODULE_OUTPUT_POS = { + "align": 4, + "convertalis": 4, + "expandaln": 5, + "filterresult": 4, + "lndb": 2, + "mergedbs": 2, + "mvdb": 2, + "pairaln": 4, + "result2msa": 4, + "search": 3, +} + +def rename_output(queries_unique, ext, base): + for job_number, (raw_jobname, query_sequences, query_seqs_cardinality, other_molecules) in enumerate(queries_unique): + os.rename( + base.joinpath(f"{job_number}.{ext}"), + base.joinpath(f"{safe_filename(raw_jobname)}.{ext}"), + ) + +def expand_db(db_path, seq_map, overwrite=True): + index_data = [] + with open(f"{db_path}.index", "r") as in_f: + for line in in_f: + index_data.append([int(x) for x in line.strip().split()]) + + print(index_data) + new_index = "" + offset = 0 + seq_itr = 0 + with open(f"{db_path}-tmp", "wb") as out_file: + for seqs in seq_map: + for seq_index in seqs: + start_byte = index_data[seq_index][1] + byte_cnt = index_data[seq_index][2] + print(start_byte, byte_cnt, index_data[seq_index]) + with open(f"{db_path}", "rb") as f: + f.seek(start_byte) + out_file.write(f.read(byte_cnt)) + new_index += f"{seq_itr}\t{offset}\t{byte_cnt}\n" + offset += index_data[seq_index][2] + seq_itr += 1 + + with open(f"{db_path}-tmp.index", "w") as out_f: + out_f.write(new_index) + + if overwrite: + os.rename(f"{db_path}-tmp.index", f"{db_path}.index") + os.rename(f"{db_path}-tmp", f"{db_path}") + +def run_mmseqs(mmseqs: Path, params: List[Union[str, Path]]): + module = params[0] + if module in MODULE_OUTPUT_POS: + output_pos = MODULE_OUTPUT_POS[module] + output_path = Path(params[output_pos]).with_suffix('.dbtype') + if output_path.exists(): + logger.info(f"Skipping {module} because {output_path} already exists") + return + + params_log = " ".join(str(i) for i in params) + logger.info(f"Running {mmseqs} {params_log}") + # hide MMseqs2 verbose paramters list that clogs up the log + os.environ["MMSEQS_CALL_DEPTH"] = "1" + os.environ["MMSEQS_FORCE_MERGE"] = "True" + subprocess.check_call([mmseqs] + params) + + +def mmseqs_search_monomer( + dbbase: Path, + base: Path, + uniref_db: Path = Path("uniref30_2302_db"), + template_db: Path = Path(""), # Unused by default + metagenomic_db: Path = Path("colabfold_envdb_202108_db"), + mmseqs: Path = Path("mmseqs"), + use_env: bool = True, + use_templates: bool = False, + filter: bool = True, + expand_eval: float = math.inf, + align_eval: int = 10, + diff: int = 3000, + qsc: float = -20.0, + max_accept: int = 1000000, + prefilter_mode: int = 0, + s: float = 8, + db_load_mode: int = 2, + threads: int = 32, + gpu: int = 0, + gpu_server: int = 0, + unpack: bool = True, +): + """Run mmseqs with a local colabfold database set + + db1: uniprot db (UniRef30) + db2: Template (unused by default) + db3: metagenomic db (colabfold_envdb_202108 or bfd_mgy_colabfold, the former is preferred) + """ + if filter: + # 0.1 was not used in benchmarks due to POSIX shell bug in line above + # EXPAND_EVAL=0.1 + align_eval = 10 + qsc = 0.8 + max_accept = 100000 + + used_dbs = [uniref_db] + if use_templates: + used_dbs.append(template_db) + if use_env: + used_dbs.append(metagenomic_db) + + for db in used_dbs: + if not dbbase.joinpath(f"{db}.dbtype").is_file(): + raise FileNotFoundError(f"Database {db} does not exist") + if ( + ( + not dbbase.joinpath(f"{db}.idx").is_file() + and not dbbase.joinpath(f"{db}.idx.index").is_file() + ) + or os.environ.get("MMSEQS_IGNORE_INDEX", False) + ): + logger.info("Search does not use index") + db_load_mode = 0 + dbSuffix1 = "_seq" + dbSuffix2 = "_aln" + dbSuffix3 = "" + else: + dbSuffix1 = ".idx" + dbSuffix2 = ".idx" + dbSuffix3 = ".idx" + + search_param = ["--num-iterations", "3", "--db-load-mode", str(db_load_mode), "-a", "-e", "0.1", "--max-seqs", "10000"] + template_search_param = [] + if gpu: + search_param += ["--gpu", str(gpu), "--prefilter-mode", "1"] # gpu version only supports ungapped prefilter currently + template_search_param += ["--gpu", str(gpu), "--prefilter-mode", "1"] + else: + search_param += ["--prefilter-mode", str(prefilter_mode)] + template_search_param += ["-s", "7.5", "--prefilter-mode", str(prefilter_mode)] + if s is not None: # sensitivy can only be set for non-gpu version, gpu version runs at max sensitivity + search_param += ["-s", "{:.1f}".format(s)] + else: + search_param += ["--k-score", "'seq:96,prof:80'"] + if gpu_server: + search_param += ["--gpu-server", str(gpu_server)] + + filter_param = ["--filter-msa", str(filter), "--filter-min-enable", "1000", "--diff", str(diff), "--qid", "0.0,0.2,0.4,0.6,0.8,1.0", "--qsc", "0", "--max-seq-id", "0.95",] + expand_param = ["--expansion-mode", "0", "-e", str(expand_eval), "--expand-filter-clusters", str(filter), "--max-seq-id", "0.95",] + + if not base.joinpath("uniref.a3m").with_suffix('.a3m.dbtype').exists(): + run_mmseqs(mmseqs, ["search", base.joinpath("qdb"), dbbase.joinpath(uniref_db), base.joinpath("res"), base.joinpath("tmp"), "--threads", str(threads)] + search_param) + os.mkdir(base.joinpath("kept_data")) + run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/profile_1"), base.joinpath("prof_res")]) + run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/aln_1"), base.joinpath("kept_data/aln_1")]) + run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/aln_0"), base.joinpath("kept_data/aln_0")]) + #run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/profile_0"), base.joinpath("kept_data/profile_0")]) + #exit() + run_mmseqs(mmseqs, ["lndb", base.joinpath("qdb_h"), base.joinpath("prof_res_h")]) + + run_mmseqs(mmseqs, ["expandaln", base.joinpath("qdb"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), base.joinpath("res"), dbbase.joinpath(f"{uniref_db}{dbSuffix2}"), base.joinpath("res_exp"), "--db-load-mode", str(db_load_mode), "--threads", str(threads)] + expand_param) + run_mmseqs(mmseqs, ["align", base.joinpath("prof_res"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), base.joinpath("res_exp"), base.joinpath("res_exp_realign"), "--db-load-mode", str(db_load_mode), "-e", str(align_eval), "--max-accept", str(max_accept), "--threads", str(threads), "--alt-ali", "10", "-a"]) + run_mmseqs(mmseqs, ["filterresult", base.joinpath("qdb"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), + base.joinpath("res_exp_realign"), base.joinpath("res_exp_realign_filter"), "--db-load-mode", + str(db_load_mode), "--qid", "0", "--qsc", str(qsc), "--diff", "0", "--threads", + str(threads), "--max-seq-id", "1.0", "--filter-min-enable", "100"]) + run_mmseqs(mmseqs, ["result2msa", base.joinpath("qdb"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), + base.joinpath("res_exp_realign_filter"), base.joinpath("uniref.a3m"), "--msa-format-mode", + "6", "--db-load-mode", str(db_load_mode), "--threads", str(threads)] + filter_param) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign_filter")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp")]) + #run_mmseqs(mmseqs, ["rmdb", base.joinpath("res")]) + + else: + logger.info(f"Skipping {uniref_db} search because uniref.a3m already exists") + + if use_env and not base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m").with_suffix('.a3m.dbtype').exists(): + run_mmseqs(mmseqs, ["search", base.joinpath("prof_res"), dbbase.joinpath(metagenomic_db), base.joinpath("res_env"), + base.joinpath("tmp3"), "--threads", str(threads)] + search_param) + run_mmseqs(mmseqs, ["expandaln", base.joinpath("prof_res"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), base.joinpath("res_env"), + dbbase.joinpath(f"{metagenomic_db}{dbSuffix2}"), base.joinpath("res_env_exp"), "-e", str(expand_eval), + "--expansion-mode", "0", "--db-load-mode", str(db_load_mode), "--threads", str(threads)]) + run_mmseqs(mmseqs, ["align", base.joinpath("tmp3/latest/profile_1"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), + base.joinpath("res_env_exp"), base.joinpath("res_env_exp_realign"), "--db-load-mode", + str(db_load_mode), "-e", str(align_eval), "--max-accept", str(max_accept), "--threads", + str(threads), "--alt-ali", "10", "-a"]) + run_mmseqs(mmseqs, ["filterresult", base.joinpath("qdb"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), + base.joinpath("res_env_exp_realign"), base.joinpath("res_env_exp_realign_filter"), + "--db-load-mode", str(db_load_mode), "--qid", "0", "--qsc", str(qsc), "--diff", "0", + "--max-seq-id", "1.0", "--threads", str(threads), "--filter-min-enable", "100"]) + run_mmseqs(mmseqs, ["result2msa", base.joinpath("qdb"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), + base.joinpath("res_env_exp_realign_filter"), + base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m"), "--msa-format-mode", "6", + "--db-load-mode", str(db_load_mode), "--threads", str(threads)] + filter_param) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env_exp_realign_filter")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env_exp_realign")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env_exp")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env")]) + elif use_env: + logger.info(f"Skipping {metagenomic_db} search because bfd.mgnify30.metaeuk30.smag30.a3m already exists") + + if use_templates and not base.joinpath(f"{template_db}.m8").with_suffix('.m8.dbtype').exists(): + run_mmseqs(mmseqs, ["search", base.joinpath("prof_res"), dbbase.joinpath(template_db), base.joinpath("res_pdb"), + base.joinpath("tmp2"), "--db-load-mode", str(db_load_mode), "--threads", str(threads), "-a", "-e", "0.1"] + template_search_param) + run_mmseqs(mmseqs, ["convertalis", base.joinpath("prof_res"), dbbase.joinpath(f"{template_db}{dbSuffix3}"), base.joinpath("res_pdb"), + base.joinpath(f"{template_db}"), "--format-output", + "query,target,fident,alnlen,mismatch,gapopen,qstart,qend,tstart,tend,evalue,bits,cigar", + "--db-output", "1", + "--db-load-mode", str(db_load_mode), "--threads", str(threads)]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_pdb")]) + elif use_templates: + logger.info(f"Skipping {template_db} search because {template_db}.m8 already exists") + + if use_env: + run_mmseqs(mmseqs, ["mergedbs", base.joinpath("qdb"), base.joinpath("final.a3m"), base.joinpath("uniref.a3m"), base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("uniref.a3m")]) + else: + run_mmseqs(mmseqs, ["mvdb", base.joinpath("uniref.a3m"), base.joinpath("final.a3m")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("uniref.a3m")]) + + if unpack: + run_mmseqs(mmseqs, ["unpackdb", base.joinpath("final.a3m"), base.joinpath("."), "--unpack-name-mode", "0", "--unpack-suffix", ".a3m"]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("final.a3m")]) + + if use_templates: + run_mmseqs(mmseqs, ["unpackdb", base.joinpath(f"{template_db}"), base.joinpath("."), "--unpack-name-mode", "0", "--unpack-suffix", ".m8"]) + if base.joinpath(f"{template_db}").exists(): + run_mmseqs(mmseqs, ["rmdb", base.joinpath(f"{template_db}")]) + + #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) + #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) + shutil.rmtree(base.joinpath("tmp")) + if use_templates: + shutil.rmtree(base.joinpath("tmp2")) + if use_env: + shutil.rmtree(base.joinpath("tmp3")) + +def mmseqs_search_pair( + dbbase: Path, + base: Path, + uniref_db: Path = Path("uniref30_2302_db"), + spire_db: Path = Path("spire_ctg10_2401_db"), + mmseqs: Path = Path("mmseqs"), + pair_env: bool = True, + prefilter_mode: int = 0, + s: float = 8, + threads: int = 64, + gpu: bool = False, + gpu_server: bool = False, + db_load_mode: int = 2, + pairing_strategy: int = 0, + unpack: bool = True, + seq_map: list=[], +): + if not dbbase.joinpath(f"{uniref_db}.dbtype").is_file(): + raise FileNotFoundError(f"Database {uniref_db} does not exist") + if ( + ( + not dbbase.joinpath(f"{uniref_db}.idx").is_file() + and not dbbase.joinpath(f"{uniref_db}.idx.index").is_file() + ) + or os.environ.get("MMSEQS_IGNORE_INDEX", False) + ): + logger.info("Search does not use index") + db_load_mode = 0 + dbSuffix1 = "_seq" + dbSuffix2 = "_aln" + else: + dbSuffix1 = ".idx" + dbSuffix2 = ".idx" + + if pair_env: + db = spire_db + output = ".env.paired.a3m" + else: + db = uniref_db + output = ".paired.a3m" + + # fmt: off + # @formatter:off + search_param = ["--num-iterations", "3", "--db-load-mode", str(db_load_mode), "-a", "-e", "0.1", "--max-seqs", "10000",] + if gpu: + search_param += ["--gpu", str(gpu), "--prefilter-mode", "1"] # gpu version only supports ungapped prefilter currently + else: + search_param += ["--prefilter-mode", str(prefilter_mode)] + if s is not None: # sensitivy can only be set for non-gpu version, gpu version runs at max sensitivity + search_param += ["-s", "{:.1f}".format(s)] + else: + search_param += ["--k-score", "'seq:96,prof:80'"] + if gpu_server: + search_param += ["--gpu-server", str(gpu_server)] + expand_param = ["--expansion-mode", "0", "-e", "inf", "--expand-filter-clusters", "0", "--max-seq-id", "0.95",] + + if db != uniref_db: + # cleaning + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) + + run_mmseqs(mmseqs, ["search", base.joinpath("qdb"), dbbase.joinpath(db), base.joinpath("res"), base.joinpath("tmp"), "--threads", str(threads),] + search_param,) + run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/profile_1"), base.joinpath("prof_res")]) + run_mmseqs(mmseqs, ["lndb", base.joinpath("qdb_h"), base.joinpath("prof_res_h")]) + else: + os.makedirs(base.joinpath("tmp/latest")) + run_mmseqs(mmseqs, ["mvdb", base.joinpath("kept_data/aln_0"), base.joinpath("tmp/latest/aln_0")]) + run_mmseqs(mmseqs, ["mvdb", base.joinpath("kept_data/aln_1"), base.joinpath("tmp/latest/aln_1")]) + #run_mmseqs(mmseqs, ["mvdb", base.joinpath("kept_data/profile_0"), base.joinpath("tmp/latest/profile_0")]) + shutil.rmtree(base.joinpath("kept_data")) + + run_mmseqs(mmseqs, ["expandaln", base.joinpath("qdb"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res"), dbbase.joinpath(f"{db}{dbSuffix2}"), base.joinpath("res_exp"), "--db-load-mode", str(db_load_mode), "--threads", str(threads),] + expand_param,) + run_mmseqs(mmseqs, ["align", base.joinpath("prof_res"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res_exp"), base.joinpath("res_exp_realign"), "--db-load-mode", str(db_load_mode), "-e", "0.001", "--max-accept", "1000000", "--threads", str(threads),],) + + # Added by Ziad + #shutil.copy(base.joinpath("res_exp_realign"), base.joinpath("res_exp_realign-minimal")) + #shutil.copy(base.joinpath("res_exp_realign.index"), base.joinpath("res_exp_realign-minimal.index")) + #exit() + run_mmseqs(mmseqs, ["cpdb", base.joinpath("qdb"), base.joinpath("qdb-minimal")]) + + for merged_db in [base.joinpath("res_exp_realign"), base.joinpath("tmp/latest/aln_0"), base.joinpath("tmp/latest/aln_1")]: + print(f"merging {merged_db}") + expand_db(merged_db, seq_map, True) + + os.rename(base.joinpath("original-query.fas"), base.joinpath("query.fas")) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("qdb")]) + query_file = base.joinpath("query.fas") + run_mmseqs( + mmseqs, + ["createdb", query_file, base.joinpath("qdb"), "--shuffle", "0", "--dbtype", "1"], + ) + shutil.copy(base.joinpath("org-qdb.lookup"), base.joinpath("qdb.lookup")) + + ### fix with res + + #exit() + + + # create profile + #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) + #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) + + prof_param = f"--sub-mat aa:blosum62.out,nucl:nucleotide.out -e 0.1 --mask-profile 1 --e-profile 0.1 --comp-bias-corr 1 --comp-bias-corr-scale 1 --wg 0 --allow-deletion 0 --filter-msa 1 --filter-min-enable 0 --max-seq-id 0.9 --qid 0.0 --qsc -20 --cov 0 --diff 1000 --pseudo-cnt-mode 0 --pca substitution:1.100,context:1.400 --pcb substitution:4.100,context:5.800 --db-load-mode 0 --gap-open aa:11,nucl:5 --gap-extend aa:1,nucl:2 --threads {threads} --compressed 0 -v 3 --profile-output-mode 0" + run_mmseqs( + mmseqs, + ["result2profile", base.joinpath("qdb"), dbbase.joinpath(db), + base.joinpath("tmp/latest/aln_0"), base.joinpath("tmp/latest/profile_0")] + prof_param.split(), + ) + run_mmseqs( + mmseqs, + ["result2profile", base.joinpath("tmp/latest/profile_0"), dbbase.joinpath(db), + base.joinpath("tmp/latest/aln_1"), base.joinpath("prof_res")] + prof_param.split(), + ) + + ### + + #exit() + run_mmseqs(mmseqs, ["pairaln", base.joinpath("qdb"), dbbase.joinpath(f"{db}"), base.joinpath("res_exp_realign"), base.joinpath("res_exp_realign_pair"), "--db-load-mode", str(db_load_mode), "--pairing-mode", str(pairing_strategy), "--pairing-dummy-mode", "0", "--threads", str(threads), ],) + + run_mmseqs(mmseqs, ["align", base.joinpath("prof_res"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res_exp_realign_pair"), base.joinpath("res_exp_realign_pair_bt"), "--db-load-mode", str(db_load_mode), "-e", "inf", "-a", "--threads", str(threads), ],) + run_mmseqs(mmseqs, ["pairaln", base.joinpath("qdb"), dbbase.joinpath(f"{db}"), base.joinpath("res_exp_realign_pair_bt"), base.joinpath("res_final"), "--db-load-mode", str(db_load_mode), "--pairing-mode", str(pairing_strategy), "--pairing-dummy-mode", "1", "--threads", str(threads),],) + run_mmseqs(mmseqs, ["result2msa", base.joinpath("qdb"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res_final"), base.joinpath("pair.a3m"), "--db-load-mode", str(db_load_mode), "--msa-format-mode", "5", "--threads", str(threads),],) + + if unpack: + run_mmseqs(mmseqs, ["unpackdb", base.joinpath("pair.a3m"), base.joinpath("."), "--unpack-name-mode", "0", "--unpack-suffix", output,],) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("pair.a3m")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign_pair")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign_pair_bt")]) + run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_final")]) + #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) + #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) + #shutil.rmtree(base.joinpath("tmp")) + # @formatter:on + # fmt: on + +def main(): + parser = ArgumentParser(formatter_class=ArgumentDefaultsHelpFormatter) + parser.add_argument( + "query", + type=Path, + help="fasta files with the queries.", + ) + parser.add_argument( + "dbbase", + type=Path, + help="The path to the database and indices you downloaded and created with setup_databases.sh", + ) + parser.add_argument( + "base", type=Path, help="Directory for the results (and intermediate files)" + ) + parser.add_argument( + "--prefilter-mode", + type=int, + default=0, + choices=[0, 1, 2], + help="Prefiltering algorithm to use: 0: k-mer (high-mem), 1: ungapped (high-cpu), 2: exhaustive (no prefilter, very slow). See wiki for more details: https://github.com/sokrypton/ColabFold/wiki#colabfold_search", + ) + parser.add_argument( + "-s", + type=float, + default=None, + help="MMseqs2 sensitivity. Lowering this will result in a much faster search but possibly sparser MSAs. By default, the k-mer threshold is directly set to the same one of the server, which corresponds to a sensitivity of ~8.", + ) + # dbs are uniref, templates and environmental + # We normally don't use templates + parser.add_argument( + "--db1", type=Path, default=Path("uniref30_2302_db"), help="UniRef database" + ) + parser.add_argument("--db2", type=Path, default=Path(""), help="Templates database") + parser.add_argument( + "--db3", + type=Path, + default=Path("colabfold_envdb_202108_db"), + help="Environmental database", + ) + parser.add_argument("--db4", type=Path, default=Path("spire_ctg10_2401_db"), help="Environmental pairing database") + + # poor man's boolean arguments + parser.add_argument( + "--use-env", type=int, default=1, choices=[0, 1], help="Use --db3" + ) + parser.add_argument( + "--use-env-pairing", type=int, default=0, choices=[0, 1], help="Use --db4" + ) + parser.add_argument( + "--use-templates", type=int, default=0, choices=[0, 1], help="Use --db2" + ) + parser.add_argument( + "--filter", + type=int, + default=1, + choices=[0, 1], + help="Filter the MSA by pre-defined align_eval, qsc, max_accept", + ) + + # mmseqs params + parser.add_argument( + "--mmseqs", + type=Path, + default=Path("mmseqs"), + help="Location of the mmseqs binary.", + ) + parser.add_argument( + "--expand-eval", + type=float, + default=math.inf, + help="e-val threshold for 'expandaln'.", + ) + parser.add_argument( + "--align-eval", type=int, default=10, help="e-val threshold for 'align'." + ) + parser.add_argument( + "--diff", + type=int, + default=3000, + help="filterresult - Keep at least this many seqs in each MSA block.", + ) + parser.add_argument( + "--qsc", + type=float, + default=-20.0, + help="filterresult - reduce diversity of output MSAs using min score thresh.", + ) + parser.add_argument( + "--max-accept", + type=int, + default=1000000, + help="align - Maximum accepted alignments before alignment calculation for a query is stopped.", + ) + parser.add_argument( + "--pairing_strategy", type=int, default=0, help="pairaln - Pairing strategy." + ) + parser.add_argument( + "--db-load-mode", + type=int, + default=0, + help="Database preload mode 0: auto, 1: fread, 2: mmap, 3: mmap+touch", + ) + parser.add_argument( + "--unpack", type=int, default=1, choices=[0, 1], help="Unpack results to loose files or keep MMseqs2 databases." + ) + parser.add_argument( + "--threads", type=int, default=64, help="Number of threads to use." + ) + parser.add_argument( + "--gpu", type=int, default=0, choices=[0, 1], help="Whether to use GPU (1) or not (0). Control number of GPUs with CUDA_VISIBLE_DEVICES env var." + ) + parser.add_argument( + "--gpu-server", type=int, default=0, choices=[0, 1], help="Whether to use GPU server (1) or not (0)" + ) + + # AlphaFold3 relevant params + parser.add_argument( + "--af3-json", action="store_true", help="Generate input JSON for AlphaFold3 from the provided FASTA/A3M file." + ) + parser.add_argument( + "--af3-msa-as-path", action="store_true", help="Save MSA as a file path instead of a string in the JSON." + ) + args = parser.parse_args() + + logging.basicConfig(level = logging.INFO) + + queries, is_complex = get_queries(args.query, None) + + monomor_seqs = set() + multimer_seqs = set() + queries_unique = [] + overall_unique_seqs = [] + seq_map = [] + for job_number, (raw_jobname, query_sequences, a3m_lines, other_molecules) in enumerate(queries): + # remove duplicates before searching + query_sequences = ( + [query_sequences] if isinstance(query_sequences, str) else query_sequences + ) + if len(query_sequences) == 1: + monomor_seqs.add(query_sequences[0]) + else: + multimer_seqs.update(query_sequences) + + query_seqs_unique = [] + for x in query_sequences: + if x not in query_seqs_unique: + query_seqs_unique.append(x) + + if x not in overall_unique_seqs: + overall_unique_seqs.append(x) + + + query_seqs_cardinality = [0] * len(query_seqs_unique) + for seq in query_sequences: + seq_idx = query_seqs_unique.index(seq) + query_seqs_cardinality[seq_idx] += 1 + + queries_unique.append([raw_jobname, query_seqs_unique, query_seqs_cardinality, other_molecules]) + # Ziad added + + monomor_seqs = monomor_seqs.difference(multimer_seqs) + + for job_number, (raw_jobname, query_sequences, a3m_lines, other_molecules) in enumerate(queries): + seq_map.append([]) + query_seqs_unique = [] + query_sequences = ( + [query_sequences] if isinstance(query_sequences, str) else query_sequences + ) + for x in query_sequences: + if x not in query_seqs_unique: + query_seqs_unique.append(x) + seq_map[job_number].append(overall_unique_seqs.index(x)) + + #print(seq_map) + #exit() + args.base.mkdir(exist_ok=True, parents=True) + + # updated by Ziad + query_file = args.base.joinpath("original-query.fas") + with query_file.open("w") as f: + for job_number, ( + raw_jobname, + query_sequences, + query_seqs_cardinality, + _ + ) in enumerate(queries_unique): + for j, seq in enumerate(query_sequences): + # The header of first sequence set as 101 + query_seq_headername = 101 + j + f.write(f">{query_seq_headername}\n{seq}\n") + + query_file = args.base.joinpath("query.fas") + with query_file.open("w") as f: + for j, seq in enumerate(overall_unique_seqs): + # The header of first sequence set as 101 + query_seq_headername = 101 + j + f.write(f">{query_seq_headername}\n{seq}\n") + + run_mmseqs( + args.mmseqs, + ["createdb", query_file, args.base.joinpath("qdb"), "--shuffle", "0", "--dbtype", "1"], + ) + with args.base.joinpath("qdb.lookup").open("w") as f: + id = 0 + file_number = 0 + for job_number, ( + raw_jobname, + query_sequences, + query_seqs_cardinality, + _ + ) in enumerate(queries_unique): + for seq in query_sequences: + raw_jobname_first = raw_jobname.split()[0] + f.write(f"{id}\t{raw_jobname_first}\t{file_number}\n") + id += 1 + file_number += 1 + shutil.copy(args.base.joinpath("qdb.lookup"), args.base.joinpath("org-qdb.lookup")) + #print("DOne") + + #exit() + mmseqs_search_monomer( + mmseqs=args.mmseqs, + dbbase=args.dbbase, + base=args.base, + uniref_db=args.db1, + template_db=args.db2, + metagenomic_db=args.db3, + use_env=args.use_env, + use_templates=args.use_templates, + filter=args.filter, + expand_eval=args.expand_eval, + align_eval=args.align_eval, + diff=args.diff, + qsc=args.qsc, + max_accept=args.max_accept, + prefilter_mode=args.prefilter_mode, + s=args.s, + db_load_mode=args.db_load_mode, + threads=args.threads, + gpu=args.gpu, + gpu_server=args.gpu_server, + unpack=args.unpack, + ) + ## + print(seq_map) + + for seq_id in range(len(overall_unique_seqs)): + a3m_content = open(args.base.joinpath(f"{seq_id}.a3m"), "r").readlines() + shutil.copy(args.base.joinpath(f"{seq_id}.a3m"), args.base.joinpath(f"u-{seq_id}.a3m")) + seq_itr = 0 + header = a3m_content[0] + for seqs in seq_map: + for j, seq_index in enumerate(seqs): + if seq_index == seq_id: + new_header = f">{101 + j}\n" + with open(args.base.joinpath(f"{seq_itr}.a3m"), "w") as out_f: + for line in a3m_content: + out_f.write(line.replace(header, new_header)) + seq_itr += 1 + + + + for seq_id in range(len(overall_unique_seqs)): + os.remove(args.base.joinpath(f"u-{seq_id}.a3m")) + #exit() + ## finish monomors and keep going for hybrid batch + ## + if is_complex is True: + mmseqs_search_pair( + mmseqs=args.mmseqs, + dbbase=args.dbbase, + base=args.base, + uniref_db=args.db1, + prefilter_mode=args.prefilter_mode, + s=args.s, + db_load_mode=args.db_load_mode, + threads=args.threads, + gpu=args.gpu, + gpu_server=args.gpu_server, + pairing_strategy=args.pairing_strategy, + pair_env=False, + unpack=args.unpack, + seq_map=seq_map + ) + #exit() + if args.use_env_pairing: + mmseqs_search_pair( + mmseqs=args.mmseqs, + dbbase=args.dbbase, + base=args.base, + uniref_db=args.db1, + spire_db=args.db4, + prefilter_mode=args.prefilter_mode, + s=args.s, + db_load_mode=args.db_load_mode, + threads=args.threads, + gpu=args.gpu, + gpu_server=args.gpu_server, + pairing_strategy=args.pairing_strategy, + pair_env=True, + unpack=args.unpack, + ) + if args.unpack or args.af3_json: + id = 0 + for job_number, ( + raw_jobname, + query_sequences, + query_seqs_cardinality, + other_molecules, + ) in enumerate(queries_unique): + unpaired_msa = [] + paired_msa = None + if len(query_seqs_cardinality) > 1: + paired_msa = [] + for seq in query_sequences: + with args.base.joinpath(f"{id}.a3m").open("r") as f: + unpaired_msa.append(f.read()) + if args.af3_json: + args.base.joinpath(f"{id}.a3m").unlink() + + if args.use_env_pairing: + with open(args.base.joinpath(f"{id}.paired.a3m"), 'a') as file_pair: + with open(args.base.joinpath(f"{id}.env.paired.a3m"), 'r') as file_pair_env: + while chunk := file_pair_env.read(10 * 1024 * 1024): + file_pair.write(chunk) + if args.unpack: + args.base.joinpath(f"{id}.env.paired.a3m").unlink() + + if len(query_seqs_cardinality) > 1: + with args.base.joinpath(f"{id}.paired.a3m").open("r") as f: + paired_msa.append(f.read()) + if args.unpack: + args.base.joinpath(f"{id}.paired.a3m").unlink() + id += 1 + + if args.af3_json: + af3 = AF3Utils(raw_jobname, query_sequences, query_seqs_cardinality, unpaired_msa, paired_msa, other_molecules) + with open(args.base.joinpath(f"{job_number}.json"), 'w') as f: + f.write(json.dumps(af3.content, indent=4)) + + if args.unpack: + msa = msa_to_str( + unpaired_msa, paired_msa, query_sequences, query_seqs_cardinality + ) + args.base.joinpath(f"{job_number}.a3m").write_text(msa) + + + #os.remove(args.base.joinpath("res_exp_realign-minimal.index")) + #os.remove(args.base.joinpath("res_exp_realign-minimal")) + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("res_exp_realign-minimal")]) + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb-minimal")]) + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb-minimal_h")]) + + + + else: + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("res")]) + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("prof_res")]) + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("prof_res_h")]) + os.remove(args.base.joinpath("original-query.fas")) + + if args.af3_json: + id = 0 + for job_number, (raw_jobname, query_sequences, query_seqs_cardinality, other_molecules) in enumerate(queries_unique): + unpaired_msa = [] + for seq in query_sequences: + with args.base.joinpath(f"{id}.a3m").open("r") as f: + unpaired_msa.append(f.read()) + id += 1 + + # Create AF3Utils object and write JSON + af3 = AF3Utils(raw_jobname, query_sequences, query_seqs_cardinality, unpaired_msa, None, other_molecules) + with open(args.base.joinpath(f"{job_number}.json"), 'w') as f: + f.write(json.dumps(af3.content, indent=4)) + if args.unpack: + # rename a3m files + rename_output(queries_unique, "a3m", args.base) + + # rename m8 files + if args.use_templates: + id = 0 + for raw_jobname, query_sequences, query_seqs_cardinality, _ in queries_unique: + with args.base.joinpath(f"{safe_filename(raw_jobname)}_{args.db2}.m8").open( + "w" + ) as f: + for _ in range(len(query_seqs_cardinality)): + with args.base.joinpath(f"{id}.m8").open("r") as g: + f.write(g.read()) + os.remove(args.base.joinpath(f"{id}.m8")) + id += 1 + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb")]) + run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb_h")]) + + if args.af3_json: + # rename json files + rename_output(queries_unique, "json", args.base) + + query_file.unlink() + os.remove(args.base.joinpath("org-qdb.lookup")) + + +if __name__ == "__main__": + main() \ No newline at end of file diff --git a/conf/gadi.config b/conf/gadi.config new file mode 100644 index 0000000..f90850f --- /dev/null +++ b/conf/gadi.config @@ -0,0 +1,68 @@ +/* +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + Nextflow config file for running minimal tests +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + Defines input files and everything required to run a fast and simple pipeline test. + + Use as follows: + nextflow run nf-core/wisps -profile test, --outdir + +---------------------------------------------------------------------------------------- +*/ +includeConfig 'https://raw.githubusercontent.com/nf-core/configs/master/conf/nci_gadi.config' + +singularity.cacheDir = "/g/data/if89/singularity_cache/" +singularity.autoMounts = true +singularity.enabled = true +if (params.use_gpu) { singularity.runOptions = '--nv' } + +params { + config_profile_name = 'Test profile' + config_profile_description = 'Minimal test dataset to check pipeline function' + + // Input data + outdir = "out-test" + input = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" + samplesheet2 = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" + + boltz_ccd = "/g/data/if89/proteinfold_dbs/boltz_dbs/ccd.pkl" + boltz_model = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz1_conf.ckpt" + colabfold_db = "/g/data/if89/proteinfold_dbs/colabfold_dbs/colabfold_envdb_202108/" + colabfold_db = "/g/data/if89/proteinfold_dbs/colabfold_dbs/colabfold_envdb_202108/" + + uniref30 = "/g/data/if89/proteinfold_dbs/colabfold_dbs/uniref30_2302/" + use_gpu = true + project = "ll61" + use_dgxa100 = false + +} + +process { + //executor = "local" + storage = "gdata/if89+scratch/${params.project}+gdata/${params.project}" + + withName: 'MMSEQS_COLABFOLDSEARCH' { + memory = 300.GB + time = 16.h + } + withName: 'RUN_BOLTZ' { + cpus = 12 + queue = "gpuvolta" + time = 10.h + memory = 24.GB + cpus = 12 + gpus = 1 + } + resourceLimits = [ + cpus: 1, + memory: '4.GB', + time: '1.h' + ] + resourceLimits = [ + cpus: 1000, + memory: '2000.GB', + time: '24.h' + ] + +} + diff --git a/conf/modules.config b/conf/modules.config index 255b138..c424f6d 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -9,7 +9,7 @@ ext.prefix = File name prefix for output files. ---------------------------------------------------------------------------------------- */ - +singularity.runOptions = params.mmseqs_gpu ? '--nv' : '' process { publishDir = [ @@ -18,7 +18,6 @@ process { saveAs: { filename -> filename.equals('versions.yml') ? null : filename } ] - withName: 'MULTIQC' { ext.args = { params.multiqc_title ? "--title \"$params.multiqc_title\"" : '' } publishDir = [ @@ -28,4 +27,29 @@ process { ] } + withName: 'MMSEQS_COLABFOLDSEARCH' { + memory = 300.GB + time = 16.h + def args = "" + if (params.mmseqs_gpu){ + args += "--gpu 1 " + } + + if ("${params.tools}".split(",").contains("alphafold3")){ + args += "--af3-json " + } + + ext.args = args + } + + withName: 'RUN_BOLTZ' { + cpus = 12 + time = 10.h + memory = 24.GB + ext.args = "--write_full_pae --output_format mmcif" + } + + withName: 'IPSAE' { + ext.args = "${params.ipsae_pae_cutoff} ${params.ipsae_dist_cutoff}" + } } diff --git a/conf/test_gadi.config b/conf/test_gadi.config index ca8ca36..4cb1c2b 100644 --- a/conf/test_gadi.config +++ b/conf/test_gadi.config @@ -9,8 +9,6 @@ ---------------------------------------------------------------------------------------- */ -includeConfig 'https://raw.githubusercontent.com/nf-core/configs/master/conf/nci_gadi.config' - singularity.cacheDir = "/g/data/if89/singularity_cache/" singularity.autoMounts = true singularity.enabled = true @@ -23,25 +21,38 @@ params { // Input data outdir = "out-test" input = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" - samplesheet2 = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" boltz_ccd = "/g/data/if89/proteinfold_dbs/boltz_dbs/ccd.pkl" boltz_model = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz1_conf.ckpt" + boltz2_aff = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz2_aff.ckpt" + boltz2_conf = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz2_conf.ckpt" + boltz2_mols = "/g/data/if89/proteinfold_dbs/boltz_dbs/mols" colabfold_db = "/g/data/if89/proteinfold_dbs/miniature_databases/colabfold_envdb_202108/" - uniref30 = "/g/data/if89/proteinfold_dbs/miniature_databases/uniref30_2302/" + uniref30 = "/g/data/za08/tom/colabfold_uniref30" + colabfold_alphafold2_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params/alphafold_params_colab_2022-12-06/" + + alphafold3_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" + alphafold3_small_bfd = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" + alphafold3_mgnify = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" + alphafold3_pdb_mmcif = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" + alphafold3_uniref90 = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" + alphafold3_pdb_seqres = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" + alphafold3_uniprot = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" + use_gpu = true project = "ll61" use_dgxa100 = false } process { + executor = "pbspro" //executor = "local" - storage = "gdata/if89+scratch/${params.project}+gdata/${params.project}" - - withName: 'MMSEQS_COLABFOLDSEARCH' { - memory = 300.GB - time = 16.h - } + storage = "gdata/za08+gdata/if89+scratch/${params.project}+gdata/${params.project}" + module = 'singularity' + cache = 'lenient' + stageInMode = 'symlink' + queue = { task.memory < 128.GB ? 'normalbw' : (task.memory >= 128.GB && task.memory <= 190.GB ? 'normal' : (task.memory > 190.GB && task.memory <= 1020.GB ? 'hugemembw' : '')) } + withName: 'RUN_BOLTZ' { cpus = 12 queue = "gpuvolta" @@ -50,6 +61,24 @@ process { cpus = 12 gpus = 1 } + withName: 'MMSEQS_COLABFOLDSEARCH' { + time = 1.h + if (params.mmseqs_gpu){ + queue = "dgxa100" + memory = 24.GB + cpus = 16 + gpus = 1 + } + } + + withName: 'COLABFOLD_BATCH' { + queue = "gpuvolta" + time = 10.h + memory = 64.GB + cpus = 12 + gpus = 1 + } + resourceLimits = [ cpus: 1, memory: '4.GB', @@ -60,6 +89,11 @@ process { memory: '2000.GB', time: '24.h' ] + resourceLimits = [ + cpus: 16, + memory: '24.GB', + time: '3.h' + ] } diff --git a/main.nf b/main.nf index a1c8c4c..c4301d2 100644 --- a/main.nf +++ b/main.nf @@ -41,15 +41,32 @@ workflow NFCORE_WISPS { // // WORKFLOW: Run pipeline // + + WISPS ( ch_samplesheet, params.mode, ch_versions, - params.boltz_ccd, - params.boltz_model, - params.colabfold_db, - params.uniref30, - params.mmseq_batch_size + Channel.fromPath(params.boltz_ccd, checkIfExists: true).first(), + Channel.fromPath(params.boltz_model, checkIfExists: true).first(), + Channel.fromPath(params.boltz2_aff, checkIfExists: true).first(), + Channel.fromPath(params.boltz2_conf, checkIfExists: true).first(), + Channel.fromPath(params.boltz2_mols, checkIfExists: true).first(), + Channel.fromPath(params.colabfold_db, checkIfExists: true).first(), + Channel.fromPath(params.uniref30, checkIfExists: true).first(), + params.mmseqs_batch_size, + params.colabfold_model_preset, + Channel.fromPath(params.colabfold_alphafold2_params, checkIfExists: true).first(), + params.colabfold_num_recycles, + Channel.fromPath(params.alphafold3_params, checkIfExists: true).first(), + Channel.fromPath(params.alphafold3_small_bfd, checkIfExists: true).first(), + Channel.fromPath(params.alphafold3_mgnify, checkIfExists: true).first(), + Channel.fromPath(params.alphafold3_pdb_mmcif, checkIfExists: true).first(), + Channel.fromPath(params.alphafold3_uniref90, checkIfExists: true).first(), + Channel.fromPath(params.alphafold3_pdb_seqres, checkIfExists: true).first(), + Channel.fromPath(params.alphafold3_uniprot, checkIfExists: true).first(), + params.tools + ) ch_versions = ch_versions.mix(WISPS.out.versions) diff --git a/modules/local/colabfold_batch/Dockerfile b/modules/local/colabfold_batch/Dockerfile new file mode 100644 index 0000000..2437848 --- /dev/null +++ b/modules/local/colabfold_batch/Dockerfile @@ -0,0 +1,5 @@ +FROM ghcr.io/sokrypton/colabfold:1.5.5-cuda12.2.2 + +RUN mamba install -y -n colabfold -c conda-forge -c bioconda mmseqs2=18.8cc5c && \ + mamba clean -afy && \ + mmseqs version diff --git a/modules/local/colabfold_batch/main.nf b/modules/local/colabfold_batch/main.nf new file mode 100644 index 0000000..bbd5d13 --- /dev/null +++ b/modules/local/colabfold_batch/main.nf @@ -0,0 +1,81 @@ +process COLABFOLD_BATCH { + tag "$meta.id" + label 'process_medium' + label 'process_gpu' + + container "nf-core/proteinfold_colabfold:dev" + + input: + tuple val(meta), path(fasta) + val colabfold_model_preset + path ('params/*') + path ('colabfold_db/*') + path ('uniref30/*') + val numRec + + output: + tuple val(meta), path ("${meta.id}_colabfold.pdb"), emit: top_ranked_pdb + tuple val(meta), path ("*relaxed_rank_*.pdb") , emit: pdb + tuple val(meta), path ("*_coverage.png") , emit: msa + tuple val(meta), path ("*_mqc.png") , emit: multiqc + tuple val(meta), path ("${meta.id}_0_pae.tsv") , emit: pae + tuple val(meta), path ("${meta.id}_scores_rank_001_*.json") , emit: top_ranked_scores + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + // Exit if running this module with -profile conda / -profile mamba + if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) { + error("Local COLABFOLD_BATCH module does not support Conda. Please use Docker / Singularity / Podman instead.") + } + def args = task.ext.args ?: '' + + """ + ln -s \$(realpath params/alphafold_params_*/*) params/ + touch params/download_finished.txt + + colabfold_batch \\ + $args \\ + --num-recycle ${numRec} \\ + --data \$PWD \\ + --model-type ${colabfold_model_preset} \\ + ${fasta} \\ + \$PWD + for i in `find *.png -maxdepth 0`; do cp \$i \${i%'.png'}_mqc.png; done + if [ ! -e `find *_relaxed_rank_001_*.pdb` ]; then + cp *_relaxed_rank_001*.pdb ${meta.id}_colabfold.pdb + else + cp *_unrelaxed_rank_001*.pdb ${meta.id}_colabfold.pdb + fi + + #Note: only multimer prefix is meta.id + extract_metrics.py --name ${meta.id} \\ + --colabfold_pae *_predicted_aligned_error_v1.json + + mv *_coverage.png ${meta.id}_seq_coverage.png + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + colabfold_batch: \$(conda run -n colabfold pip list | grep "^colabfold" | awk '{print \$2}') + END_VERSIONS + """ + + stub: + """ + touch ./"${meta.id}"_colabfold.pdb + touch ./"${meta.id}"_mqc.png + touch ./${meta.id}_relaxed_rank_01.pdb + touch ./${meta.id}_relaxed_rank_02.pdb + touch ./${meta.id}_relaxed_rank_03.pdb + touch ./${meta.id}_coverage.png + touch ./${meta.id}_scores_rank.json + touch ./${meta.id}_0_pae.tsv + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + colabfold_batch: \$(conda run -n colabfold pip list | grep "^colabfold" | awk '{print \$2}') + END_VERSIONS + """ +} diff --git a/modules/local/data_convertor/boltz_fasta/main.nf b/modules/local/data_convertor/boltz_fasta/main.nf new file mode 100644 index 0000000..200125a --- /dev/null +++ b/modules/local/data_convertor/boltz_fasta/main.nf @@ -0,0 +1,129 @@ +process BOLTZ_FASTA { + tag "$meta.id" + label 'process_single' + + conda "${moduleDir}/environment.yml" + container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? + 'https://depot.galaxyproject.org/singularity/python:3.8.3' : + 'quay.io/biocontainers/python:3.8.3' }" + + input: + tuple val(meta), path(fasta), path(msa) + + output: + tuple val(meta), path ("output_fasta/*.fasta"), path(msa), emit: formatted_fasta + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + def msa_files = msa ? "\"" + msa.join('", "') + "\"" : "" + """ + #!/usr/bin/env python3 + import os, sys + import string + import re + #def safe_filename(file: str) -> str: + # return "".join([c if c.isalnum() or c in ["_", ".", "-"] else "_" for c in file]) + ".a3m" + + all_combinations = list(string.ascii_uppercase) + list(string.ascii_lowercase) + [str(x) for x in range(0, 10)] + msa_files = [${msa_files}] + ENTITY_TYPES = ["protein", "ccd", "smiles", "dna", "rna"] + + def infer_entity_type(header, sequence): + header_lower = header.lower() + for entity in ENTITY_TYPES: + if entity in header_lower: + return entity + seq = sequence.strip() + seq_set = set(seq) + # RNA: only A,C,U,G,N + if len(seq_set - set("ACUGN")) == 0: + return "rna" + # DNA: only A,C,T,G,N + if len(seq_set - set("ACTGN")) == 0: + return "dna" + # Protein: only 20 AA, not just A,C,T,G,U,N + protein_letters = set("ACDEFGHIKLMNPQRSTVWY") + if len(seq_set - protein_letters) == 0 and not (seq_set <= set("ACUGTN")): + return "protein" + # SMILES: fallback + if re.fullmatch(r"[A-Za-z0-9@+\\-\\[\\]\\(\\)=#\\\$%]+", seq): + return "smiles" + return "unknown" + + os.makedirs("output_fasta", exist_ok=True) + counter = 0 + msa_counter = 0 + with open("${fasta}", "r") as f: + lines = f.readlines() + + msa = "" + fasta_data = "" + seq_lines = [] + header = None + + unique_proteins = {} + for line in lines: + line = line.strip() + if line.startswith(">"): + # Write previous entry if exists + if header is not None: + sequence = "".join(seq_lines) + entity_type = infer_entity_type(header, sequence) + msa = "" + if entity_type == 'protein': + if len(msa_files) > 0: + if not sequence in unique_proteins: + unique_proteins[sequence] = msa_counter + msa_counter += 1 + this_msa = unique_proteins[sequence] + msa = f"|{os.path.basename(msa_files[this_msa])}" + if msa[1:] not in msa_files: + print(f"Can not find msa file {os.path.basename(msa_files[counter])}") + exit(1) + fasta_data += f">{all_combinations[counter]}|{entity_type}{msa}\\n{sequence}\\n" + counter += 1 + header = line + seq_lines = [] + else: + seq_lines.append(line) + # Write last entry + if header is not None: + sequence = "".join(seq_lines) + entity_type = infer_entity_type(header, sequence) + msa = "" + if entity_type == 'protein': + if len(msa_files) > 0: + if not sequence in unique_proteins: + unique_proteins[sequence] = msa_counter + msa_counter += 1 + this_msa = unique_proteins[sequence] + msa = f"|{os.path.basename(msa_files[this_msa])}" + if msa[1:] not in msa_files: + print(f"Can not find msa file {os.path.basename(msa_files[counter])}") + exit(1) + fasta_data += f">{all_combinations[counter]}|{entity_type}{msa}\\n{sequence}\\n" + + if len(fasta_data) > 0: + with open(f"output_fasta/${meta.id}.fasta", "w") as outfile: + outfile.write(fasta_data) + + with open ("versions.yml", "w") as version_file: + version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) + ${args} + """ + + stub: + """ + mkdir output_fasta + touch "output_fasta/${meta.id}.fasta" + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + END_VERSIONS + """ +} diff --git a/modules/local/data_convertor/fasta2json/main.nf b/modules/local/data_convertor/fasta2json/main.nf new file mode 100644 index 0000000..4b5c507 --- /dev/null +++ b/modules/local/data_convertor/fasta2json/main.nf @@ -0,0 +1,74 @@ +process FASTA2JSON { + tag "$meta.id" + label 'process_single' + + conda "${moduleDir}/environment.yml" + container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? + 'https://depot.galaxyproject.org/singularity/python:3.8.3' : + 'quay.io/biocontainers/python:3.8.3' }" + + input: + tuple val(meta), path(fasta) + output: + tuple val(meta), path ("*.json"), emit: json + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + + """ + #!/usr/bin/env python3 + import os, sys + import json + import copy + seq_template = { + "type": "", + "sequence": "", + "count": 1 + } + final_res = {"entities": []} + seq_type = "protein" + counter = 0 + fasta_data = "" + + with open("${fasta}", "r") as f: + lines = f.readlines() + + for line in lines: + line = line.strip() + if line.startswith(">"): + if len(fasta_data) > 0: + new_entry = copy.deepcopy(seq_template) + new_entry["type"] = seq_type + new_entry["sequence"] = fasta_data + final_res["entities"].append(new_entry) + counter += 1 + fasta_data = "" + else: + fasta_data += f"{line}" + if len(fasta_data) > 0: + new_entry = copy.deepcopy(seq_template) + new_entry["type"] = seq_type + new_entry["sequence"] = fasta_data + final_res["entities"].append(new_entry) + + with open("${meta.id}.json", "w") as json_file: + json.dump(final_res, json_file, indent=4, sort_keys=True) + + with open ("versions.yml", "w") as version_file: + version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) + """ + + stub: + """ + touch "${meta.id}.json" + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + END_VERSIONS + """ +} diff --git a/modules/local/data_convertor/fasta2yaml/main.nf b/modules/local/data_convertor/fasta2yaml/main.nf new file mode 100644 index 0000000..5c4dccc --- /dev/null +++ b/modules/local/data_convertor/fasta2yaml/main.nf @@ -0,0 +1,72 @@ +process FASTA2YAML { + tag "$meta.id" + label 'process_single' + + conda "${moduleDir}/environment.yml" + container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? + 'https://depot.galaxyproject.org/singularity/python:3.8.3' : + 'quay.io/biocontainers/python:3.8.3' }" + + input: + tuple val(meta), path(fasta) + + output: + tuple val(meta), path ("*.yaml"), emit: yaml + tuple val(meta), path ("out_fasta/*.fasta"), emit: fasta + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + + """ + #!/usr/bin/env python3 + import os, sys + import string + yaml_template = "defaults:\\n - base\\njob_name: \\"${meta.id}\\"\\nprotein_inputs:\\n" + seq_type = "protein" + counter = 0 + fasta_data = "" + os.makedirs("out_fasta", exist_ok=True) + all_combinations = list(string.ascii_uppercase) + list(string.ascii_lowercase) + [str(x) for x in range(0, 10)] + with open("${fasta}", "r") as f: + lines = f.readlines() + + for line in lines: + line = line.strip() + if line.startswith(">"): + if len(fasta_data) > 0: + with open(f"out_fasta/{all_combinations[counter]}.fasta", "w") as fasta_file: + fasta_file.write(fasta_data + "\\n") + yaml_template += f" {all_combinations[counter]}:\\n fasta_file: {all_combinations[counter]}.fasta\\n" + counter += 1 + fasta_data = f"{line}\\n" + else: + fasta_data += f"{line}" + if len(fasta_data) > 0: + with open(f"out_fasta/{all_combinations[counter]}.fasta", "w") as fasta_file: + fasta_file.write(fasta_data + "\\n") + yaml_template += f" {all_combinations[counter]}:\\n fasta_file: {all_combinations[counter]}.fasta\\n" + + with open("${meta.id}.yaml", "w") as yaml_file: + yaml_file.write(yaml_template) + + with open ("versions.yml", "w") as version_file: + version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) + """ + + stub: + """ + touch "${meta.id}.yaml" + mkdir out_fasta + touch "out_fasta/A.fasta" + touch "out_fasta/B.fasta" + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + END_VERSIONS + """ +} diff --git a/modules/local/ipsae/main.nf b/modules/local/ipsae/main.nf new file mode 100644 index 0000000..72f3eeb --- /dev/null +++ b/modules/local/ipsae/main.nf @@ -0,0 +1,46 @@ +process IPSAE { + tag "$meta.id" + label 'process_single' + + conda "${moduleDir}/environment.yml" + container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? + 'https://depot.galaxyproject.org/singularity/numpy:2.2.2' : + 'quay.io/biocontainers/numpy:2.2.2' }" + + input: + tuple val(meta), path(pae), path(pdb) + output: + tuple val(meta), path ("*.pml"), emit: pml + tuple val(meta), path ("*_byres.txt"), emit: byres + tuple val(meta), path ("*.txt"), emit: txt + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + + """ + ipsae.py ${pae} \\ + ${pdb} \\ + ${args} + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + END_VERSIONS + """ + + stub: + """ + touch "${meta.id}.pml" + touch "${meta.id}.txt" + touch "${meta.id}.byres.txt" + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + END_VERSIONS + """ +} diff --git a/modules/local/mmseqs_colabfoldsearch/main.nf b/modules/local/mmseqs_colabfoldsearch/main.nf index a3e53ea..232f42a 100644 --- a/modules/local/mmseqs_colabfoldsearch/main.nf +++ b/modules/local/mmseqs_colabfoldsearch/main.nf @@ -2,7 +2,7 @@ process MMSEQS_COLABFOLDSEARCH { tag "$meta.id" label 'process_high_memory' - container "nf-core/proteinfold_colabfold:dev" + container "/g/data/ll61/colabfold_search-gpu.sif" input: tuple val(meta), path(fasta) @@ -11,6 +11,7 @@ process MMSEQS_COLABFOLDSEARCH { output: tuple val(meta), path("**.a3m"), emit: a3m + tuple val(meta), path("**.json"), emit: json, optional: true path "versions.yml", emit: versions when: @@ -24,9 +25,11 @@ process MMSEQS_COLABFOLDSEARCH { def args = task.ext.args ?: '' """ - colabfold_search \\ + mamba run --name colab colabfold_search \\ $args \\ - --threads $task.cpus ${fasta} \\ + --threads $task.cpus \\ + --use-env 0 --db1 colabfold_uniref30/uniref30_2302_db --db3 colabfold_envdb_202108/colabfold_envdb_202108_db \\ + ${fasta} \\ ./db \\ "result/" @@ -34,7 +37,7 @@ process MMSEQS_COLABFOLDSEARCH { "${task.process}": colabfold_search: \$(conda run -n colabfold pip list | grep "^colabfold" | awk '{print \$2}') alphafold_colabfold: \$(conda run -n colabfold pip list | grep "^alphafold-colabfold" | awk '{print \$2}') - mmseqs: \$(mmseqs version) + mmseqs: \$(mamba run --name colab mmseqs version) END_VERSIONS """ diff --git a/modules/local/msa_manager/split_msa.nf b/modules/local/msa_manager/split_msa.nf new file mode 100644 index 0000000..c7f7b4d --- /dev/null +++ b/modules/local/msa_manager/split_msa.nf @@ -0,0 +1,42 @@ +process SPLIT_MSA { + tag "$meta.id" + label 'process_single' + + conda "${moduleDir}/environment.yml" + container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? + 'https://depot.galaxyproject.org/singularity/python:3.8.3' : + 'quay.io/biocontainers/python:3.8.3' }" + + input: + tuple val(meta), path(msa) + output: + tuple val(meta), path ("output_msa/*.csv"), emit: msa_csv + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + + """ + msa_manager.py ${msa} -o output_msa --meta_id ${meta.id} + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + END_VERSIONS + """ + + stub: + """ + mkdir output_msa + touch "output_msa/A.csv" + touch "output_msa/B.csv" + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + END_VERSIONS + """ +} diff --git a/modules/local/prepare_interactions.nf b/modules/local/prepare_interactions.nf index 2eb0a49..b26693e 100644 --- a/modules/local/prepare_interactions.nf +++ b/modules/local/prepare_interactions.nf @@ -53,6 +53,7 @@ process PREPARE_INTERACTIONS { continue # Skip empty FASTA files #header = lines[0].strip() + lines[-1] = lines[-1].strip() + "\\n" body = lines[1:] header = f">{all_combinations[counter]}|{seq_type}" counter += 1 diff --git a/modules/local/run_alphafold3/Dockerfile b/modules/local/run_alphafold3/Dockerfile new file mode 100644 index 0000000..1a541f2 --- /dev/null +++ b/modules/local/run_alphafold3/Dockerfile @@ -0,0 +1,59 @@ +FROM nvidia/cuda:12.6.0-base-ubuntu22.04 + +LABEL authors="Jose Espinosa-Carrasco" \ + title="nfcore/proteinfold_alphafold3" \ + Version="1.2.0dev" \ + description="Docker image containing all software requirements to run Alphafold3 using the nf-core/proteinfold pipeline" + +# Some RUN statements are combined together to make Docker build run faster. +# Get latest package listing, install software-properties-common, git and wget. +# git is required for pyproject.toml toolchain's use of CMakeLists.txt. +RUN apt update --quiet \ + && apt install --yes --quiet software-properties-common \ + && apt install --yes --quiet git wget jq \ + && rm -rf /var/lib/apt/lists/* + +# Get apt repository of specific Python versions. Then install Python. Tell APT +# this isn't an interactive TTY to avoid timezone prompt when installing. +RUN add-apt-repository ppa:deadsnakes/ppa \ + && DEBIAN_FRONTEND=noninteractive apt install --yes --quiet python3.11 python3-pip python3.11-venv python3.11-dev +RUN python3.11 -m venv /alphafold3_venv +ENV PATH="/hmmer/bin:/alphafold3_venv/bin:$PATH" + +# Install HMMER. Do so before copying the source code, so that docker can cache +# the image layer containing HMMER. +RUN mkdir /hmmer_build /hmmer ; \ + wget http://eddylab.org/software/hmmer/hmmer-3.4.tar.gz --directory-prefix /hmmer_build ; \ + (cd /hmmer_build && tar zxf hmmer-3.4.tar.gz && rm hmmer-3.4.tar.gz) ; \ + (cd /hmmer_build/hmmer-3.4 && ./configure --prefix /hmmer) ; \ + (cd /hmmer_build/hmmer-3.4 && make -j8) ; \ + (cd /hmmer_build/hmmer-3.4 && make install) ; \ + (cd /hmmer_build/hmmer-3.4/easel && make install) ; \ + rm -R /hmmer_build + +# Clone AlphaFold3 +RUN git clone https://github.com/google-deepmind/alphafold3.git /app/alphafold && \ + cd /app/alphafold && \ + git checkout 3c27a149a25b6c8930ce68cfeb2a6cbb9afb3359 && \ + cd - + +# # Install the Python dependencies AlphaFold 3 needs. +# RUN pip3 install -r dev-requirements.txt +# RUN pip3 install --no-deps . + +# Install pip packages. +RUN pip3 install --upgrade pip --no-cache-dir \ + && pip3 install -r /app/alphafold/dev-requirements.txt --no-cache-dir \ + && pip3 install --no-deps /app/alphafold/ --no-cache-dir \ + && pip3 install --no-deps biopython + +# # Build chemical components database (this binary was installed by pip). +RUN build_data + +# To work around a known XLA issue causing the compilation time to greatly +# increase, the following environment variable setting XLA flags must be enabled +# when running AlphaFold 3: +ENV XLA_FLAGS="--xla_gpu_enable_triton_gemm=false" +# Memory settings used for folding up to 5,120 tokens on A100 80 GB. +ENV XLA_PYTHON_CLIENT_PREALLOCATE=true +ENV XLA_CLIENT_MEM_FRACTION=0.95 diff --git a/modules/local/run_alphafold3/main.nf b/modules/local/run_alphafold3/main.nf new file mode 100644 index 0000000..556980e --- /dev/null +++ b/modules/local/run_alphafold3/main.nf @@ -0,0 +1,95 @@ +/* + * Run Alphafold3 + */ +process RUN_ALPHAFOLD3 { + tag "$meta.id" + label 'process_medium' + label 'process_gpu' + container "nf-core/proteinfold_alphafold3_standard:1.2.0dev" + input: + tuple val(meta), path(json) + path "params/*" + path "small_bfd/*" + path "mgnify/*" + path "mmcif_files" + path "uniref90/*" + path "pdb_seqres/*" + path "uniprot/*" + output: + tuple val(meta), path ("publish/*alphafold3.cif") , emit: top_ranked_cif + tuple val(meta), path ("publish/*ranked_*.cif") , emit: cif + tuple val(meta), path ("${meta.id}_plddt.tsv") , emit: multiqc + tuple val(meta), path ("${meta.id}_alphafold3_msa.tsv") , emit: msa + tuple val(meta), path ("${meta.id}_0_pae.tsv") , emit: pae + tuple val(meta), path ("*_full_data_0.json") , emit: raw_pae + path "versions.yml" , emit: versions + when: + task.ext.when == null || task.ext.when + script: + // Exit if running this module with -profile conda / -profile mamba + if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) { + error("Local RUN_ALPHAFOLD3 module does not support Conda. Please use Docker / Singularity / Podman instead.") + } + def args = task.ext.args ?: '' + def prefix = task.ext.prefix ?: "${meta.id}" + def af3_id = meta.id.toLowerCase() + """ + if [ -f pdb_seqres/pdb_seqres.txt ] + then + sed -i "/^\\w*0/d" pdb_seqres/pdb_seqres.txt + fi + python3 /app/alphafold/run_alphafold.py \\ + --json_path=${json} \\ + --model_dir=./params \\ + --uniref90_database_path=./uniref90/uniref90_2022_05.fa \\ + --mgnify_database_path=./mgnify/mgy_clusters_2022_05.fa \\ + --pdb_database_path=./mmcif_files \\ + --small_bfd_database_path=./small_bfd/bfd-first_non_consensus_sequences.fasta \\ + --uniprot_cluster_annot_database_path=./uniprot/uniprot_all_2021_04.fa \\ + --seqres_database_path=./pdb_seqres/pdb_seqres_2022_09_28.fasta \\ + --output_dir=\$PWD \\ + $args + ## Rename the top ranked model + if [ ! -d publish ]; then + mkdir -p publish + fi + ## Move the rest of the models and rename them according to their rank + name=\$(jq -r '.name' ${json}) + cp -n "\${name}/\${name}_model.cif" "publish/${prefix}_alphafold3.cif" + # Sort the rows by ranking_score in descending order + sorted_csv=\$(head -n 1 "\${name}/ranking_scores.csv"; tail -n +2 "\${name}/ranking_scores.csv" | sort -t, -k3 -nr) + rank=0 + touch publish/combined_plddt_mqc.tsv + # Generate files with rank tag + echo "\$sorted_csv" | tail -n +2 | while IFS=',' read -r seed sample ranking_score; do + cp -n "\${name}/seed-\${seed}_sample-\${sample}/model.cif" "publish/seed_\${seed}_sample_\${sample}_ranked_\${rank}.cif" + rank=\$((rank + 1)) + done + extract_metrics.py --name ${prefix} \\ + --jsons ${af3_id}/${af3_id}_data.json ${af3_id}/${af3_id}_summary_confidences.json ${af3_id}/${af3_id}_confidences.json \\ + --structs publish/*ranked_*.cif + mv "${prefix}_msa.tsv" "${meta.id}_alphafold3_msa.tsv" + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + END_VERSIONS + """ + stub: + def prefix = task.ext.prefix ?: "${meta.id}" + """ + mkdir publish + touch publish/${prefix}_alphafold3.cif + touch publish/${prefix}_ranked_1.cif + touch publish/${prefix}_ranked_2.cif + touch publish/${prefix}_ranked_3.cif + touch publish/${prefix}_ranked_4.cif + touch publish/${prefix}_ranked_5.cif + touch ${prefix}_plddt.tsv + touch ${prefix}_alphafold3_msa.tsv + touch ${prefix}_0_pae.tsv + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + END_VERSIONS + """ +} diff --git a/modules/local/run_boltz/Dockerfile b/modules/local/run_boltz/Dockerfile new file mode 100644 index 0000000..0ef3a4f --- /dev/null +++ b/modules/local/run_boltz/Dockerfile @@ -0,0 +1,25 @@ +FROM python:3.12-slim + +LABEL authors="Ziad Al-Bkhetan " \ + title="nfcore/proteinfold_boltz" \ + Version="1.2.0dev" \ + description="Docker image containing all software requirements to run boltz using the nf-core/proteinfold pipeline" + +RUN apt-get update && \ + apt-get install -y --no-install-recommends \ + build-essential \ + procps \ + && apt-get autoremove -y \ + && rm -rf /var/lib/apt/lists/* + +RUN pip install --no-cache-dir boltz==2.0.3 + +## To update to version 2.2.0, uncomment the following lines, though still was complaining +## about triton version, thought the error msg state to be sure of using 3.3.0 +# RUN pip install --no-cache-dir \ +# cuequivariance_ops_cu12==0.5.1\ +# cuequivariance_ops_torch_cu12==0.5.1 \ +# cuequivariance_torch==0.5.1 \ +# triton==3.3.0 + +CMD ["boltz"] diff --git a/modules/local/run_boltz/main.nf b/modules/local/run_boltz/main.nf index b513437..581bbbc 100644 --- a/modules/local/run_boltz/main.nf +++ b/modules/local/run_boltz/main.nf @@ -4,46 +4,113 @@ process RUN_BOLTZ { tag "$meta.id" label 'process_medium' + label 'process_gpu' + + container "nf-core/proteinfold_boltz:dev" - container "fastfold/boltz-1:latest" - input: tuple val(meta), path(fasta) path (files) path ('boltz1_conf.ckpt') path ('ccd.pkl') - + path ('boltz2_aff.ckpt') + path ('boltz2_conf.ckpt') + path ('mols') + output: - tuple val(meta), path ("boltz_results_*/processed/msa/*.npz"), emit: msa - tuple val(meta), path ("boltz_results_*/processed/structures/*.npz"), emit: structures - tuple val(meta), path ("boltz_results_*/predictions/*/confidence*.json"), emit: confidence - tuple val(meta), path ("*"), emit: plddt - tuple val(meta), path ("boltz_results_*/predictions/*/*.pdb"), emit: pdb + // TODO: rename npz into different emit channels as to not conflict with raw (.tsv) PAE etc. As in PR #306 + tuple val(meta), path ("boltz_results_*/processed/msa/*.npz") , optional: true, emit: msa + tuple val(meta), path ("boltz_results_*/processed/structures/*.npz") , emit: structures + tuple val(meta), path ("boltz_results_*/predictions/*/confidence*.json") , emit: confidence + tuple val(meta), path ("${meta.id}_plddt.tsv") , optional: true, emit: multiqc + // TODO: support cif as well like with HelixFold3 + tuple val(meta), path ("${meta.id}_boltz.pdb") , optional: true, emit: top_ranked_pdb + tuple val(meta), path ("boltz_results_*/predictions/*/*.pdb") , optional: true, emit: pdb + tuple val(meta), path ("boltz_results_*/predictions/*/*model_0.cif") , optional: true, emit: cif + tuple val(meta), path ("boltz_results_*/predictions/*/plddt_*model_0.npz") , emit: plddt + tuple val(meta), path ("boltz_results_*/predictions/*/pae_*model_0.npz") , optional: true, emit: pae + tuple val(meta), path ("${meta.id}_plddt.tsv") , optional: true, emit: plddt_raw + tuple val(meta), path ("${meta.id}_boltz_msa.tsv") , optional: true, emit: msa_raw + tuple val(meta), path ("${meta.id}_*_pae.tsv") , optional: true, emit: pae_raw + tuple val(meta), path ("${meta.id}_ptm.tsv") , optional: true, emit: ptm_raw + tuple val(meta), path ("${meta.id}_iptm.tsv") , optional: true, emit: iptm_raw + tuple val(meta), path ("${meta.id}_chainwise_ptm.tsv") , optional: true, emit: summary_chainwise_ptm_raw + tuple val(meta), path ("${meta.id}_chainwise_iptm.tsv") , optional: true, emit: chainwise_iptm_raw + + path "versions.yml", emit: versions when: task.ext.when == null || task.ext.when - + script: + // Exit if running this module with -profile conda / -profile mamba + + // TODO: "boltz_results_*" dir should be be further specified using --out_dir when running Boltz, and being able to go "boltz_results_${meta.id}" instead of "boltz_results_*" + // TODO: MSA processing for Boltz is not solid yet. They can come from webserver, local mmseq, or a custom paired .csv (see docs below) + // https://github.com/jwohlwend/boltz/blob/main/docs/prediction.md#yaml-format + // TODO: what I really need to do is add a function to read /processed/msa/*.npz and convert it to a .tsv file + + // TODO: Boltz is the example to do chain-wise summary files. This will be better if model_id was properly written per prog and EXTRACT_METRICs was a process + if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) { + error("Local RUN_BOLTZ module does not support Conda. Please use Docker / Singularity / Podman instead.") + } + def version = "2.0.3" def args = task.ext.args ?: '' """ - boltz predict --output_format pdb ${args} "${fasta}" --cache ./ + export NUMBA_CACHE_DIR=/tmp + export HOME=/tmp + + boltz predict "${fasta}" ${args} --cache ./ + + if [[ "${args}" == *pdb* ]]; then + cp boltz_results_*/predictions/${meta.id}/*_0.pdb ./${meta.id}_boltz.pdb + if [ -f boltz_results_*/msa/${meta.id}_0.csv ]; then + cp boltz_results_*/msa/${meta.id}_*.csv ./ + fi + + extract_metrics.py --name ${meta.id} \\ + --structs boltz_results_*/predictions/${meta.id}/*.pdb \\ + --jsons boltz_results_*/predictions/${meta.id}/confidence_*_model_*.json \\ + --npzs boltz_results_*/predictions/${meta.id}/pae_*_model_*.npz \\ + --csvs ${meta.id}_*.csv + + mv "${meta.id}_msa.tsv" "${meta.id}_boltz_msa.tsv" + fi + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + boltz: $version + END_VERSIONS """ + stub: + def version = "2.0.3" """ mkdir -p boltz_results_${meta.id}/processed/msa/ mkdir -p boltz_results_${meta.id}/processed/structures/ mkdir -p boltz_results_${meta.id}/predictions/${meta.id}/ - + touch boltz_results_${meta.id}/processed/msa/${meta.id}.npz touch boltz_results_${meta.id}/processed/structures/${meta.id}.npz touch boltz_results_${meta.id}/predictions/${meta.id}/confidence_${meta.id}.json touch boltz_results_${meta.id}/predictions/${meta.id}/${meta.id}.pdb - + touch boltz_results_${meta.id}/predictions/${meta.id}/${meta.id}.cif + touch boltz_results_${meta.id}/predictions/${meta.id}/plddt_${meta.id}_model_0.npz + touch boltz_results_${meta.id}/predictions/${meta.id}/pae_${meta.id}_model_0.npz + + touch "${meta.id}_boltz.pdb" + touch "${meta.id}_plddt.tsv" + touch "${meta.id}_boltz_msa.tsv" + touch "${meta.id}_0_pae.tsv" + touch "${meta.id}_0_ptm.tsv" + touch "${meta.id}_0_iptm.tsv" + touch "${meta.id}_chainwise_ptm.tsv" + touch "${meta.id}_chainwise_iptm.tsv" cat <<-END_VERSIONS > versions.yml "${task.process}": - python: \$(python3 --version | sed 's/Python //g') + boltz: $version END_VERSIONS """ } diff --git a/nextflow.config b/nextflow.config index dcfccf8..7423d46 100644 --- a/nextflow.config +++ b/nextflow.config @@ -13,8 +13,16 @@ params { // Input options input = null mode = "all-all" - mmseq_batch_size = 10 - + mmseqs_batch_size = 10 + mmseqs_gpu = false + + colabfold_model_preset = "alphafold2_multimer_v3" + colabfold_num_recycles = 3 + tools = "boltz,colabfold" + + ipsae_pae_cutoff = 10 + ipsae_dist_cutoff = 10 + // MultiQC options multiqc_config = null multiqc_title = null @@ -154,6 +162,7 @@ profiles { test { includeConfig 'conf/test.config' } test_full { includeConfig 'conf/test_full.config' } test_gadi { includeConfig 'conf/test_gadi.config' } + gadi { includeConfig 'conf/gadi.config' } } // Load nf-core custom profiles from different Institutions diff --git a/nextflow_schema.json b/nextflow_schema.json index f29da16..e59345f 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -29,6 +29,23 @@ "description": "The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.", "fa_icon": "fas fa-folder-open" }, + "mode": { + "type": "string", + "default": "alphafold2", + "description": "Specifies the mode in which the pipeline will be run. mode can be any combination of ['alphafold2', 'alphafold3', 'colabfold', 'esmfold', 'rosettafold_all_atom', 'boltz', 'helixfold3'] separated by a comma (',') with no spaces.", + "fa_icon": "fas fa-cogs", + "errorMessage": "Mode must be a comma-separated list containing any combination of 'alphafold2', 'alphafold3', 'colabfold', 'esmfold', 'rosettafold_all_atom', 'boltz', or 'helixfold3' with no spaces." + }, + "mmseq_batch_size": { + "type": "integer", + "description": "Number of samples in each mmseq run (batching leads to higher performance time in total.)", + "fa_icon": "fas fa-microchip" + }, + "use_gpu": { + "type": "boolean", + "description": "Run on CPUs (default) or GPUs", + "fa_icon": "fas fa-microchip" + }, "email": { "type": "string", "description": "Email address for completion summary.", @@ -43,6 +60,78 @@ } } }, + "dbs_options": { + "title": "Databases options", + "type": "object", + "fa_icon": "fas fa-terminal", + "description": "Define where the pipeline should find input data and save output data.", + "required": ["input", "outdir"], + "properties": { + "colabfold_db": { + "type": "string", + "format": "path", + "exists": true, + "description": "Specifies the PARAMS and DB path used by 'colabfold' mode", + "fa_icon": "fas fa-folder-open", + "errorMessage": "Please provide a valid path to ColabFold database" + }, + "uniref30": { + "type": "string", + "description": "Link to the UniRef30 database", + "fa_icon": "fas fa-folder-open", + "default": "null/colabfold_uniref30/*" + }, + "colabfold_envdb": { + "type": "string", + "description": "Link to the ColabFold database", + "fa_icon": "fas fa-folder-open", + "default": "null/colabfold_envdb/*" + }, + "colabfold_alphafold2_params": { + "type": "string", + "description": "Link to the Alphafold2 parameters for Colabfold", + "fa_icon": "fas fa-folder-open" + }, + "colabfold_alphafold2_params_tags": { + "type": "object", + "description": "Dictionary with Alphafold2 parameters tags", + "fa_icon": "fas fa-stream" + }, + "boltz_db": { + "type": "string", + "description": "Path to boltz databases", + "icon": "fas folder-open" + }, + "boltz_ccd": { + "type": "string", + "description": "Path to CCD file", + "icon": "fas folder-open", + "default": "null/params/ccd.pkl" + }, + "boltz_model": { + "type": "string", + "description": "Path to boltz Model file", + "icon": "fas folder-open", + "default": "null/params/boltz1_conf.ckpt" + }, + "boltz2_aff": { + "type": "string", + "default": "null/params/boltz2_aff.ckpt", + "description": "Path to boltz affinity file" + }, + "boltz2_conf_path": { + "type": "string", + "default": "null/params/boltz2_conf.ckpt", + "description": "Path to boltz-2 conf file" + }, + "boltz2_mols_path": { + "type": "string", + "default": "null/params/mols/", + "description": "Path to boltz-2 mols" + } + } + }, + "institutional_config_options": { "title": "Institutional config options", "type": "object", diff --git a/subworkflows/local/msa.nf b/subworkflows/local/msa.nf index e30b989..b32acc0 100644 --- a/subworkflows/local/msa.nf +++ b/subworkflows/local/msa.nf @@ -13,11 +13,12 @@ workflow MSA { ch_samplesheet ch_colabfold_db // channel: path(colabfold_db) ch_uniref30 // channel: path(uniref30) - mmseq_batch_size + batch_size main: ch_versions = Channel.empty() ch_a3m = Channel.empty() + ch_json = Channel.empty() ch_samplesheet .branch { @@ -33,7 +34,7 @@ workflow MSA { } .set{ch_yaml_seqs} - if (mmseq_batch_size > 1){ + if (batch_size > 1){ def batch_itr = 0 ch_input.fasta @@ -43,7 +44,7 @@ workflow MSA { .mix( ch_yaml_seqs.map{it[1]} ) - .buffer( size: mmseq_batch_size, remainder: true ) + .buffer( size: batch_size, remainder: true ) .collectFile { batch_itr += 1; [ "input_seqs_${batch_itr}.csv", "id,sequence\n" + it.join("\n") + '\n' ] @@ -64,7 +65,7 @@ workflow MSA { .map{[it[2], it[1]]} ).set{ch_input_seqs} } - ch_input_seqs.view() + //ch_input_seqs.view() MMSEQS_COLABFOLDSEARCH ( ch_input_seqs, @@ -85,12 +86,25 @@ workflow MSA { ) .map{[it[1], it[2]]} ) + ch_json = ch_json.mix( + ch_input.fasta.mix(ch_input.yaml) + .map{[it[1].baseName, it[0]]} + .combine( + MMSEQS_COLABFOLDSEARCH.out.json + .map{it[1]} + .flatten() + .map {[it.baseName, it]}, + by:0 + ) + .map{[it[1], it[2]]} + ) //MMSEQS_COLABFOLDSEARCH.out.a3m.view() //ch_a3m.view() emit: formated_input = ch_input.fasta.mix(ch_input.yaml) a3m = ch_a3m + json = ch_json versions = ch_versions } diff --git a/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf b/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf index 784c656..9a5b9c4 100644 --- a/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf +++ b/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf @@ -68,26 +68,7 @@ workflow PIPELINE_INITIALISATION { // ch_samplesheet = Channel.fromList(samplesheetToList(params.input, "assets/schema_input.json")) - if (params.split_fasta) { - // TODO: here we have to validate that the ids are unique and valid as an extra step - // since it is not done with the samplesheet schema (they are all in the same file) - ch_samplesheet.map { meta, fasta -> - validateFasta(fasta) - } - - // Split the fasta file into individual files for each sequence - ch_samplesheet - .map { meta,fasta -> fasta } - .splitFasta( record: [header: true, sequence: true] ) - .collectFile { item -> - [ "${cleanHeader(item["header"])}.fa", ">" + cleanHeader(item["header"]) + '\n' +item["sequence"] ] - } - .map { - file -> [[id: file.baseName], file] - } - .set { ch_samplesheet } - } - + emit: samplesheet = ch_samplesheet versions = ch_versions diff --git a/workflows/interactions.nf b/workflows/interactions.nf deleted file mode 100644 index 6542a68..0000000 --- a/workflows/interactions.nf +++ /dev/null @@ -1,138 +0,0 @@ -/* -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - IMPORT LOCAL MODULES/SUBWORKFLOWS -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -*/ - -// -// MODULE: Loaded from modules/local/ -// - -/* -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - IMPORT NF-CORE MODULES/SUBWORKFLOWS -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -*/ - -// -// MODULE: Installed directly from nf-core/modules -// -include { MULTIQC } from '../modules/nf-core/multiqc/main' -include { CREATE_SAMPLESHEET_YAML } from '../modules/local/create_samplesheet' -include { MMSEQS_COLABFOLDSEARCH } from '../modules/local/mmseqs_colabfoldsearch' -include { PREPARE_INTERACTIONS } from '../modules/local/prepare_interactions' -include { COLLECT_CONFIDENCE } from '../modules/local/collect_confidence' -// -// SUBWORKFLOW: Consisting entirely of nf-core/modules -// -include { paramsSummaryMap } from 'plugin/nf-schema' -include { paramsSummaryMultiqc } from '../subworkflows/nf-core/utils_nfcore_pipeline' -include { softwareVersionsToYAML } from '../subworkflows/nf-core/utils_nfcore_pipeline' -include { methodsDescriptionText } from '../subworkflows/local/utils_nfcore_proteinfold_pipeline' - -// -// MODULE: Boltz -// -include { RUN_BOLTZ } from '../modules/local/run_boltz' - -/* -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - RUN MAIN WORKFLOW -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -*/ - -workflow INTERACTIONS { - - take: - ch_samplesheet_1 // channel: samplesheet read from --input - samplesheet_2 // channel: samplesheet read from --input - ch_versions // channel: [ path(versions.yml) ] - ch_boltz_ccd // channel: [ path(boltz_ccd) ] - ch_boltz_model // channel: [ path(model) ] - ch_colabfold_params // channel: [ path(colabfold_params) ] - ch_colabfold_db // channel: [ path(colabfold_db) ] - ch_uniref30 // channel: [ path(uniref30) ] - - main: - ch_multiqc_files = Channel.empty() - - Channel.fromPath(samplesheet_2) - .splitCsv(header: true) - .map{row -> [["id": row.id, "type": row.type ?: "protein"], file(row.fasta, checkIfExists: true)]} - .set{ch_samplesheet_2} - - ch_samplesheet_1.map{it[0]}.combine(ch_samplesheet_2.map{it[0]}).map{["id": [it[0]["id"], it[1]["id"]].min() + "-" + [it[0]["id"], it[1]["id"]].max()]}.unique().set{ch_unique_pairs} - - - MMSEQS_COLABFOLDSEARCH ( - ch_samplesheet_1.map{it[0].type = "protein"; it}.mix(ch_samplesheet_2).unique().filter{it[0].type == "protein"}, - ch_colabfold_params, - ch_colabfold_db, - ch_uniref30 - ) - ch_versions = ch_versions.mix(MMSEQS_COLABFOLDSEARCH.out.versions) - - ch_left_list = ch_samplesheet_1.join(MMSEQS_COLABFOLDSEARCH.out.a3m, remainder: true) - ch_right_list = ch_samplesheet_2.join(MMSEQS_COLABFOLDSEARCH.out.a3m, remainder: true) - - //ch_samplesheet_1.view() - //ch_samplesheet_2.view() - //MMSEQS_COLABFOLDSEARCH.out.a3m.view() - - //ch_left_list.combine(ch_right_list).view() - - ch_left_list - .combine(ch_right_list) - .map{[ - ["id": [it[0]["id"], it[3]["id"]].min() + "-" + [it[0]["id"], it[3]["id"]].max()], - [it[1].name, it[4].name], - [it[2] ? it[2].name : "", it[5] ? it[5].name : ""], - [it[0]["type"], it[3]["type"]], - [it[1], it[2], it[4], it[5]].findAll{it}.unique{it.toUriString()}, - - ]}.set{ch_pairs} - - ch_pairs - .join(ch_unique_pairs) - .set{ch_interaction_input} - - PREPARE_INTERACTIONS( - ch_interaction_input.map{[it[0], it[1]]}, - ch_interaction_input.map{[it[0], it[2]]}, - ch_interaction_input.map{[it[0], it[3]]}, - ch_interaction_input.map{it[4]} - ) - - PREPARE_INTERACTIONS.out.fasta - .join(ch_interaction_input) - .set{ch_boltz_input} - - RUN_BOLTZ( - ch_boltz_input.map{[it[0], it[1]]}, - ch_boltz_input.map{it[5].findAll { it.name.endsWith(".a3m") }}, - ch_boltz_model, - ch_boltz_ccd - ) - RUN_BOLTZ.out.confidence.toSortedList().multiMap{json_list -> - ids: json_list.collect{it[0].id} - json: json_list.collect{it[1]} - }.set{ch_confidence_scores} - - COLLECT_CONFIDENCE( - ch_confidence_scores.ids.map{[["id": "full_run"], it]}, - ch_confidence_scores.json - ) - - //ch_confidence_scores.ids.view() - //ch_confidence_scores.json.view() - - emit: - versions = ch_versions - msa = RUN_BOLTZ.out.msa - structures = RUN_BOLTZ.out.structures - confidence = RUN_BOLTZ.out.confidence - run_confidence = COLLECT_CONFIDENCE.out.confidence - plddt = RUN_BOLTZ.out.plddt - pdb = RUN_BOLTZ.out.pdb - -} diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 23364ca..d927483 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -29,9 +29,15 @@ include { softwareVersionsToYAML } from '../subworkflows/nf-core/utils_nfcore_pi include { MSA } from '../subworkflows/local/msa' // -// MODULE: Boltz +// LOCAL MODULE: Boltz // include { RUN_BOLTZ } from '../modules/local/run_boltz' +include { RUN_ALPHAFOLD3 } from '../modules/local/run_alphafold3' +include { COLABFOLD_BATCH } from '../modules/local/colabfold_batch' +include { BOLTZ_FASTA } from '../modules/local/data_convertor/boltz_fasta' +include { SPLIT_MSA } from '../modules/local/msa_manager/split_msa' +include { IPSAE } from '../modules/local/ipsae' + // // FUNCTIONS @@ -55,12 +61,26 @@ workflow WISPS { ch_boltz_ccd // channel: [ path(boltz_ccd) ] ch_boltz_model // channel: [ path(model) ] ch_colabfold_db // channel: [ path(colabfold_db) ] + ch_boltz2_aff // channel: [ path(boltz2_aff) ] + ch_boltz2_conf // channel: [ path(boltz2_conf) ] + ch_mols // channel: [ path(mols) ] ch_uniref30 // channel: [ path(uniref30) ] - mmseq_batch_size // number + mmseqs_batch_size // number + colabfold_model_preset + ch_colabfold_params + num_recycles + ch_alphafold3_params // channel: path(alphafold2_params) + ch_small_bfd // channel: path(small_bfd) + ch_mgnify // channel: path(mgnify) + ch_mmcif_files // channel: path(mmcif_files) + ch_uniref90 // channel: path(uniref90) + ch_pdb_seqres // channel: path(pdb_seqres) + ch_uniprot // channel: path(uniprot) + tools main: ch_multiqc_files = Channel.empty() - + ch_confidence_scores = Channel.empty() interaction_mode = mode.split(",").collect { pair -> pair.split('-').sort().join('-') } @@ -92,90 +112,242 @@ workflow WISPS { .unique() .set{ch_unique_pairs} - ch_samplesheet - .branch { - fasta: it[1].extension == "fasta" || it[1].extension == "fa" - it[0].cnt = getFastaSequences(it[1].text).size() - return it - yaml: it[1].extension == "yaml" || it[1].extension == ".yml" - it[0].cnt = getYamlSequences(it[1].text).size() - return it - json: it[1].extension == "json" + /*ch_samplesheet + .map { + if (it[1].extension == "fasta" || it[1].extension == "fa") + {it[0].cnt = getFastaSequences(it[1].text).size()} + else if (it[1].extension == "yaml" || it[1].extension == ".yml") + {it[0].cnt = getYamlSequences(it[1].text).size()} + else if (it[1].extension == "json") + {it[0].cnt = 0} } - .set{ch_input} + .set{ch_input_seqs} + */ + + ch_samplesheet + .combine(ch_samplesheet) + .map{[ + [ + "id": [it[0]["id"], it[2]["id"]].min() + "-" + [it[0]["id"], it[2]["id"]].max(), + "group": [it[0]["group"], it[2]["group"]].min() + "-" + [it[0]["group"], it[2]["group"]].max(), + ], + [it[0], it[2]], + [it[1], it[3]], + ]}.set{ch_pairs} + ch_pairs + .join(ch_unique_pairs) + .set{ch_interaction_in} + //ch_interaction_in.view() + + ch_interaction_in + .filter{it[1][0].type == "protein" && it[1][1].type == "protein"} + .collectFile{ + seqs = [] + for (j in [0, 1]){ + if (it[2][j].extension == "fasta" || it[2][j].extension == "fa") + {seqs.add(getFastaSequences(it[2][j].text))} + else if (it[2][j].extension == "yaml" || it[2][j].extension == ".yml") + {seqs.add(getYamlSequences(it[2][j].text))} + else if (it[2][j].extension == "json") + {seqs.add("")} + } + [ "${it[0].id}.fasta", ">${it[0].id}\n${seqs.collect{it.sequence.join(":")}.join(":")}\n" ] + } + .map{[["id": it.baseName], it]} + .set {ch_protein_pairs} + //ch_protein_pairs.view() MSA ( - ch_input.fasta - .mix(ch_input.json) - .mix(ch_input.yaml) - .filter{it[0].type == "protein"}, + ch_protein_pairs + .mix( + ch_interaction_in + .map{ + if (it[1][0].type != "protein" && it[1][1].type == "protein"){ + [it[1][1], it[2][1]] + }else if (it[1][1].type != "protein" && it[1][0].type == "protein"){ + [it[1][0], it[2][0]] + } + }.unique() + ), ch_colabfold_db, ch_uniref30, - mmseq_batch_size + mmseqs_batch_size ) ch_versions = ch_versions.mix(MSA.out.versions) - ch_input.fasta - .mix(ch_input.json) - .mix(ch_input.yaml) - .map{[it[0].id, it]} - .join( - MSA.out.a3m.map{[it[0].id, it]} - , remainder: true - ) - .map{[it[2][0], it[1][1], it[2][1]]} - .set{ch_input_aligned} - - ch_input_aligned - .combine(ch_input_aligned) - .map{[ - [ - "id": [it[0]["id"], it[3]["id"]].min() + "-" + [it[0]["id"], it[3]["id"]].max(), - "group": [it[0]["group"], it[3]["group"]].min() + "-" + [it[0]["group"], it[3]["group"]].max(), - ], - [it[1].name, it[4].name], - [it[2] ? it[2].name : "", it[5] ? it[5].name : ""], - [it[0]["type"], it[3]["type"]], - [it[1], it[2], it[4], it[5]].findAll{it}.unique{it.toUriString()}, - - ]}.set{ch_pairs} + //MSA.out.json.view() + //ch_interaction_in.view() - //ch_pairs.view() + // Prepare interactions for boltz + ch_boltz_data = Channel.empty() + ch_split_msa_in = Channel.empty() + ch_boltz_interactions_in = Channel.empty() + + if ("boltz" in tools.split(",")){ + ch_split_msa_in = MSA.out.a3m.join(ch_protein_pairs.map{it[0]}) + ch_boltz_interactions_in = ch_interaction_in + } + + ch_boltz_data = ch_boltz_data.mix(ch_boltz_interactions_in + .filter{it[1][0].type != "protein" && it[1][1].type != "protein"} + .map{[it, ["", ""]]} + ) + + ch_boltz_data = ch_boltz_data.mix( + ch_boltz_interactions_in + .filter{[it[1][0].type, it[1][1].type].count("protein") == 1} + .map{ + if (it[1][0].type == "protein"){ + [it[1][0], it] + }else if (it[1][1].type == "protein"){ + [it[1][1], it] + } + } + .combine(MSA.out.a3m.filter{it[0].type == "protein"}) + .filter{it[0] == it[2]} + .map{ + if (it[1][1][0].type == "protein") + [it[1], [it[3], ""]] + else + [it[1], ["", it[3]]] + } + ) + + SPLIT_MSA( + ch_split_msa_in.join(ch_protein_pairs.map{it[0]}) + ) + + ch_versions = ch_versions.mix(SPLIT_MSA.out.versions) - ch_pairs - .join(ch_unique_pairs) - .set{ch_interaction_input} + ch_boltz_data = ch_boltz_data.mix(ch_boltz_interactions_in + .filter{it[1][0].type == "protein" && it[1][1].type == "protein"} + .map{[["id": it[0].id], it]} + .join( + SPLIT_MSA.out.msa_csv + .map{ + if (it[1] instanceof List){ + if (it[1].size() != 2){ + log.warn "Something wrong with the data expected 2 csv!" + } + }else{ + it[1] = [it[1], it[1]] + } + it + } + + ) + .map{[it[1], it[2]]} + ) - //ch_interaction_input.view() - PREPARE_INTERACTIONS( - ch_interaction_input.map{[it[0], it[1]]}, - ch_interaction_input.map{[it[0], it[2]]}, - ch_interaction_input.map{[it[0], it[3]]}, - ch_interaction_input.map{it[4]} + ch_boltz_data.map{[it[0][0], it[0][2].collect{it.name}]}, + ch_boltz_data.map{[it[0][0], it[1].collect{it ? it.name: ""}]}, + ch_boltz_data.map{[it[0][0], [it[0][1][0].type, it[0][1][1].type]]}, + ch_boltz_data.map{[it[0][2][0], it[0][2][1], it[1][0], it[1][1]].findAll{it}.unique{it.toUriString()}} + ) + //PREPARE_INTERACTIONS.out.fasta.view() + + PREPARE_INTERACTIONS.out.fasta.join( + ch_boltz_data.map{[it[0][0], [it[1][0], it[1][1]].findAll{it}.unique{it.toUriString()}]} ) + .map{ + meta = it[0].clone() + meta.model = "boltz" + [meta, it[1], it[2]] + } + .set{ch_boltz_in} + + //ch_boltz_in.view() - PREPARE_INTERACTIONS.out.fasta - .join(ch_interaction_input) - .set{ch_boltz_input} RUN_BOLTZ( - ch_boltz_input.map{[it[0], it[1]]}, - ch_boltz_input.map{it[5].findAll { it.name.endsWith(".a3m") }}, + ch_boltz_in.map{[it[0], it[1]]}, + ch_boltz_in.map{it[2]}, ch_boltz_model, - ch_boltz_ccd + ch_boltz_ccd, + ch_boltz2_aff, + ch_boltz2_conf, + ch_mols ) - RUN_BOLTZ.out.confidence.toSortedList().multiMap{json_list -> + + RUN_BOLTZ.out.confidence.collect(flat: false, sort: true).multiMap{json_list -> ids: json_list.collect{it[0].id} json: json_list.collect{it[1]} }.set{ch_confidence_scores} + + //prepare interactions for colabfold + ch_colabfold_interaction_in = Channel.empty() + if ("colabfold" in tools.split(",")){ + MSA.out.a3m.join(ch_protein_pairs.map{it[0]}) + .map{ + meta = it[0].clone() + meta.model = "colabfold" + [meta, it[1]] + } + .set{ + ch_colabfold_interaction_in + } + } + //ch_colabfold_interaction_in.view() + + COLABFOLD_BATCH( + ch_colabfold_interaction_in, + colabfold_model_preset, + ch_colabfold_params, + [], + [], + num_recycles + ) + ch_versions = ch_versions.mix(COLABFOLD_BATCH.out.versions) + + ch_alphafold3_interaction_in = Channel.empty() + if ("ZZalphafold3" in tools.split(",")){ + MSA.out.json.join(ch_protein_pairs.map{it[0]}) + .map{ + meta = it[0].clone() + meta.model = "alphafold3" + [meta, it[1]]} + .set{ + ch_alphafold3_interaction_in + } + } + + + RUN_ALPHAFOLD3 ( + ch_alphafold3_interaction_in, + ch_alphafold3_params, + ch_small_bfd, + ch_mgnify, + ch_mmcif_files, + ch_uniref90, + ch_pdb_seqres, + ch_uniprot + ) + + IPSAE( + COLABFOLD_BATCH.out.top_ranked_scores.join( + COLABFOLD_BATCH.out.top_ranked_pdb + ).map{[["id": it[0].id], it]} + .join(ch_protein_pairs.map{it[0]}) + .mix( + RUN_BOLTZ.out.pae.join(RUN_BOLTZ.out.cif) + .map{[["id": it[0].id], it]} + .join(ch_protein_pairs.map{it[0]}) + ) + .mix( + RUN_ALPHAFOLD3.out.pae.join(RUN_ALPHAFOLD3.out.top_ranked_cif) + .map{[["id": it[0].id], it]} + .join(ch_protein_pairs.map{it[0]}) + ) + .map{it[1]} + ) + COLLECT_CONFIDENCE( ch_confidence_scores.ids.map{[["id": "full_run"], it]}, ch_confidence_scores.json ) - //ch_confidence_scores.ids.view() //ch_confidence_scores.json.view() @@ -187,5 +359,4 @@ workflow WISPS { run_confidence = COLLECT_CONFIDENCE.out.confidence plddt = RUN_BOLTZ.out.plddt pdb = RUN_BOLTZ.out.pdb - } From 2bea094eb8105daf40fc457698e1e67348023a8b Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Thu, 2 Oct 2025 17:20:26 +1000 Subject: [PATCH 04/70] fixing ipsae input --- modules/local/ipsae/main.nf | 2 + workflows/wisps.nf | 78 ++++++++++++++++++++++--------------- 2 files changed, 48 insertions(+), 32 deletions(-) diff --git a/modules/local/ipsae/main.nf b/modules/local/ipsae/main.nf index 72f3eeb..ed4551c 100644 --- a/modules/local/ipsae/main.nf +++ b/modules/local/ipsae/main.nf @@ -9,6 +9,8 @@ process IPSAE { input: tuple val(meta), path(pae), path(pdb) + path (extra_files) + output: tuple val(meta), path ("*.pml"), emit: pml tuple val(meta), path ("*_byres.txt"), emit: byres diff --git a/workflows/wisps.nf b/workflows/wisps.nf index d927483..48e9b5a 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -157,18 +157,21 @@ workflow WISPS { } .map{[["id": it.baseName], it]} .set {ch_protein_pairs} + + ch_interaction_in + .map{ + if (it[1][0].type != "protein" && it[1][1].type == "protein"){ + [it[1][1], it[2][1]] + }else if (it[1][1].type != "protein" && it[1][0].type == "protein"){ + [it[1][0], it[2][0]] + } + }.unique() + .set{ch_single_protein} //ch_protein_pairs.view() MSA ( ch_protein_pairs .mix( - ch_interaction_in - .map{ - if (it[1][0].type != "protein" && it[1][1].type == "protein"){ - [it[1][1], it[2][1]] - }else if (it[1][1].type != "protein" && it[1][0].type == "protein"){ - [it[1][0], it[2][0]] - } - }.unique() + ch_single_protein ), ch_colabfold_db, ch_uniref30, @@ -252,15 +255,14 @@ workflow WISPS { ch_boltz_data.map{[it[0][0], [it[1][0], it[1][1]].findAll{it}.unique{it.toUriString()}]} ) .map{ - meta = it[0].clone() - meta.model = "boltz" - [meta, it[1], it[2]] + meta = it[0].clone() + meta.model = "boltz" + [meta, it[1], it[2]] } .set{ch_boltz_in} //ch_boltz_in.view() - - + RUN_BOLTZ( ch_boltz_in.map{[it[0], it[1]]}, ch_boltz_in.map{it[2]}, @@ -302,7 +304,7 @@ workflow WISPS { ch_versions = ch_versions.mix(COLABFOLD_BATCH.out.versions) ch_alphafold3_interaction_in = Channel.empty() - if ("ZZalphafold3" in tools.split(",")){ + if ("alphafold3" in tools.split(",")){ MSA.out.json.join(ch_protein_pairs.map{it[0]}) .map{ meta = it[0].clone() @@ -313,7 +315,6 @@ workflow WISPS { } } - RUN_ALPHAFOLD3 ( ch_alphafold3_interaction_in, ch_alphafold3_params, @@ -325,22 +326,37 @@ workflow WISPS { ch_uniprot ) - IPSAE( - COLABFOLD_BATCH.out.top_ranked_scores.join( - COLABFOLD_BATCH.out.top_ranked_pdb - ).map{[["id": it[0].id], it]} - .join(ch_protein_pairs.map{it[0]}) - .mix( - RUN_BOLTZ.out.pae.join(RUN_BOLTZ.out.cif) - .map{[["id": it[0].id], it]} - .join(ch_protein_pairs.map{it[0]}) + + COLABFOLD_BATCH.out.top_ranked_scores + .join(COLABFOLD_BATCH.out.top_ranked_pdb) + .map{[["id": it[0].id], it, []]} + .join(ch_interaction_in + .filter{it[1][0].type == "protein" || it[1][1].type == "protein"} + .map{["id": it[0].id]} + ) + .mix( + RUN_BOLTZ.out.pae + .join(RUN_BOLTZ.out.cif) + .join(RUN_BOLTZ.out.confidence) + .map{[["id": it[0].id], [it[0], it[1], it[2]], it[3]]} + .join(ch_interaction_in + .filter{it[1][0].type == "protein" || it[1][1].type == "protein"} + .map{["id": it[0].id]} ) - .mix( - RUN_ALPHAFOLD3.out.pae.join(RUN_ALPHAFOLD3.out.top_ranked_cif) - .map{[["id": it[0].id], it]} - .join(ch_protein_pairs.map{it[0]}) + ) + .mix( + RUN_ALPHAFOLD3.out.pae.join(RUN_ALPHAFOLD3.out.top_ranked_cif) + .map{[["id": it[0].id], it, []]} + .join(ch_interaction_in + .filter{it[1][0].type == "protein" || it[1][1].type == "protein"} + .map{["id": it[0].id]} ) - .map{it[1]} + ) + .set{ch_ipsae_in} + + IPSAE( + ch_ipsae_in.map{it[1]}, + ch_ipsae_in.map{it[2]} ) @@ -348,9 +364,7 @@ workflow WISPS { ch_confidence_scores.ids.map{[["id": "full_run"], it]}, ch_confidence_scores.json ) - //ch_confidence_scores.ids.view() - //ch_confidence_scores.json.view() - + emit: versions = ch_versions msa = RUN_BOLTZ.out.msa From 2c9b86c1026a35e4dbfd84ac2c5ebfcb9c4d1465 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Thu, 2 Oct 2025 23:42:36 +1000 Subject: [PATCH 05/70] add multiqc --- bin/extract_metrics.py | 218 +----------------------- main.nf | 29 ++-- modules/local/collect_confidence.nf | 100 ++++++++--- modules/local/run_alphafold3/Dockerfile | 97 ++++++----- modules/local/run_alphafold3/main.nf | 30 +--- workflows/wisps.nf | 96 ++++++++--- 6 files changed, 222 insertions(+), 348 deletions(-) diff --git a/bin/extract_metrics.py b/bin/extract_metrics.py index c8db726..f952b21 100755 --- a/bin/extract_metrics.py +++ b/bin/extract_metrics.py @@ -243,220 +243,4 @@ def read_csv(name, csv_files): unpaired_msa_rows[csv_file.split('_')[-1].split('.csv')[0]] = [[str(AA_to_int.get(residue, 20)) for residue in line] for line in unpaired_msa_lines] # Get Chain to MSA mapping (ie non-redundant for homomers) - # TODO: Make this explicit input - with open(f'boltz_results_{name}/processed/manifest.json') as f: - manifest = json.load(f) - - final_rows = [] - # Paired - for i in range(len(msa_rows["0"])): #The number of paired lines is common to all MSAs - temp_row = [] - #This needs to be fixed if inference is batched in future. - for chain in manifest["records"][0]["chains"]: - j = chain["msa_id"].split("_")[-1] - temp_row.extend(msa_rows[j][i]) - final_rows.append(temp_row) - - # Un-paired - msa_widths = [len(msa_rows[chain["msa_id"].split("_")[-1]][0]) for chain in manifest["records"][0]["chains"]] - msa_heights = [len(unpaired_msa_rows[chain["msa_id"].split("_")[-1]]) for chain in manifest["records"][0]["chains"]] - - cum_total_rows = np.cumsum(msa_heights) - - for row_idx in range(cum_total_rows[-1]): - temp_row = [] - - for i, chain in enumerate(manifest["records"][0]["chains"]): - msa = unpaired_msa_rows[chain["msa_id"].split("_")[-1]] - width = msa_widths[i] - if i == 0: - minrow = 0 - else: - minrow = cum_total_rows[i-1] - maxrow = cum_total_rows[i] - - if minrow <= row_idx < maxrow: - msa_row_idx = row_idx - minrow - temp_row.extend(msa[msa_row_idx]) - else: - temp_row.extend(["21"] * width) #gap - final_rows.append(temp_row) - - write_tsv(f"{name}_msa.tsv", final_rows) - -def read_json(name, json_files): - ptm_data = {} - iptm_data = {} - chain_pair_iptm_data = {} # For iPTM data to be converted into formatted pairs with non-self elements - chain_pair_entries = {} - chainwise_ptms = {} - chain_ids = [] - - for idx, json_file in enumerate(json_files): - with open(json_file, 'r') as f: - data = json.load(f) - if json_file.endswith("_data.json"): #AF3 output with MSA info - # Can't just used format_msa_rows since there's FASTA headers in the json content - paired_msa_rows = [] - unpaired_msa_rows = [] - for chain in data['sequences']: - unpaired_MSA = chain['protein']['unpairedMsa'] - unpaired_msa_lines = [''.join(c for c in line if not c.islower()) for line in unpaired_MSA.split("\n") if line.strip() and not line.startswith(">")] - unpaired_msa_rows.append([[str(AA_to_int.get(residue, 20)) for residue in line] for line in unpaired_msa_lines]) - paired_MSA = chain['protein']['pairedMsa'] - paired_msa_lines = [''.join(c for c in line if not c.islower()) for line in paired_MSA.split("\n") if line.strip() and not line.startswith(">")] - paired_msa_rows.append([[str(AA_to_int.get(residue, 20)) for residue in line] for line in paired_msa_lines]) - - chains = len(data['sequences']) - final_rows = [] - # Paired - for i in range(len(paired_msa_rows[0])): #The number of paired lines is common to all MSAs - temp_row = [] - #This needs to be fixed if inference is batched in future. - for j in range(chains): - temp_row.extend(paired_msa_rows[j][i]) - final_rows.append(temp_row) - - # Un-paired - msa_widths = [len(paired_msa_rows[chain][0]) for chain in range(chains)] - msa_heights = [len(unpaired_msa_rows[chain]) for chain in range(chains)] - - cum_total_rows = np.cumsum(msa_heights) - - for row_idx in range(cum_total_rows[-1]): - temp_row = [] - - for i in range(chains): - msa = unpaired_msa_rows[i] - width = msa_widths[i] - if i == 0: - minrow = 0 - else: - minrow = cum_total_rows[i-1] - maxrow = cum_total_rows[i] - if minrow <= row_idx < maxrow: - msa_row_idx = row_idx - minrow - temp_row.extend(msa[msa_row_idx]) - else: - temp_row.extend(["21"] * width) #gap - final_rows.append(temp_row) - write_tsv(f"{name}_msa.tsv", final_rows) - #AF3 output with PAE info, or HF3 PAE data. TODO: Need to make sure the workflow points to [protein]/[protein]_rank1/all_results.json - - # TODO: I think I need to capture model_id and inference_id -- MUST FIX since this is so fragile and will be different for different programs. - #if '_alphafold2_ptm_model_' in json_file: # ColabFold, multimer or monomer - ## Might want to cut more if I just want ${meta.id}_[metric].tsv - # model_id = os.path.basename(json_file) - # print(model_id) - if 'all_results' in json_file: # Individual predictions in HF3 - model_id = int(os.path.dirname(json_file).split('-rank')[-1]) #Use re-ranked output - if 'predictions' in json_file: # Boltz-1 confidences in predictions/[protein]/confidence_[protein]_model_*.json - # TODO: haven't tested this for multiple models with --diffusion_samples - model_id = os.path.basename(json_file).split('_model_')[-1].split('.json')[0] - #TODO: Fix this for AF3 - the top-ranked files are in the top-level directory - if 'confidences' in json_file: #Prevent crash when model_id is not defined - #model_id = os.path.basename(json_file).split('confidences_')[-1].split('.json')[0] - model_id = 0 - - if "pae" not in data.keys(): - print(f"No PAE output in {json_file}, it was likely a monomer calculation") - else: - write_tsv(f"{name}_{model_id}_pae.tsv", format_pae_rows(data["pae"])) - - if 'ptm' not in data.keys(): - print(f"No pTM/iPTM output in {json_file}, it was likely a monomer calculation") - #This message should change - currently called on boltz files not expected to contain ptm - else: - ptm_data[model_id] = f"{np.round(data['ptm'],3)}\n" - - if 'iptm' not in data.keys(): - print(f"No pTM/iPTM output in {json_file}, it was likely a monomer calculation") - else: - if data['iptm']: #ie not null - iptm_data[model_id] = f"{np.round(data['iptm'],3)}\n" - - if 'chain_pair_iptm' not in data.keys() and 'pair_chains_iptm' not in data.keys(): - print(f"No chain-wise iPTM output in {json_file}, it was likely a monomer calculation") - else: - if 'chain_pair_iptm' in data.keys(): - chain_pair_iptm_data = data['chain_pair_iptm'] - chain_iptm_matrix = np.array(chain_pair_iptm_data) - elif 'pair_chains_iptm' in data.keys(): #Boltz key - chain_pair_iptm_data = data['pair_chains_iptm'] - # casting to int works for sorting boltz - need to carefully check other modes - chain_iptm_matrix = np.array([[chain_pair_iptm_data[row][col] for col in sorted(chain_pair_iptm_data[row], key=int)] for row in sorted(chain_pair_iptm_data, key=int)]) - basename = os.path.basename(json_file) - dirname = os.path.dirname(json_file) - pdb_name = ".".join(basename[11:].split('.')[:-1])+'.pdb' #TODO: Fix magic number - chain_ids = get_chain_ids(os.path.join(dirname,pdb_name)) - else: - raise ValueError("No chain-wise iPTM data found in the JSON file.") - - chain_pair_entries[model_id] = chain_iptm_matrix_to_pairs(chain_iptm_matrix) - chainwise_ptms[model_id] = chainwise_iptm_matrix_to_ptms(chain_iptm_matrix) - - if chainwise_ptms: - write_tsv(f"{name}_chainwise_ptm.tsv", format_iptm_rows(chainwise_ptms, chain_ids=chain_ids)) - - if chain_pair_entries: - write_tsv(f"{name}_chainwise_iptm.tsv", format_iptm_rows(chain_pair_entries, chain_ids=chain_ids)) - - if ptm_data: - ptm_rows = [[k, v.strip()] for k, v in sorted(ptm_data.items(), key=lambda x: x[0])] - write_tsv(f"{name}_ptm.tsv", ptm_rows) - - if iptm_data: - iptm_rows = [[k, v.strip()] for k, v in sorted(iptm_data.items(), key=lambda x: x[0])] - write_tsv(f"{name}_iptm.tsv", iptm_rows) - - -def read_pt(name, pt_files): - import torch # moved to a conditional import since too bulky import if not used - #TODO: Handle this better when refactored - Is this just RFAA?? - for pt_file in pt_files: - with open(pt_file, 'rb') as f: # TODO: point to [protein]_aux.pt - data = torch.load(f, map_location="cpu") - if 'pae' in data: - # The pt file contains a tensor that needs to be cast as an array - # Squeeze leading dimension (batch?) - write_tsv(f"{name}_0_pae.tsv", format_pae_rows(np.squeeze(data["pae"].numpy()))) - break - -def read_colabfold_paes(name, colabfold_pae_fn): - with open(colabfold_pae_fn) as f: - data = json.load(f) - pae = data["predicted_aligned_error"] - write_tsv(f"{name}_0_pae.tsv", format_pae_rows(pae)) - -def main(): - parser = argparse.ArgumentParser() - parser.add_argument("--pkls", dest="pkls", required=False, nargs="+") # For reading both HelixFold3 and AlphaFold2 MSA formats - parser.add_argument("--npzs", dest="npzs", required=False, nargs="+") # For reading the Boltz-1 PAE formats. TODO: Boltz-1 MSA not implemented (go straight to .a3m file), implement - parser.add_argument("--a3ms", dest="a3ms", required=False, nargs="+") # For reading the RosettaFold-All-Atom, ColabFold MSA formats - parser.add_argument("--csvs", dest="csvs", required=False, nargs="+") # For reading boltz csvs - parser.add_argument("--jsons", dest="jsons", required=False, nargs="+") # For reading the AF3 MSA & PAE, HF3 PAE - parser.add_argument("--colabfold_pae_fn", required=False) - parser.add_argument("--pts", dest="pts", required=False, nargs="+") # For read RFAA pytorch model to get PAE data - parser.add_argument("--structs", dest="structs", required=False, nargs="+") - parser.add_argument("--name", default="untitled", dest="name") # might need a --name $meta.id - args = parser.parse_args() - - if args.pkls: - read_pkl(args.name, args.pkls) - if args.a3ms: - read_a3m(args.name, args.a3ms) - if args.csvs: - read_csv(args.name, args.csvs) - if args.npzs: - read_npz(args.name, args.npzs) - if args.jsons: - read_json(args.name, args.jsons) - if args.pts: - read_pt(args.name, args.pts) - if args.structs: - extract_structs_plddt_to_tsv(args.name, args.structs) - if args.colabfold_pae_fn: - read_colabfold_paes(args.name, args.colabfold_pae_fn) - -if __name__ == "__main__": - main() + # TODO: Make this explicit inpu... \ No newline at end of file diff --git a/main.nf b/main.nf index c4301d2..291b09f 100644 --- a/main.nf +++ b/main.nf @@ -8,15 +8,12 @@ Slack : https://nfcore.slack.com/channels/wisps ---------------------------------------------------------------------------------------- */ - /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ IMPORT FUNCTIONS / MODULES / SUBWORKFLOWS / WORKFLOWS ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ - include { WISPS } from './workflows/wisps' - include { PIPELINE_INITIALISATION } from './subworkflows/local/utils_nfcore_wisps_pipeline' include { PIPELINE_COMPLETION } from './subworkflows/local/utils_nfcore_wisps_pipeline' /* @@ -24,24 +21,24 @@ include { PIPELINE_COMPLETION } from './subworkflows/local/utils_nfcore_wisp NAMED WORKFLOWS FOR PIPELINE ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ - // // WORKFLOW: Run main analysis pipeline depending on type of input // workflow NFCORE_WISPS { - take: samplesheet // channel: samplesheet read in from --input - main: ch_samplesheet = samplesheet ch_multiqc = Channel.empty() ch_versions = Channel.empty() multiqc_report = Channel.empty() + ch_multiqc_config = Channel.fromPath("$projectDir/assets/multiqc_config.yml", checkIfExists: true).first() + ch_multiqc_custom_config = params.multiqc_config ? Channel.fromPath( params.multiqc_config ).first() : Channel.empty() + ch_multiqc_logo = params.multiqc_logo ? Channel.fromPath( params.multiqc_logo ).first() : Channel.empty() + ch_multiqc_methods_description = params.multiqc_methods_description ? file(params.multiqc_methods_description, checkIfExists: true) : file("$projectDir/assets/methods_description_template.yml", checkIfExists: true) // // WORKFLOW: Run pipeline // - WISPS ( ch_samplesheet, @@ -59,14 +56,12 @@ workflow NFCORE_WISPS { Channel.fromPath(params.colabfold_alphafold2_params, checkIfExists: true).first(), params.colabfold_num_recycles, Channel.fromPath(params.alphafold3_params, checkIfExists: true).first(), - Channel.fromPath(params.alphafold3_small_bfd, checkIfExists: true).first(), - Channel.fromPath(params.alphafold3_mgnify, checkIfExists: true).first(), - Channel.fromPath(params.alphafold3_pdb_mmcif, checkIfExists: true).first(), - Channel.fromPath(params.alphafold3_uniref90, checkIfExists: true).first(), - Channel.fromPath(params.alphafold3_pdb_seqres, checkIfExists: true).first(), - Channel.fromPath(params.alphafold3_uniprot, checkIfExists: true).first(), - params.tools - + params.tools, + ch_multiqc_config, + ch_multiqc_custom_config, + ch_multiqc_logo, + ch_multiqc_methods_description, + params.outdir ) ch_versions = ch_versions.mix(WISPS.out.versions) @@ -78,9 +73,7 @@ workflow NFCORE_WISPS { RUN MAIN WORKFLOW ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ */ - workflow { - main: // // SUBWORKFLOW: Run initialisation tasks @@ -93,7 +86,6 @@ workflow { params.outdir, params.input ) - // // WORKFLOW: Run main workflow // @@ -113,7 +105,6 @@ workflow { NFCORE_WISPS.out.multiqc_report ) } - /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ THE END diff --git a/modules/local/collect_confidence.nf b/modules/local/collect_confidence.nf index 77881ac..95223c1 100644 --- a/modules/local/collect_confidence.nf +++ b/modules/local/collect_confidence.nf @@ -11,7 +11,7 @@ process COLLECT_CONFIDENCE { tuple val(meta), val(samples) path(json_files) output: - tuple val(meta), path ("confidence_scores_full.csv"), emit: confidence + tuple val(meta), path ("*confidence_scores_full.csv"), emit: confidence path "versions.yml" , emit: versions when: @@ -28,41 +28,87 @@ process COLLECT_CONFIDENCE { import csv # Folder containing the JSON files - output_csv = "confidence_scores_full.csv" + output_csv = "${meta.model}_confidence_scores_full.csv" # Collect all JSON files json_files = ["${json_files.join('", "')}"] samples = ["${samples.join('", "')}"] - # Store all rows here - rows = [] - all_keys = ["confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde", "chains_ptm"] - writing_keys = ["id", "confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde"] - # First pass: read and collect keys - cntr = 0 - for file in json_files: - with open(file) as f: - data = json.load(f) - flat_data = {"id" : samples[cntr]} - cntr += 1 - for key, value in data.items(): - if key not in all_keys: + def extract_boltz_results(json_files, samples, output_csv): + rows = [] + all_keys = ["confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde", "chains_ptm"] + writing_keys = ["id", "confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde"] + # First pass: read and collect keys + cntr = 0 + for file in json_files: + with open(file) as f: + data = json.load(f) + flat_data = {"id": samples[cntr]} + cntr += 1 + for key, value in data.items(): + if key not in all_keys: + continue + if isinstance(value, dict): + for sub_key, sub_value in value.items(): + flat_data[f"{key}_{sub_key}"] = sub_value + writing_keys.append(f"{key}_{sub_key}") + else: + flat_data[key] = value + rows.append(flat_data) + + # Write to CSV + with open(output_csv, "w", newline="") as f: + writer = csv.DictWriter(f, fieldnames=writing_keys) + writer.writeheader() + for row in rows: + writer.writerow({key: row.get(key, "") for key in writing_keys}) + + def extract_colabfold_results(json_files, samples, output_csv): + def parse_colabfold_metrics(json_file): + with open(json_file, "r") as f: + data = json.load(f) + + result = {} + for key in ["iptm", "max_pae", "pae", "ptm", "plddt"]: + if key not in data: + result[key] = None continue - if isinstance(value, dict): - for sub_key, sub_value in value.items(): - flat_data[f"{key}_{sub_key}"] = sub_value - writing_keys.append(f"{key}_{sub_key}") + + if key == "plddt" and isinstance(data[key], list): + # Compute mean for list + result[key] = statistics.mean(data[key]) if data[key] else None else: - flat_data[key] = value + # Take value directly + result[key] = data[key] + + return result + + rows = [] + all_keys = ["id", "plddt", "ptm", "iptm", "max_pae"] + writing_keys = all_keys + cntr = 0 + for file in json_files: + flat_data = parse_colabfold_metrics(file) + flat_data["id"] = samples[cntr] + cntr += 1 rows.append(flat_data) - - # Write to CSV - with open(output_csv, "w", newline="") as f: - writer = csv.DictWriter(f, fieldnames=writing_keys) - writer.writeheader() - for row in rows: - writer.writerow({key: row.get(key, "") for key in writing_keys}) + # Write to CSV + with open(output_csv, "w", newline="") as f: + writer = csv.DictWriter(f, fieldnames=writing_keys) + writer.writeheader() + for row in rows: + writer.writerow({key: row.get(key, "") for key in writing_keys}) + + + + if "${meta.model}".lower() == "boltz": + extract_boltz_results(json_files, samples, output_csv) + elif "${meta.model}".lower() == "colabfold": + extract_colabfold_results(json_files, samples, output_csv) + elif "${meta.model}".lower() == "alphafold3": + extract_alphafold3_results(json_files, samples, output_csv) + print(f"CSV file created at: {output_csv}") with open ("versions.yml", "w") as version_file: diff --git a/modules/local/run_alphafold3/Dockerfile b/modules/local/run_alphafold3/Dockerfile index 1a541f2..2f6526e 100644 --- a/modules/local/run_alphafold3/Dockerfile +++ b/modules/local/run_alphafold3/Dockerfile @@ -1,59 +1,70 @@ -FROM nvidia/cuda:12.6.0-base-ubuntu22.04 - -LABEL authors="Jose Espinosa-Carrasco" \ - title="nfcore/proteinfold_alphafold3" \ - Version="1.2.0dev" \ - description="Docker image containing all software requirements to run Alphafold3 using the nf-core/proteinfold pipeline" - +# Copyright 2024 DeepMind Technologies Limited +# +# AlphaFold 3 source code is licensed under CC BY-NC-SA 4.0. To view a copy of +# this license, visit https://creativecommons.org/licenses/by-nc-sa/4.0/ +# +# To request access to the AlphaFold 3 model parameters, follow the process set +# out at https://github.com/google-deepmind/alphafold3. You may only use these +# if received directly from Google. Use is subject to terms of use available at +# https://github.com/google-deepmind/alphafold3/blob/main/WEIGHTS_TERMS_OF_USE.md +FROM nvidia/cuda:12.6.3-base-ubuntu24.04 # Some RUN statements are combined together to make Docker build run faster. -# Get latest package listing, install software-properties-common, git and wget. -# git is required for pyproject.toml toolchain's use of CMakeLists.txt. -RUN apt update --quiet \ - && apt install --yes --quiet software-properties-common \ - && apt install --yes --quiet git wget jq \ - && rm -rf /var/lib/apt/lists/* - -# Get apt repository of specific Python versions. Then install Python. Tell APT -# this isn't an interactive TTY to avoid timezone prompt when installing. -RUN add-apt-repository ppa:deadsnakes/ppa \ - && DEBIAN_FRONTEND=noninteractive apt install --yes --quiet python3.11 python3-pip python3.11-venv python3.11-dev -RUN python3.11 -m venv /alphafold3_venv +# Get latest package listing, install python, git, wget, compilers and libs. +# * git is required for pyproject.toml toolchain's use of CMakeLists.txt. +# * gcc, g++, make are required for compiling HMMER and AlphaFold 3 libaries. +# * zlib is a required dependency of AlphaFold 3. +RUN DEBIAN_FRONTEND=noninteractive \ + apt-get update --quiet \ + && apt-get install --yes --quiet python3.12 python3-pip python3.12-venv python3.12-dev \ + && apt-get install --yes --quiet git wget gcc g++ make zlib1g-dev zstd jq +# The base image uses Python 3.12. For local installation use 3.11 or greater. +RUN python3 -m venv /alphafold3_venv ENV PATH="/hmmer/bin:/alphafold3_venv/bin:$PATH" - +# Update pip to the latest version. Not necessary in Docker, but good to do when +# this is used as a recipe for local installation since we rely on new pip +# features for secure installs. +RUN pip3 install --no-cache-dir --upgrade pip # Install HMMER. Do so before copying the source code, so that docker can cache -# the image layer containing HMMER. +# the image layer containing HMMER. Alternatively, you could also install it +# using `apt-get install hmmer` instead of bulding it from source, but we want +# to have control over the exact version of HMMER and also apply the sequence +# limit patch. Also note that eddylab.org unfortunately doesn't support HTTPS +# and the tar file published on GitHub is explicitly not recommended to be used +# for building from source. +# Download, check hash, and extract the HMMER source code. RUN mkdir /hmmer_build /hmmer ; \ wget http://eddylab.org/software/hmmer/hmmer-3.4.tar.gz --directory-prefix /hmmer_build ; \ - (cd /hmmer_build && tar zxf hmmer-3.4.tar.gz && rm hmmer-3.4.tar.gz) ; \ - (cd /hmmer_build/hmmer-3.4 && ./configure --prefix /hmmer) ; \ - (cd /hmmer_build/hmmer-3.4 && make -j8) ; \ + (cd /hmmer_build && echo "ca70d94fd0cf271bd7063423aabb116d42de533117343a9b27a65c17ff06fbf3 hmmer-3.4.tar.gz" | sha256sum --check) && \ + (cd /hmmer_build && tar zxf hmmer-3.4.tar.gz && rm hmmer-3.4.tar.gz) +# Apply the --seq_limit patch to HMMER. +COPY docker/jackhmmer_seq_limit.patch /hmmer_build/ +RUN (cd /hmmer_build && patch -p0 < jackhmmer_seq_limit.patch) +# Build HMMER. +RUN (cd /hmmer_build/hmmer-3.4 && ./configure --prefix /hmmer) ; \ + (cd /hmmer_build/hmmer-3.4 && make -j) ; \ (cd /hmmer_build/hmmer-3.4 && make install) ; \ (cd /hmmer_build/hmmer-3.4/easel && make install) ; \ rm -R /hmmer_build - -# Clone AlphaFold3 -RUN git clone https://github.com/google-deepmind/alphafold3.git /app/alphafold && \ - cd /app/alphafold && \ - git checkout 3c27a149a25b6c8930ce68cfeb2a6cbb9afb3359 && \ - cd - - -# # Install the Python dependencies AlphaFold 3 needs. -# RUN pip3 install -r dev-requirements.txt -# RUN pip3 install --no-deps . - -# Install pip packages. -RUN pip3 install --upgrade pip --no-cache-dir \ - && pip3 install -r /app/alphafold/dev-requirements.txt --no-cache-dir \ - && pip3 install --no-deps /app/alphafold/ --no-cache-dir \ +# Copy the AlphaFold 3 source code from the local machine to the container and +# set the working directory to there. +COPY . /app/alphafold +WORKDIR /app/alphafold +# Install setuptools (removed in Python 3.12) which some libraries still need. +# Then install the Python dependencies of AlphaFold 3. +RUN pip3 install --no-cache-dir setuptools \ + && pip3 install --no-cache-dir -r dev-requirements.txt \ + && pip3 install --no-cache-dir --no-deps . \ && pip3 install --no-deps biopython - -# # Build chemical components database (this binary was installed by pip). +# Build chemical components database (this binary was installed by pip). RUN build_data - # To work around a known XLA issue causing the compilation time to greatly # increase, the following environment variable setting XLA flags must be enabled -# when running AlphaFold 3: +# when running AlphaFold 3. Note that if using CUDA capability 7 GPUs, it is +# necessary to set the following XLA_FLAGS value instead: +# ENV XLA_FLAGS="--xla_disable_hlo_passes=custom-kernel-fusion-rewriter" +# (no need to disable gemm in that case as it is not supported for such GPU). ENV XLA_FLAGS="--xla_gpu_enable_triton_gemm=false" # Memory settings used for folding up to 5,120 tokens on A100 80 GB. ENV XLA_PYTHON_CLIENT_PREALLOCATE=true ENV XLA_CLIENT_MEM_FRACTION=0.95 +CMD ["python3", "run_alphafold.py"] diff --git a/modules/local/run_alphafold3/main.nf b/modules/local/run_alphafold3/main.nf index 556980e..61d8935 100644 --- a/modules/local/run_alphafold3/main.nf +++ b/modules/local/run_alphafold3/main.nf @@ -5,23 +5,17 @@ process RUN_ALPHAFOLD3 { tag "$meta.id" label 'process_medium' label 'process_gpu' - container "nf-core/proteinfold_alphafold3_standard:1.2.0dev" + container "" input: tuple val(meta), path(json) path "params/*" - path "small_bfd/*" - path "mgnify/*" - path "mmcif_files" - path "uniref90/*" - path "pdb_seqres/*" - path "uniprot/*" output: tuple val(meta), path ("publish/*alphafold3.cif") , emit: top_ranked_cif tuple val(meta), path ("publish/*ranked_*.cif") , emit: cif tuple val(meta), path ("${meta.id}_plddt.tsv") , emit: multiqc tuple val(meta), path ("${meta.id}_alphafold3_msa.tsv") , emit: msa tuple val(meta), path ("${meta.id}_0_pae.tsv") , emit: pae - tuple val(meta), path ("*_full_data_0.json") , emit: raw_pae + tuple val(meta), path ("${meta.id}/${meta.id}_confidences.json") , emit: raw_pae path "versions.yml" , emit: versions when: task.ext.when == null || task.ext.when @@ -32,21 +26,11 @@ process RUN_ALPHAFOLD3 { } def args = task.ext.args ?: '' def prefix = task.ext.prefix ?: "${meta.id}" - def af3_id = meta.id.toLowerCase() """ - if [ -f pdb_seqres/pdb_seqres.txt ] - then - sed -i "/^\\w*0/d" pdb_seqres/pdb_seqres.txt - fi python3 /app/alphafold/run_alphafold.py \\ --json_path=${json} \\ --model_dir=./params \\ - --uniref90_database_path=./uniref90/uniref90_2022_05.fa \\ - --mgnify_database_path=./mgnify/mgy_clusters_2022_05.fa \\ - --pdb_database_path=./mmcif_files \\ - --small_bfd_database_path=./small_bfd/bfd-first_non_consensus_sequences.fasta \\ - --uniprot_cluster_annot_database_path=./uniprot/uniprot_all_2021_04.fa \\ - --seqres_database_path=./pdb_seqres/pdb_seqres_2022_09_28.fasta \\ + --norun_data_pipeline \\ --output_dir=\$PWD \\ $args ## Rename the top ranked model @@ -57,18 +41,18 @@ process RUN_ALPHAFOLD3 { name=\$(jq -r '.name' ${json}) cp -n "\${name}/\${name}_model.cif" "publish/${prefix}_alphafold3.cif" # Sort the rows by ranking_score in descending order - sorted_csv=\$(head -n 1 "\${name}/ranking_scores.csv"; tail -n +2 "\${name}/ranking_scores.csv" | sort -t, -k3 -nr) + sorted_csv=\$(head -n 1 "\${name}/\${name}_ranking_scores.csv"; tail -n +2 "\${name}/\${name}_ranking_scores.csv" | sort -t, -k3 -nr) rank=0 touch publish/combined_plddt_mqc.tsv # Generate files with rank tag echo "\$sorted_csv" | tail -n +2 | while IFS=',' read -r seed sample ranking_score; do - cp -n "\${name}/seed-\${seed}_sample-\${sample}/model.cif" "publish/seed_\${seed}_sample_\${sample}_ranked_\${rank}.cif" + cp -n "\${name}/seed-\${seed}_sample-\${sample}/\${name}_seed-\${seed}_sample-\${sample}_model.cif" "publish/seed_\${seed}_sample_\${sample}_ranked_\${rank}.cif" rank=\$((rank + 1)) done extract_metrics.py --name ${prefix} \\ - --jsons ${af3_id}/${af3_id}_data.json ${af3_id}/${af3_id}_summary_confidences.json ${af3_id}/${af3_id}_confidences.json \\ + --jsons ${meta.id}/${meta.id}_data.json ${meta.id}/${meta.id}_summary_confidences.json ${meta.id}/${meta.id}_confidences.json \\ --structs publish/*ranked_*.cif - mv "${prefix}_msa.tsv" "${meta.id}_alphafold3_msa.tsv" + mv "${meta.id}_msa.tsv" "${meta.id}_alphafold3_msa.tsv" cat <<-END_VERSIONS > versions.yml "${task.process}": python: \$(python3 --version | sed 's/Python //g') diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 48e9b5a..ee1853d 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -26,6 +26,7 @@ include { COLLECT_CONFIDENCE } from '../modules/local/collect_confidence' include { paramsSummaryMap } from 'plugin/nf-schema' include { paramsSummaryMultiqc } from '../subworkflows/nf-core/utils_nfcore_pipeline' include { softwareVersionsToYAML } from '../subworkflows/nf-core/utils_nfcore_pipeline' +include { methodsDescriptionText } from '../subworkflows/local/utils_nfcore_wisps_pipeline' include { MSA } from '../subworkflows/local/msa' // @@ -70,17 +71,18 @@ workflow WISPS { ch_colabfold_params num_recycles ch_alphafold3_params // channel: path(alphafold2_params) - ch_small_bfd // channel: path(small_bfd) - ch_mgnify // channel: path(mgnify) - ch_mmcif_files // channel: path(mmcif_files) - ch_uniref90 // channel: path(uniref90) - ch_pdb_seqres // channel: path(pdb_seqres) - ch_uniprot // channel: path(uniprot) tools - + ch_multiqc_config + ch_multiqc_custom_config + ch_multiqc_logo + ch_multiqc_methods_description + outdir + main: ch_multiqc_files = Channel.empty() ch_confidence_scores = Channel.empty() + + interaction_mode = mode.split(",").collect { pair -> pair.split('-').sort().join('-') } @@ -276,7 +278,7 @@ workflow WISPS { RUN_BOLTZ.out.confidence.collect(flat: false, sort: true).multiMap{json_list -> ids: json_list.collect{it[0].id} json: json_list.collect{it[1]} - }.set{ch_confidence_scores} + }.set{ch_boltz_confidence_scores} //prepare interactions for colabfold ch_colabfold_interaction_in = Channel.empty() @@ -302,7 +304,11 @@ workflow WISPS { num_recycles ) ch_versions = ch_versions.mix(COLABFOLD_BATCH.out.versions) - + COLABFOLD_BATCH.out.top_ranked_scores.collect(flat: false, sort: true).multiMap{json_list -> + ids: json_list.collect{it[0].id} + json: json_list.collect{it[1]} + }.set{ch_colabfold_confidence_scores} + ch_alphafold3_interaction_in = Channel.empty() if ("alphafold3" in tools.split(",")){ MSA.out.json.join(ch_protein_pairs.map{it[0]}) @@ -317,15 +323,15 @@ workflow WISPS { RUN_ALPHAFOLD3 ( ch_alphafold3_interaction_in, - ch_alphafold3_params, - ch_small_bfd, - ch_mgnify, - ch_mmcif_files, - ch_uniref90, - ch_pdb_seqres, - ch_uniprot + ch_alphafold3_params ) - + ch_versions = ch_versions.mix(RUN_ALPHAFOLD3.out.versions) + + RUN_ALPHAFOLD3.out.raw_pae.collect(flat: false, sort: true).multiMap{json_list -> + ids: json_list.collect{it[0].id} + json: json_list.collect{it[1]} + }.set{ch_alphafold3_confidence_scores} + COLABFOLD_BATCH.out.top_ranked_scores .join(COLABFOLD_BATCH.out.top_ranked_pdb) @@ -359,12 +365,64 @@ workflow WISPS { ch_ipsae_in.map{it[2]} ) + ch_versions = ch_versions.mix(IPSAE.out.versions) COLLECT_CONFIDENCE( - ch_confidence_scores.ids.map{[["id": "full_run"], it]}, - ch_confidence_scores.json + ch_boltz_confidence_scores.ids + .map{[["id": "all-boltz", "model": "boltz"], it]} + .mix(ch_colabfold_confidence_scores.ids + .map{[["id": "all-colabfold", "model": "colabfold"], it]} + ) + .mix(ch_alphafold3_confidence_scores.ids + .map{[["id": "all-alphafold3", "model": "alphafold3"], it]} + ), + ch_boltz_confidence_scores.json + .mix(ch_colabfold_confidence_scores.json) + .mix(ch_alphafold3_confidence_scores.json) ) + ch_versions = ch_versions.mix(COLLECT_CONFIDENCE.out.versions) + + + // + // Collate and save software versions + // + softwareVersionsToYAML(ch_versions) + .collectFile( + storeDir: "${outdir}/pipeline_info", + name: 'nf_core_' + 'proteinfold_software_' + 'mqc_' + 'versions.yml', + sort: true, + newLine: true + ).set { ch_collated_versions } + + // + // MODULE: MultiQC + // + summary_params = paramsSummaryMap(workflow, parameters_schema: "nextflow_schema.json") + ch_workflow_summary = Channel.value(paramsSummaryMultiqc(summary_params)) + ch_methods_description = Channel.value(methodsDescriptionText(ch_multiqc_methods_description)) + + ch_multiqc_files = Channel.empty() + ch_multiqc_files = ch_multiqc_files.mix(ch_workflow_summary.collectFile(name: 'workflow_summary_mqc.yaml')) + ch_multiqc_files = ch_multiqc_files.mix(ch_methods_description.collectFile(name: 'methods_description_mqc.yaml')) + ch_multiqc_files = ch_multiqc_files.mix(ch_collated_versions) + + MULTIQC ( + COLLECT_CONFIDENCE.out.confidence.collect(flat: false, sort: true), + ch_multiqc_config.collect() + .ifEmpty([]), + ch_multiqc_custom_config + .collect() + .ifEmpty([]), + ch_multiqc_logo + .collect() + .ifEmpty([]), + [], + [] + ) + + ch_versions = ch_versions.mix(MULTIQC.out.versions) + emit: versions = ch_versions msa = RUN_BOLTZ.out.msa From 348b765538da6036372d9f46e5332cd34362e6fe Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Fri, 3 Oct 2025 13:58:55 +1000 Subject: [PATCH 06/70] update --- conf/test_gadi.config | 6 ------ modules/local/colabfold_batch/main.nf | 4 ++-- workflows/wisps.nf | 2 +- 3 files changed, 3 insertions(+), 9 deletions(-) diff --git a/conf/test_gadi.config b/conf/test_gadi.config index 4cb1c2b..96293d6 100644 --- a/conf/test_gadi.config +++ b/conf/test_gadi.config @@ -32,12 +32,6 @@ params { colabfold_alphafold2_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params/alphafold_params_colab_2022-12-06/" alphafold3_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" - alphafold3_small_bfd = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" - alphafold3_mgnify = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" - alphafold3_pdb_mmcif = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" - alphafold3_uniref90 = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" - alphafold3_pdb_seqres = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" - alphafold3_uniprot = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" use_gpu = true project = "ll61" diff --git a/modules/local/colabfold_batch/main.nf b/modules/local/colabfold_batch/main.nf index bbd5d13..4b672f1 100644 --- a/modules/local/colabfold_batch/main.nf +++ b/modules/local/colabfold_batch/main.nf @@ -58,7 +58,7 @@ process COLABFOLD_BATCH { cat <<-END_VERSIONS > versions.yml "${task.process}": - colabfold_batch: \$(conda run -n colabfold pip list | grep "^colabfold" | awk '{print \$2}') + colabfold_batch: \$(pip list | grep "^colabfold" | awk '{print \$2}') END_VERSIONS """ @@ -75,7 +75,7 @@ process COLABFOLD_BATCH { cat <<-END_VERSIONS > versions.yml "${task.process}": - colabfold_batch: \$(conda run -n colabfold pip list | grep "^colabfold" | awk '{print \$2}') + colabfold_batch: \$(pip list | grep "^colabfold" | awk '{print \$2}') END_VERSIONS """ } diff --git a/workflows/wisps.nf b/workflows/wisps.nf index ee1853d..b7bb700 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -244,7 +244,7 @@ workflow WISPS { ) .map{[it[1], it[2]]} ) - + PREPARE_INTERACTIONS( ch_boltz_data.map{[it[0][0], it[0][2].collect{it.name}]}, ch_boltz_data.map{[it[0][0], it[1].collect{it ? it.name: ""}]}, From 91bd5036650c3bffba0af7b362448420d1644eb3 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Fri, 3 Oct 2025 19:33:21 +1000 Subject: [PATCH 07/70] update batching analysis --- bin/extract_metrics.py | 246 -------------------------- bin/utils.py | 112 ------------ conf/test_gadi.config | 2 +- main.nf | 3 +- modules/local/colabfold_batch/main.nf | 30 +--- modules/local/prepare_interactions.nf | 84 +++++---- modules/local/run_alphafold3/main.nf | 29 +-- modules/local/run_boltz/main.nf | 51 +----- nextflow.config | 3 +- workflows/wisps.nf | 140 ++++++++++----- 10 files changed, 157 insertions(+), 543 deletions(-) delete mode 100755 bin/extract_metrics.py delete mode 100755 bin/utils.py diff --git a/bin/extract_metrics.py b/bin/extract_metrics.py deleted file mode 100755 index f952b21..0000000 --- a/bin/extract_metrics.py +++ /dev/null @@ -1,246 +0,0 @@ -#!/usr/bin/env python -import pickle -import os -import argparse -import json -#import torch moved to a conditional import since too bulky import if not used -import numpy as np -import csv -import string -from utils import plddt_from_struct_b_factor, get_chain_ids - -# TODO: Issue #309, make into a poper separate process, it its own module so that dependencies can be managed better -# TODO: Need a sense of ranking, so that metrics can be traced back to correct model structure, even if they're not in sequential order. The enumerates() here are not sufficient. -# Needs to be program-dependent, (see item below). -# TODO: look into have a --prog argument that could set filenames etc, logically seperate it? -# {name}_{prog}_{metric}.tsv might be easier for MultiQC to parse a complex workdir, than without the .prog -# TODO: read --prog from ${meta.model} in the NextFlow pipes. This also allows case switching in a proper EXTRACT_METRICS process. -# E.g. in main.nf of EXTACT_METRICS process, we could have: -# match ${meta.mode}: -# case 'alphafold2': -# ... -# case 'rosettafold_all_atom': -# ... -#... -# ^ overwrought with duplication, but can catch program specific weirdness, and lower barrier to adding new programs in the future. - -# TODO: Chain-wise iPTM since the relevant interface might not always be the average of all. -# Would complete Issue #308 -# Proposed format is pair-interfaces in rows, structure inference number in cols: https://github.com/nf-core/proteinfold/pull/312#issuecomment-2917709432 -# KR - changed to have both sides of the matrix, because it's not symmetrical (see comment in Issue #306) - -# Mapping of characters to integers for MSA parsing. -# 20 is for unknown characters, and 21 is for gaps. -AA_to_int = { - "A": 0, "C": 1, "D": 2, "E": 3, "F": 4, "G": 5, "H": 6, "I": 7, "K": 8, "L": 9, - "M": 10, "N": 11, "P": 12, "Q": 13, "R": 14, "S": 15, "T": 16, "V": 17, "W": 18, "Y": 19, - ".": 20, "-": 21 -} - -def a3m_to_int(a3m_file): - """ - Convert an A3M MSA representation into an integer representation (0-21). - """ - with open(a3m_file, "r") as f: - msa = f.read() - - # Convert each sequence in the MSA - int_sequences = [] - for idx, line in enumerate(msa.splitlines()): - if idx == 0 and not line.startswith(">"): # If there's an additional header (non-FASTA) skip it. E.g ColabFold - continue - - if not line.startswith(">"): # Ignore header lines - filtered_line = ''.join(char for char in line if not char.islower()) # Remove inserts (lower-case chars) in a3m - int_sequence = [AA_to_int.get(char.upper(), 20) for char in filtered_line] - int_sequences.append(int_sequence) - - int_sequences_array = np.array(int_sequences, dtype=object) - return int_sequences_array - -def format_msa_rows(msa_data): - return [[str(x) for x in val] for val in msa_data] - -def format_pae_rows(pae_data): - return [[f"{num:.4f}" for num in row] for row in pae_data] - -def format_iptm_rows(chain_pair_entries, chain_ids=None): - """ - Format iPTM data into a list of rows for writing to a TSV file. - Each row contains: the chain-pair in uppercase, e.g. "A:B", "B:A", A:C", etc. and then the iPTM value formatted to 4 decimal places. - """ - def idx_to_letter(idx): - """ Convert the index integer of the matrix to a letter representation that wraps to double representation, e.g. 0 -> A, 1 -> B, ..., 25 -> Z, 26 -> AA, 27 -> AB, etc. - This is somewhat compatible with how protein structure chain names are numbered by biochemists. - But we should move away from fixed-format PDB files -- we have nothing to lose but our chains.""" - result = "" - while idx >= 0: - result = string.ascii_uppercase[idx % 26] + result - idx = idx // 26 - 1 - if idx < 0: - break - return result - - if chain_ids: - #would be better with some model_id sorting - iptm_rows = [[""]+[f"{chain_ids[idx[0]]}:{chain_ids[idx[1]]}" for idx, val in next(iter(chain_pair_entries.values()))]] - else: - iptm_rows = [[""]+[f"{idx_to_letter(idx[0])}:{idx_to_letter(idx[1])}" for idx, val in next(iter(chain_pair_entries.values()))]] - - for model_idx, chain_pair_entries_values in chain_pair_entries.items(): - iptm_rows.append([model_idx]+[f"{val:.4f}" for idx, val in chain_pair_entries_values]) - - return [list(row) for row in zip(*iptm_rows)] - - -def chain_iptm_matrix_to_pairs(iptm_matrix): - """ - Convert a chain-wise iPTM matrix to pair values by taking off-diagonal elements. - """ - # From AlphaFold3 output docs: - # 'chain_pair_iptm': An [num_chains, num_chains] array. - # Off-diagonal element (i, j) of the array contains the ipTM restricted to tokens from chains i and j. - # Diagonal element (i, i) contains the pTM restricted to chain i. - return [(idx, val) for idx, val in np.ndenumerate(iptm_matrix) if idx[0] != idx[1]] - -def chainwise_iptm_matrix_to_ptms(iptm_matrix): - return [(idx, val) for idx, val in np.ndenumerate(iptm_matrix) if idx[0] == idx[1]] - -def write_tsv(file_path, rows): - with open(file_path, 'w') as out_f: - writer = csv.writer(out_f, delimiter='\t') - writer.writerows(rows) - -def extract_structs_plddt_to_tsv(name, structures): - """ - Write out a tsv file contain pLDDTs for reading by MultiQC in nf-core/proteinfold - Uses utils function with BioPython PDB package to extract residue pLDDT values from the b-factor column. - """ - plddt_cols = [plddt_from_struct_b_factor(structure) for structure in structures] - res_counts = [len(plddt_col) for plddt_col in plddt_cols] - - if len(set(res_counts)) != 1: - raise ValueError("Not all structures have the same number of residues!") - - rank_names = [f"rank_{i}" for i in range(len(structures))] - # Create header as the first row - plddt_rows = [["Positions"] + rank_names] - res_id_col = list(range(len(plddt_cols[0]))) - plddt_rows.extend(zip(res_id_col, *plddt_cols)) # Combine lists column-wise to make rows - write_tsv(f"{name}_plddt.tsv", plddt_rows) - -def read_pkl(name, pkl_files): - """ - Adapted from the Galaxy AlphaFold tool (https://github.com/usegalaxy-au/tools-au/blob/de94df520c8dc7b8652aedb92e90f6ebb312f95f/tools/alphafold/scripts/outputs.py), originally authored by @neoformit and @graceahall and funded by Australian Biocommons and QCIF Australia. - """ - ptm_data = {} - iptm_data = {} - for pkl_file in pkl_files: - print(f"Processing {pkl_file}") - data = pickle.load(open(pkl_file, "rb")) - - # Process MSA data - if pkl_file.endswith("final_features.pkl"): # HelixFold3 - This one must be first - write_tsv(f"{name}_msa.tsv", format_msa_rows(data["feat"]["msa"])) - elif pkl_file.endswith("features.pkl"): # AlphaFold2.3 - # TODO: AlphaFold2.3 fills end rows with 0s in AlpahFold muliter for an alanine nf-core/proteinfold Issue #300 - write_tsv(f"{name}_msa.tsv", format_msa_rows(data["msa"])) - # AlphaFold2.3 non-summary, for each pkl. TODO: Need to either read in ranking_debug.json to get the ranking order, or do it later in the workflow. - else: - model_info = os.path.basename(pkl_file).replace("result_", "").replace(".pkl", "") - #TODO: Make this explicit input - with open(os.path.join(os.path.dirname(pkl_file),"ranking_debug.json")) as f: - ranking_data = json.load(f)['order'] - model_id = ranking_data.index(model_info) - if 'predicted_aligned_error' not in data.keys(): - print(f"No PAE output in {pkl_file}, it was likely a monomer calculation") - else: - write_tsv(f"{name}_{model_id}_pae.tsv", format_pae_rows(data["predicted_aligned_error"])) - - if 'ptm' not in data.keys(): - print(f"No pTM/iPTM output in {pkl_file}, it was likely a monomer calculation") - else: - #with open(f"{name}_{model_id}_ptm.tsv", 'w') as f: - # f.write(f"{np.round(data['ptm'],3)}\n") - #with open(f"{name}_{model_id}_iptm.tsv", 'w') as f: - # f.write(f"{np.round(data['iptm'],3)}\n") - ptm_data[f"{model_id}"] = f"{np.round(data['ptm'],3)}\n" - iptm_data[f"{model_id}"] = f"{np.round(data.get('iptm',0.),3)}\n" - if ptm_data: - ptm_rows = [[k, v.strip()] for k, v in ptm_data.items()] - write_tsv(f"{name}_ptm.tsv", ptm_rows) - - if iptm_data: - iptm_rows = [[k, v.strip()] for k, v in iptm_data.items()] - write_tsv(f"{name}_iptm.tsv", iptm_rows) - - - -def read_a3m(name, a3m_files): - # RosettaFold-All-Atom - #TODO: DRY with unpaired below for Boltz - msa_rows = {} - for a3m_file in a3m_files: #Should already be alphabetical by chain - msa_rows[a3m_file] = a3m_to_int(a3m_file) - - final_rows = [] - temp_row = [] - for a3m_file in a3m_files: - temp_row.extend(msa_rows[a3m_file][0]) - final_rows.append(temp_row) - - # Un-paired TODO: get pairing code from RF-AA source - # https://github.com/baker-laboratory/RoseTTAFold-All-Atom/blob/main/rf2aa/data/parsers.py#L405 - msa_widths = [len(msa_rows[chain][0]) for chain in a3m_files] - msa_heights = [len(msa_rows[chain]) for chain in a3m_files] - - cum_total_rows = np.cumsum(msa_heights) - for row_idx in range(cum_total_rows[-1]): - temp_row = [] - - for i, chain in enumerate(a3m_files): - msa = msa_rows[chain] - width = msa_widths[i] - if i == 0: - minrow = 0 - else: - minrow = cum_total_rows[i-1] - maxrow = cum_total_rows[i] - - if minrow <= row_idx < maxrow: - msa_row_idx = row_idx - minrow - temp_row.extend(msa[msa_row_idx]) - else: - temp_row.extend(["21"] * width) #gap - final_rows.append(temp_row) - - write_tsv(f"{name}_msa.tsv", format_msa_rows(final_rows)) - -def read_npz(name, npz_files): - for idx, npz_file in enumerate(npz_files): - data = np.load(npz_file) - #Boltz PAE files if --write_full_pae is used - if npz_file.split('/')[-1].startswith('pae') and npz_file.endswith('.npz'): - model_id = os.path.basename(npz_file).split('_model_')[-1].split('.npz')[0] - write_tsv(f"{name}_{model_id}_pae.tsv", format_pae_rows(data["pae"])) - -# Boltz MSA processing -def read_csv(name, csv_files): - if not os.path.isfile(csv_files[0]): return #TODO: Fix temporary workaround - msa_rows = {} - unpaired_msa_rows = {} - for csv_file in sorted(csv_files, key=lambda x: int(x.split('_')[-1].split('.csv')[0])): - msa_lines = [] - unpaired_msa_lines = [] - with open(csv_file) as f: - f.readline() - for line in f: - if line.split(',')[0] == '-1' and len(csv_files)>1: #Server MSA appears as un-paired - unpaired_msa_lines.append(''.join(c for c in line.strip('\n').split(',')[1] if not c.islower())) - else: - msa_lines.append(''.join(c for c in line.strip('\n').split(',')[1] if not c.islower())) - msa_rows[csv_file.split('_')[-1].split('.csv')[0]] = [[str(AA_to_int.get(residue, 20)) for residue in line] for line in msa_lines] - unpaired_msa_rows[csv_file.split('_')[-1].split('.csv')[0]] = [[str(AA_to_int.get(residue, 20)) for residue in line] for line in unpaired_msa_lines] - - # Get Chain to MSA mapping (ie non-redundant for homomers) - # TODO: Make this explicit inpu... \ No newline at end of file diff --git a/bin/utils.py b/bin/utils.py deleted file mode 100755 index 60f2f1c..0000000 --- a/bin/utils.py +++ /dev/null @@ -1,112 +0,0 @@ -import importlib.util -import numpy as np -bio_is_installed = importlib.util.find_spec("Bio") is not None - -def _convert_plddt_to_100(res_plddt): - if (res_plddt < 1): # Converting to a [0,100] range - res_plddt *= 100 - return res_plddt - - -def plddt_from_struct_b_factor_adhoc(struct_file): - """ - Uses ad hoc PDB parser to extract residue pLDDT values from the b-factor column. Iterates over PDB objects rather than processes raw file - """ - #NOTE: this is a temporary hack which is not robust as a general parser. - #Should be temporary - need to check with non-protein entities - if not str(struct_file).endswith(".pdb"): - raise ValueError(f"{struct_file} must be a PDB file!") - - res_plddts = [] - resid_prev = -1 - atom_plddt_list = [] - - with open(struct_file) as f: - for line in f: - if not line.startswith('ATOM'): continue - resid = int(line[23:26].strip()) - if resid == resid_prev: - atom_plddt_list.append(float(line[61:66].strip())) - else: - if resid_prev == -1: - resid_prev = resid - continue - res_plddt = sum(atom_plddt_list)/len(atom_plddt_list) - res_plddt = _convert_plddt_to_100(res_plddt) - res_plddts.append(res_plddt) - resid_prev = resid - - # Reset atom tracking - atom_plddt_list = [] - atom_plddt_list.append(float(line[61:66].strip())) - - res_plddt = sum(atom_plddt_list)/len(atom_plddt_list) - res_plddt = _convert_plddt_to_100(res_plddt) - res_plddts.append(res_plddt) - - res_plddts = np.array(res_plddts) - res_plddts = np.round(res_plddts, 2) - - return res_plddts - -def get_chain_ids(struct_file): - from Bio import PDB - if str(struct_file).endswith(".pdb"): - parser = PDB.PDBParser(QUIET=True) - structure = parser.get_structure(id=id, file=struct_file) - elif str(struct_file).endswith(".cif"): - parser = PDB.MMCIFParser(QUIET=True) - structure = parser.get_structure(structure_id=id, filename=struct_file) - else: - raise ValueError(f"{struct_file} is neither a PDB or mmCIF file!") - - return [chain.id for chain in structure.get_chains()] - - -def plddt_from_struct_b_factor_biopython(struct_file): - """ - Uses the BioPython PDB package to extract residue pLDDT values from the b-factor column. Iterates over PDB objects rather than processes raw file - """ - from Bio import PDB - if str(struct_file).endswith(".pdb"): - parser = PDB.PDBParser(QUIET=True) - structure = parser.get_structure(id=id, file=struct_file) - elif str(struct_file).endswith(".cif"): - parser = PDB.MMCIFParser(QUIET=True) - structure = parser.get_structure(structure_id=id, filename=struct_file) - else: - raise ValueError(f"{struct_file} is neither a PDB or mmCIF file!") - -# res_list = [] - res_plddts = [] -# plddt_tot = 0 - - for model in structure: - for chain in model: - chain_res_list = chain.get_unpacked_list() -# res_list.extend(chain_res_list) - for residue in chain: - atom_list = residue.get_unpacked_list() - atom_plddt_tot = 0 - for atom in residue: # ESMFold and others have separate atom-wise values, so doing atom-wise to cover that and residue-wise - atom_plddt = atom.get_bfactor() - atom_plddt_tot += atom_plddt - - res_plddt = float(atom_plddt_tot / len(atom_list)) - - if (res_plddt < 1): # RFAA the multiplication of mean isn't failing. Anyway covering to a [0,100] range for any structure file1 - res_plddt *= 100 - res_plddt = _convert_plddt_to_100(res_plddt) - - res_plddts.append(res_plddt) -# plddt_tot += res_plddt - - res_plddts = np.array(res_plddts) - res_plddts = np.round(res_plddts, 2) - - return res_plddts - -if bio_is_installed: - plddt_from_struct_b_factor = plddt_from_struct_b_factor_biopython -else: - plddt_from_struct_b_factor = plddt_from_struct_b_factor_adhoc diff --git a/conf/test_gadi.config b/conf/test_gadi.config index 96293d6..8892cd8 100644 --- a/conf/test_gadi.config +++ b/conf/test_gadi.config @@ -83,7 +83,7 @@ process { memory: '2000.GB', time: '24.h' ] - resourceLimits = [ + resourceLimits1 = [ cpus: 16, memory: '24.GB', time: '3.h' diff --git a/main.nf b/main.nf index 291b09f..86ff548 100644 --- a/main.nf +++ b/main.nf @@ -61,7 +61,8 @@ workflow NFCORE_WISPS { ch_multiqc_custom_config, ch_multiqc_logo, ch_multiqc_methods_description, - params.outdir + params.outdir, + params.analysis_batch_size ) ch_versions = ch_versions.mix(WISPS.out.versions) diff --git a/modules/local/colabfold_batch/main.nf b/modules/local/colabfold_batch/main.nf index 4b672f1..734fc79 100644 --- a/modules/local/colabfold_batch/main.nf +++ b/modules/local/colabfold_batch/main.nf @@ -6,7 +6,7 @@ process COLABFOLD_BATCH { container "nf-core/proteinfold_colabfold:dev" input: - tuple val(meta), path(fasta) + tuple val(meta), path("alignment/*") val colabfold_model_preset path ('params/*') path ('colabfold_db/*') @@ -14,12 +14,9 @@ process COLABFOLD_BATCH { val numRec output: - tuple val(meta), path ("${meta.id}_colabfold.pdb"), emit: top_ranked_pdb - tuple val(meta), path ("*relaxed_rank_*.pdb") , emit: pdb + tuple val(meta), path ("*relaxed_rank*_model_1_*.pdb") , emit: pdb tuple val(meta), path ("*_coverage.png") , emit: msa - tuple val(meta), path ("*_mqc.png") , emit: multiqc - tuple val(meta), path ("${meta.id}_0_pae.tsv") , emit: pae - tuple val(meta), path ("${meta.id}_scores_rank_001_*.json") , emit: top_ranked_scores + tuple val(meta), path ("*_scores_rank_001_*.json") , emit: top_ranked_scores path "versions.yml" , emit: versions when: @@ -41,21 +38,9 @@ process COLABFOLD_BATCH { --num-recycle ${numRec} \\ --data \$PWD \\ --model-type ${colabfold_model_preset} \\ - ${fasta} \\ + alignment \\ \$PWD - for i in `find *.png -maxdepth 0`; do cp \$i \${i%'.png'}_mqc.png; done - if [ ! -e `find *_relaxed_rank_001_*.pdb` ]; then - cp *_relaxed_rank_001*.pdb ${meta.id}_colabfold.pdb - else - cp *_unrelaxed_rank_001*.pdb ${meta.id}_colabfold.pdb - fi - - #Note: only multimer prefix is meta.id - extract_metrics.py --name ${meta.id} \\ - --colabfold_pae *_predicted_aligned_error_v1.json - - mv *_coverage.png ${meta.id}_seq_coverage.png - + cat <<-END_VERSIONS > versions.yml "${task.process}": colabfold_batch: \$(pip list | grep "^colabfold" | awk '{print \$2}') @@ -64,15 +49,12 @@ process COLABFOLD_BATCH { stub: """ - touch ./"${meta.id}"_colabfold.pdb - touch ./"${meta.id}"_mqc.png touch ./${meta.id}_relaxed_rank_01.pdb touch ./${meta.id}_relaxed_rank_02.pdb touch ./${meta.id}_relaxed_rank_03.pdb touch ./${meta.id}_coverage.png touch ./${meta.id}_scores_rank.json - touch ./${meta.id}_0_pae.tsv - + cat <<-END_VERSIONS > versions.yml "${task.process}": colabfold_batch: \$(pip list | grep "^colabfold" | awk '{print \$2}') diff --git a/modules/local/prepare_interactions.nf b/modules/local/prepare_interactions.nf index b26693e..c8189dd 100644 --- a/modules/local/prepare_interactions.nf +++ b/modules/local/prepare_interactions.nf @@ -8,13 +8,15 @@ process PREPARE_INTERACTIONS { 'quay.io/biocontainers/python:3.8.3' }" input: - tuple val(meta), val(fasta) - tuple val(meta), val(a3m) - tuple val(meta), val(types) - path(files) + tuple val(meta), val(ids) + val(fasta) + val(a3m) + val(types) + path(files) + output: - tuple val(meta), path ("*.fasta"), emit: fasta - path "versions.yml" , emit: versions + tuple val(meta), path ("*_boltz_interaction_input.fasta"), emit: fasta + path "versions.yml" , emit: versions when: task.ext.when == null || task.ext.when @@ -26,44 +28,48 @@ process PREPARE_INTERACTIONS { #!/usr/bin/env python3 import os, sys import string + ids_batch = ${ids.collect { "\"${it}\"" }.toString()} + fasta_files_batch = ${fasta.collect { inner -> inner.collect { "\"${it}\"" }}.toString()} + a3m_files_batch = ${a3m.collect { inner -> inner.collect { "\"${it}\"" }}.toString()} + seq_types_batch = ${types.collect { inner -> inner.collect { "\"${it}\"" }}.toString()} - #single_letters = list(string.ascii_uppercase) - #two_letter_combinations = [''.join(p) for p in product(string.ascii_uppercase, repeat=2)] - #all_combinations = single_letters + two_letter_combinations all_combinations = list(string.ascii_uppercase) + list(string.ascii_lowercase) + [str(x) for x in range(0, 10)] - fasta_files = ["${fasta.join('", "')}"] - a3m_files = ["${a3m.join('", "')}"] - seq_types = ["${types.join('", "')}"] - for seq_type in seq_types: - if seq_type not in {"protein", "dna", "rna", "smiles", "ccd"}: - print(f'seqeuence type should be ["protein", "dna", "rna", "smiles", "ccd"], found {seq_type}!') - exit (1) - output_file = "${meta.id}_boltz_interaction_input.fasta" - counter = 0 - with open(output_file, "w") as outfile: - for seq_itr in range(len(seq_types)): - fasta = fasta_files[seq_itr] - a3m = a3m_files[seq_itr] - seq_type = seq_types[seq_itr] + batch_itr = 0 + for batch_itr in range(len(fasta_files_batch)): + a3m_files = a3m_files_batch[batch_itr] + seq_types = seq_types_batch[batch_itr] + fasta_files = fasta_files_batch[batch_itr] + + for seq_type in seq_types: + if seq_type not in {"protein", "dna", "rna", "smiles", "ccd"}: + print(f'seqeuence type should be ["protein", "dna", "rna", "smiles", "ccd"], found {seq_type}!') + exit (1) + output_file = ids_batch[batch_itr] + "_boltz_interaction_input.fasta" + counter = 0 + with open(output_file, "w") as outfile: + for seq_itr in range(len(seq_types)): + fasta = fasta_files[seq_itr] + a3m = a3m_files[seq_itr] + seq_type = seq_types[seq_itr] - with open(fasta, "r") as f: - lines = f.readlines() + with open(fasta, "r") as f: + lines = f.readlines() - if not lines: - continue # Skip empty FASTA files + if not lines: + continue # Skip empty FASTA files - #header = lines[0].strip() - lines[-1] = lines[-1].strip() + "\\n" - body = lines[1:] - header = f">{all_combinations[counter]}|{seq_type}" - counter += 1 - if seq_type == "protein": - header += f"|{os.path.basename(a3m)}\\n" - else: - header += "\\n" - - outfile.write(header) - outfile.writelines(body) + #header = lines[0].strip() + lines[-1] = lines[-1].strip() + "\\n" + body = lines[1:] + header = f">{all_combinations[counter]}|{seq_type}" + counter += 1 + if seq_type == "protein": + header += f"|{os.path.basename(a3m)}\\n" + else: + header += "\\n" + + outfile.write(header) + outfile.writelines(body) with open ("versions.yml", "w") as version_file: version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) diff --git a/modules/local/run_alphafold3/main.nf b/modules/local/run_alphafold3/main.nf index 61d8935..dcba10b 100644 --- a/modules/local/run_alphafold3/main.nf +++ b/modules/local/run_alphafold3/main.nf @@ -7,14 +7,11 @@ process RUN_ALPHAFOLD3 { label 'process_gpu' container "" input: - tuple val(meta), path(json) + tuple val(meta), path("data/*") path "params/*" output: tuple val(meta), path ("publish/*alphafold3.cif") , emit: top_ranked_cif tuple val(meta), path ("publish/*ranked_*.cif") , emit: cif - tuple val(meta), path ("${meta.id}_plddt.tsv") , emit: multiqc - tuple val(meta), path ("${meta.id}_alphafold3_msa.tsv") , emit: msa - tuple val(meta), path ("${meta.id}_0_pae.tsv") , emit: pae tuple val(meta), path ("${meta.id}/${meta.id}_confidences.json") , emit: raw_pae path "versions.yml" , emit: versions when: @@ -28,31 +25,13 @@ process RUN_ALPHAFOLD3 { def prefix = task.ext.prefix ?: "${meta.id}" """ python3 /app/alphafold/run_alphafold.py \\ - --json_path=${json} \\ + --input_dir=${data} \\ --model_dir=./params \\ --norun_data_pipeline \\ --output_dir=\$PWD \\ $args - ## Rename the top ranked model - if [ ! -d publish ]; then - mkdir -p publish - fi - ## Move the rest of the models and rename them according to their rank - name=\$(jq -r '.name' ${json}) - cp -n "\${name}/\${name}_model.cif" "publish/${prefix}_alphafold3.cif" - # Sort the rows by ranking_score in descending order - sorted_csv=\$(head -n 1 "\${name}/\${name}_ranking_scores.csv"; tail -n +2 "\${name}/\${name}_ranking_scores.csv" | sort -t, -k3 -nr) - rank=0 - touch publish/combined_plddt_mqc.tsv - # Generate files with rank tag - echo "\$sorted_csv" | tail -n +2 | while IFS=',' read -r seed sample ranking_score; do - cp -n "\${name}/seed-\${seed}_sample-\${sample}/\${name}_seed-\${seed}_sample-\${sample}_model.cif" "publish/seed_\${seed}_sample_\${sample}_ranked_\${rank}.cif" - rank=\$((rank + 1)) - done - extract_metrics.py --name ${prefix} \\ - --jsons ${meta.id}/${meta.id}_data.json ${meta.id}/${meta.id}_summary_confidences.json ${meta.id}/${meta.id}_confidences.json \\ - --structs publish/*ranked_*.cif - mv "${meta.id}_msa.tsv" "${meta.id}_alphafold3_msa.tsv" + + cat <<-END_VERSIONS > versions.yml "${task.process}": python: \$(python3 --version | sed 's/Python //g') diff --git a/modules/local/run_boltz/main.nf b/modules/local/run_boltz/main.nf index 581bbbc..9c24533 100644 --- a/modules/local/run_boltz/main.nf +++ b/modules/local/run_boltz/main.nf @@ -9,8 +9,8 @@ process RUN_BOLTZ { container "nf-core/proteinfold_boltz:dev" input: - tuple val(meta), path(fasta) - path (files) + tuple val(meta), path("fasta/*") + path(alignments) path ('boltz1_conf.ckpt') path ('ccd.pkl') path ('boltz2_aff.ckpt') @@ -18,39 +18,20 @@ process RUN_BOLTZ { path ('mols') output: - // TODO: rename npz into different emit channels as to not conflict with raw (.tsv) PAE etc. As in PR #306 tuple val(meta), path ("boltz_results_*/processed/msa/*.npz") , optional: true, emit: msa tuple val(meta), path ("boltz_results_*/processed/structures/*.npz") , emit: structures tuple val(meta), path ("boltz_results_*/predictions/*/confidence*.json") , emit: confidence - tuple val(meta), path ("${meta.id}_plddt.tsv") , optional: true, emit: multiqc - // TODO: support cif as well like with HelixFold3 - tuple val(meta), path ("${meta.id}_boltz.pdb") , optional: true, emit: top_ranked_pdb tuple val(meta), path ("boltz_results_*/predictions/*/*.pdb") , optional: true, emit: pdb tuple val(meta), path ("boltz_results_*/predictions/*/*model_0.cif") , optional: true, emit: cif tuple val(meta), path ("boltz_results_*/predictions/*/plddt_*model_0.npz") , emit: plddt tuple val(meta), path ("boltz_results_*/predictions/*/pae_*model_0.npz") , optional: true, emit: pae - tuple val(meta), path ("${meta.id}_plddt.tsv") , optional: true, emit: plddt_raw - tuple val(meta), path ("${meta.id}_boltz_msa.tsv") , optional: true, emit: msa_raw - tuple val(meta), path ("${meta.id}_*_pae.tsv") , optional: true, emit: pae_raw - tuple val(meta), path ("${meta.id}_ptm.tsv") , optional: true, emit: ptm_raw - tuple val(meta), path ("${meta.id}_iptm.tsv") , optional: true, emit: iptm_raw - tuple val(meta), path ("${meta.id}_chainwise_ptm.tsv") , optional: true, emit: summary_chainwise_ptm_raw - tuple val(meta), path ("${meta.id}_chainwise_iptm.tsv") , optional: true, emit: chainwise_iptm_raw - + path "versions.yml", emit: versions when: task.ext.when == null || task.ext.when script: - // Exit if running this module with -profile conda / -profile mamba - - // TODO: "boltz_results_*" dir should be be further specified using --out_dir when running Boltz, and being able to go "boltz_results_${meta.id}" instead of "boltz_results_*" - // TODO: MSA processing for Boltz is not solid yet. They can come from webserver, local mmseq, or a custom paired .csv (see docs below) - // https://github.com/jwohlwend/boltz/blob/main/docs/prediction.md#yaml-format - // TODO: what I really need to do is add a function to read /processed/msa/*.npz and convert it to a .tsv file - - // TODO: Boltz is the example to do chain-wise summary files. This will be better if model_id was properly written per prog and EXTRACT_METRICs was a process if (workflow.profile.tokenize(',').intersect(['conda', 'mamba']).size() >= 1) { error("Local RUN_BOLTZ module does not support Conda. Please use Docker / Singularity / Podman instead.") } @@ -61,22 +42,7 @@ process RUN_BOLTZ { export NUMBA_CACHE_DIR=/tmp export HOME=/tmp - boltz predict "${fasta}" ${args} --cache ./ - - if [[ "${args}" == *pdb* ]]; then - cp boltz_results_*/predictions/${meta.id}/*_0.pdb ./${meta.id}_boltz.pdb - if [ -f boltz_results_*/msa/${meta.id}_0.csv ]; then - cp boltz_results_*/msa/${meta.id}_*.csv ./ - fi - - extract_metrics.py --name ${meta.id} \\ - --structs boltz_results_*/predictions/${meta.id}/*.pdb \\ - --jsons boltz_results_*/predictions/${meta.id}/confidence_*_model_*.json \\ - --npzs boltz_results_*/predictions/${meta.id}/pae_*_model_*.npz \\ - --csvs ${meta.id}_*.csv - - mv "${meta.id}_msa.tsv" "${meta.id}_boltz_msa.tsv" - fi + boltz predict fasta ${args} --cache ./ cat <<-END_VERSIONS > versions.yml "${task.process}": @@ -99,15 +65,6 @@ process RUN_BOLTZ { touch boltz_results_${meta.id}/predictions/${meta.id}/plddt_${meta.id}_model_0.npz touch boltz_results_${meta.id}/predictions/${meta.id}/pae_${meta.id}_model_0.npz - touch "${meta.id}_boltz.pdb" - touch "${meta.id}_plddt.tsv" - touch "${meta.id}_boltz_msa.tsv" - touch "${meta.id}_0_pae.tsv" - touch "${meta.id}_0_ptm.tsv" - touch "${meta.id}_0_iptm.tsv" - touch "${meta.id}_chainwise_ptm.tsv" - touch "${meta.id}_chainwise_iptm.tsv" - cat <<-END_VERSIONS > versions.yml "${task.process}": boltz: $version diff --git a/nextflow.config b/nextflow.config index 7423d46..4b641ce 100644 --- a/nextflow.config +++ b/nextflow.config @@ -13,8 +13,9 @@ params { // Input options input = null mode = "all-all" - mmseqs_batch_size = 10 + mmseqs_batch_size = 10000 mmseqs_gpu = false + analysis_batch_size = 10000 colabfold_model_preset = "alphafold2_multimer_v3" colabfold_num_recycles = 3 diff --git a/workflows/wisps.nf b/workflows/wisps.nf index b7bb700..a863cd6 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -77,7 +77,8 @@ workflow WISPS { ch_multiqc_logo ch_multiqc_methods_description outdir - + analysis_batch_size + main: ch_multiqc_files = Channel.empty() ch_confidence_scores = Channel.empty() @@ -114,18 +115,6 @@ workflow WISPS { .unique() .set{ch_unique_pairs} - /*ch_samplesheet - .map { - if (it[1].extension == "fasta" || it[1].extension == "fa") - {it[0].cnt = getFastaSequences(it[1].text).size()} - else if (it[1].extension == "yaml" || it[1].extension == ".yml") - {it[0].cnt = getYamlSequences(it[1].text).size()} - else if (it[1].extension == "json") - {it[0].cnt = 0} - } - .set{ch_input_seqs} - */ - ch_samplesheet .combine(ch_samplesheet) .map{[ @@ -169,6 +158,7 @@ workflow WISPS { } }.unique() .set{ch_single_protein} + //ch_protein_pairs.view() MSA ( ch_protein_pairs @@ -194,11 +184,13 @@ workflow WISPS { ch_boltz_interactions_in = ch_interaction_in } + // Adding non protein for boltz ch_boltz_data = ch_boltz_data.mix(ch_boltz_interactions_in .filter{it[1][0].type != "protein" && it[1][1].type != "protein"} .map{[it, ["", ""]]} ) + // Adding single protein for boltz ch_boltz_data = ch_boltz_data.mix( ch_boltz_interactions_in .filter{[it[1][0].type, it[1][1].type].count("protein") == 1} @@ -244,30 +236,47 @@ workflow WISPS { ) .map{[it[1], it[2]]} ) + + batch_id = 0 PREPARE_INTERACTIONS( - ch_boltz_data.map{[it[0][0], it[0][2].collect{it.name}]}, - ch_boltz_data.map{[it[0][0], it[1].collect{it ? it.name: ""}]}, - ch_boltz_data.map{[it[0][0], [it[0][1][0].type, it[0][1][1].type]]}, - ch_boltz_data.map{[it[0][2][0], it[0][2][1], it[1][0], it[1][1]].findAll{it}.unique{it.toUriString()}} + ch_boltz_data + .map{it[0][0].id} + .buffer( size: analysis_batch_size, remainder: true ) + .map{ batch_id += 1; [["id" : "batch-${batch_id}"], it]}, + ch_boltz_data + .map{it[0][2].collect{it.name}} + .buffer( size: analysis_batch_size, remainder: true ), + ch_boltz_data + .map{it[1].collect{it ? it.name: ""}} + .buffer( size: analysis_batch_size, remainder: true ), + ch_boltz_data + .map{[it[0][1][0].type, it[0][1][1].type]} + .buffer( size: analysis_batch_size, remainder: true ), + ch_boltz_data + .map{[it[0][2][0], it[0][2][1], it[1][0], it[1][1]]} + .buffer( size: analysis_batch_size, remainder: true ) + .map{it.flatten()findAll{it}.unique{it.toUriString()}} + ) - //PREPARE_INTERACTIONS.out.fasta.view() - PREPARE_INTERACTIONS.out.fasta.join( - ch_boltz_data.map{[it[0][0], [it[1][0], it[1][1]].findAll{it}.unique{it.toUriString()}]} + PREPARE_INTERACTIONS.out.fasta + .map{it[1]} + .flatten() + .map{[it.baseName.replace("_boltz_interaction_input", ""), it]} + .join( + ch_boltz_data + .map{[it[0][0].id, [it[1][0], it[1][1]]]} ) - .map{ - meta = it[0].clone() - meta.model = "boltz" - [meta, it[1], it[2]] - } + .buffer( size: analysis_batch_size, remainder: true ) .set{ch_boltz_in} //ch_boltz_in.view() - + boltz_batch = 0 + RUN_BOLTZ( - ch_boltz_in.map{[it[0], it[1]]}, - ch_boltz_in.map{it[2]}, + ch_boltz_in.map{boltz_batch += 1; [["id": "batch-${boltz_batch}"], it.collect{it[1]}]}, + ch_boltz_in.map{it.collect{it[2]}.flatten().findAll{it}.unique{it.toUriString()}}, ch_boltz_model, ch_boltz_ccd, ch_boltz2_aff, @@ -275,19 +284,43 @@ workflow WISPS { ch_mols ) - RUN_BOLTZ.out.confidence.collect(flat: false, sort: true).multiMap{json_list -> + + RUN_BOLTZ.out.confidence + .map{it[1]} + .flatten() + .map{[["id": it.baseName.split("_")[1], "model": "boltz"], it]} + .view() + .set{ch_boltz_confidence} + + RUN_BOLTZ.out.pae + .map{it[1]} + .flatten() + .map{[["id": it.baseName.split("_")[1], "model": "boltz"], it]} + .set{ch_boltz_pae} + + RUN_BOLTZ.out.cif + .map{it[1]} + .flatten() + .map{[["id": it.baseName.split("_")[1], "model": "boltz"], it]} + .set{ch_boltz_cif} + + + ch_boltz_confidence + .collect(flat: false, sort: true).multiMap{json_list -> ids: json_list.collect{it[0].id} json: json_list.collect{it[1]} }.set{ch_boltz_confidence_scores} - + //prepare interactions for colabfold ch_colabfold_interaction_in = Channel.empty() if ("colabfold" in tools.split(",")){ + colabfold_batch = 0 MSA.out.a3m.join(ch_protein_pairs.map{it[0]}) + .map{it[1]} + .buffer( size: analysis_batch_size, remainder: true ) .map{ - meta = it[0].clone() - meta.model = "colabfold" - [meta, it[1]] + colabfold_batch += 1; + [["id": "batch-${colabfold_batch}"], it] } .set{ ch_colabfold_interaction_in @@ -304,11 +337,28 @@ workflow WISPS { num_recycles ) ch_versions = ch_versions.mix(COLABFOLD_BATCH.out.versions) - COLABFOLD_BATCH.out.top_ranked_scores.collect(flat: false, sort: true).multiMap{json_list -> + + COLABFOLD_BATCH.out.top_ranked_scores + .map{it[1]} + .flatten() + .map{[["id": it.baseName.split("_")[0], "model": "colabfold"], it]} + .set{ch_colabfold_scores} + + COLABFOLD_BATCH.out.pdb + .map{it[1]} + .flatten() + .map{[["id": it.baseName.split("_")[0], "model": "colabfold"], it]} + .set{ch_colabfold_pdb} + + + ch_colabfold_scores + .collect(flat: false, sort: true).multiMap{json_list -> ids: json_list.collect{it[0].id} json: json_list.collect{it[1]} }.set{ch_colabfold_confidence_scores} + + ch_alphafold3_interaction_in = Channel.empty() if ("alphafold3" in tools.split(",")){ MSA.out.json.join(ch_protein_pairs.map{it[0]}) @@ -327,37 +377,38 @@ workflow WISPS { ) ch_versions = ch_versions.mix(RUN_ALPHAFOLD3.out.versions) + RUN_ALPHAFOLD3.out.raw_pae.collect(flat: false, sort: true).multiMap{json_list -> ids: json_list.collect{it[0].id} json: json_list.collect{it[1]} }.set{ch_alphafold3_confidence_scores} - COLABFOLD_BATCH.out.top_ranked_scores - .join(COLABFOLD_BATCH.out.top_ranked_pdb) + ch_colabfold_scores + .join(ch_colabfold_pdb) .map{[["id": it[0].id], it, []]} .join(ch_interaction_in .filter{it[1][0].type == "protein" || it[1][1].type == "protein"} .map{["id": it[0].id]} ) .mix( - RUN_BOLTZ.out.pae - .join(RUN_BOLTZ.out.cif) - .join(RUN_BOLTZ.out.confidence) + ch_boltz_pae + .join(ch_boltz_cif) + .join(ch_boltz_confidence) .map{[["id": it[0].id], [it[0], it[1], it[2]], it[3]]} .join(ch_interaction_in .filter{it[1][0].type == "protein" || it[1][1].type == "protein"} .map{["id": it[0].id]} ) ) - .mix( + /*.mix( RUN_ALPHAFOLD3.out.pae.join(RUN_ALPHAFOLD3.out.top_ranked_cif) .map{[["id": it[0].id], it, []]} .join(ch_interaction_in .filter{it[1][0].type == "protein" || it[1][1].type == "protein"} .map{["id": it[0].id]} ) - ) + )*/ .set{ch_ipsae_in} IPSAE( @@ -425,10 +476,5 @@ workflow WISPS { emit: versions = ch_versions - msa = RUN_BOLTZ.out.msa - structures = RUN_BOLTZ.out.structures - confidence = RUN_BOLTZ.out.confidence - run_confidence = COLLECT_CONFIDENCE.out.confidence - plddt = RUN_BOLTZ.out.plddt - pdb = RUN_BOLTZ.out.pdb + } From 2894b937db26e0ae0c5a9322e209da94f92c5116 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Fri, 3 Oct 2025 21:30:49 +1000 Subject: [PATCH 08/70] adding statistics --- modules/local/collect_confidence.nf | 1 + 1 file changed, 1 insertion(+) diff --git a/modules/local/collect_confidence.nf b/modules/local/collect_confidence.nf index 95223c1..d36c20e 100644 --- a/modules/local/collect_confidence.nf +++ b/modules/local/collect_confidence.nf @@ -26,6 +26,7 @@ process COLLECT_CONFIDENCE { import os, sys import json import csv + import statistics # Folder containing the JSON files output_csv = "${meta.model}_confidence_scores_full.csv" From 05a7ba6c8e1124c83a9e737299db9dffe86b46eb Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Fri, 3 Oct 2025 21:32:12 +1000 Subject: [PATCH 09/70] adding af3 container --- modules/local/run_alphafold3/main.nf | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/modules/local/run_alphafold3/main.nf b/modules/local/run_alphafold3/main.nf index dcba10b..11e9e91 100644 --- a/modules/local/run_alphafold3/main.nf +++ b/modules/local/run_alphafold3/main.nf @@ -5,7 +5,7 @@ process RUN_ALPHAFOLD3 { tag "$meta.id" label 'process_medium' label 'process_gpu' - container "" + container "quay.io/nf-core/proteinfold_alphafold3_standard:2.1.0dev" input: tuple val(meta), path("data/*") path "params/*" From 96f97e06859fcb7740315f92de0dd466fb4be540 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Sat, 4 Oct 2025 18:12:24 +1000 Subject: [PATCH 10/70] update batching --- modules/local/msa_manager/split_msa.nf | 8 ++++++- workflows/wisps.nf | 32 ++++++++++++++++---------- 2 files changed, 27 insertions(+), 13 deletions(-) diff --git a/modules/local/msa_manager/split_msa.nf b/modules/local/msa_manager/split_msa.nf index c7f7b4d..db74af4 100644 --- a/modules/local/msa_manager/split_msa.nf +++ b/modules/local/msa_manager/split_msa.nf @@ -20,7 +20,13 @@ process SPLIT_MSA { def args = task.ext.args ?: '' """ - msa_manager.py ${msa} -o output_msa --meta_id ${meta.id} + files=(${msa.collect { "\"${it}\"" }.join(" ")}) + + for f in "\${files[@]}"; do + meta_id=\$(basename "\$f") + msa_manager.py \$f -o output_msa --meta_id "\${meta_id}" + done + cat <<-END_VERSIONS > versions.yml "${task.process}": diff --git a/workflows/wisps.nf b/workflows/wisps.nf index a863cd6..7f2cec0 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -210,24 +210,31 @@ workflow WISPS { [it[1], ["", it[3]]] } ) - + split_batch_id = 0 SPLIT_MSA( - ch_split_msa_in.join(ch_protein_pairs.map{it[0]}) + ch_split_msa_in + .map{it[1]} + .buffer( size: mmseqs_batch_size, remainder: true ) + .map{ split_batch_id += 1; [["id" : "batch-${split_batch_id}"], it]} ) ch_versions = ch_versions.mix(SPLIT_MSA.out.versions) - ch_boltz_data = ch_boltz_data.mix(ch_boltz_interactions_in + SPLIT_MSA.out.msa_csv + .map{it[1]} + .flatten() + .map{[["id" : it.baseName.split("_")[0]], it]} + .groupTuple(sort: true) + .set{ch_split_msa_out} + + ch_boltz_data = ch_boltz_data + .mix(ch_boltz_interactions_in .filter{it[1][0].type == "protein" && it[1][1].type == "protein"} .map{[["id": it[0].id], it]} .join( - SPLIT_MSA.out.msa_csv + ch_split_msa_out .map{ - if (it[1] instanceof List){ - if (it[1].size() != 2){ - log.warn "Something wrong with the data expected 2 csv!" - } - }else{ + if (it[1].size() == 1){ it[1] = [it[1], it[1]] } it @@ -289,7 +296,6 @@ workflow WISPS { .map{it[1]} .flatten() .map{[["id": it.baseName.split("_")[1], "model": "boltz"], it]} - .view() .set{ch_boltz_confidence} RUN_BOLTZ.out.pae @@ -457,9 +463,11 @@ workflow WISPS { ch_multiqc_files = ch_multiqc_files.mix(ch_workflow_summary.collectFile(name: 'workflow_summary_mqc.yaml')) ch_multiqc_files = ch_multiqc_files.mix(ch_methods_description.collectFile(name: 'methods_description_mqc.yaml')) ch_multiqc_files = ch_multiqc_files.mix(ch_collated_versions) - + ch_multiqc_files = ch_multiqc_files + .mix(COLLECT_CONFIDENCE.out.confidence.map{it[1]}) + //ch_multiqc_files.view() MULTIQC ( - COLLECT_CONFIDENCE.out.confidence.collect(flat: false, sort: true), + ch_multiqc_files.collect(sort: true), ch_multiqc_config.collect() .ifEmpty([]), ch_multiqc_custom_config From 5d3fd40c919c29eb9b6d3658e859f5d898753211 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Mon, 6 Oct 2025 10:31:21 +1100 Subject: [PATCH 11/70] update batching --- workflows/wisps.nf | 14 ++++++++------ 1 file changed, 8 insertions(+), 6 deletions(-) diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 7f2cec0..6d4bebc 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -364,15 +364,17 @@ workflow WISPS { }.set{ch_colabfold_confidence_scores} - + af3_batch = 0 ch_alphafold3_interaction_in = Channel.empty() if ("alphafold3" in tools.split(",")){ - MSA.out.json.join(ch_protein_pairs.map{it[0]}) + MSA.out.a3m.join(ch_protein_pairs.map{it[0]}) + .map{it[1]} + .buffer( size: analysis_batch_size, remainder: true ) .map{ - meta = it[0].clone() - meta.model = "alphafold3" - [meta, it[1]]} - .set{ + af3_batch += 1; + [["id": "batch-${af3_batch}"], it] + } + .set{ ch_alphafold3_interaction_in } } From 098d132c0464c9ffdb356be42963da80cee92d0e Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Mon, 6 Oct 2025 16:11:31 +1100 Subject: [PATCH 12/70] fix boltz output names --- modules/local/colabfold_batch/main.nf | 8 ++++---- modules/local/run_alphafold3/main.nf | 24 +++++++++------------- workflows/wisps.nf | 29 +++++++++++++++++++++------ 3 files changed, 36 insertions(+), 25 deletions(-) diff --git a/modules/local/colabfold_batch/main.nf b/modules/local/colabfold_batch/main.nf index 734fc79..82f9513 100644 --- a/modules/local/colabfold_batch/main.nf +++ b/modules/local/colabfold_batch/main.nf @@ -49,11 +49,11 @@ process COLABFOLD_BATCH { stub: """ - touch ./${meta.id}_relaxed_rank_01.pdb - touch ./${meta.id}_relaxed_rank_02.pdb - touch ./${meta.id}_relaxed_rank_03.pdb + touch ./${meta.id}_relaxed_rank_model_1_00.pdb + touch ./${meta.id}_relaxed_rank_model_2_00.pdb + touch ./${meta.id}_relaxed_rank_model_3_00.pdb touch ./${meta.id}_coverage.png - touch ./${meta.id}_scores_rank.json + touch ./${meta.id}_scores_rank_001_00.json cat <<-END_VERSIONS > versions.yml "${task.process}": diff --git a/modules/local/run_alphafold3/main.nf b/modules/local/run_alphafold3/main.nf index 11e9e91..2726361 100644 --- a/modules/local/run_alphafold3/main.nf +++ b/modules/local/run_alphafold3/main.nf @@ -10,9 +10,9 @@ process RUN_ALPHAFOLD3 { tuple val(meta), path("data/*") path "params/*" output: - tuple val(meta), path ("publish/*alphafold3.cif") , emit: top_ranked_cif - tuple val(meta), path ("publish/*ranked_*.cif") , emit: cif - tuple val(meta), path ("${meta.id}/${meta.id}_confidences.json") , emit: raw_pae + tuple val(meta), path ("out/*/_model.cif") , emit: top_ranked_cif + tuple val(meta), path ("out/*/*_confidences.json") , emit: confidence + tuple val(meta), path ("out/*/*_summary_confidences.json") , emit: summary_confidences path "versions.yml" , emit: versions when: task.ext.when == null || task.ext.when @@ -28,28 +28,22 @@ process RUN_ALPHAFOLD3 { --input_dir=${data} \\ --model_dir=./params \\ --norun_data_pipeline \\ - --output_dir=\$PWD \\ + --output_dir=out/ \\ $args - cat <<-END_VERSIONS > versions.yml "${task.process}": python: \$(python3 --version | sed 's/Python //g') END_VERSIONS """ + stub: def prefix = task.ext.prefix ?: "${meta.id}" """ - mkdir publish - touch publish/${prefix}_alphafold3.cif - touch publish/${prefix}_ranked_1.cif - touch publish/${prefix}_ranked_2.cif - touch publish/${prefix}_ranked_3.cif - touch publish/${prefix}_ranked_4.cif - touch publish/${prefix}_ranked_5.cif - touch ${prefix}_plddt.tsv - touch ${prefix}_alphafold3_msa.tsv - touch ${prefix}_0_pae.tsv + mkdir out + touch out/${prefix}_model.cif + touch out/${prefix}_confidences.json + touch out/${prefix}_summary_confidences.json cat <<-END_VERSIONS > versions.yml "${task.process}": python: \$(python3 --version | sed 's/Python //g') diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 6d4bebc..1fb3cd8 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -307,10 +307,9 @@ workflow WISPS { RUN_BOLTZ.out.cif .map{it[1]} .flatten() - .map{[["id": it.baseName.split("_")[1], "model": "boltz"], it]} + .map{[["id": it.baseName.split("_")[0], "model": "boltz"], it]} .set{ch_boltz_cif} - ch_boltz_confidence .collect(flat: false, sort: true).multiMap{json_list -> ids: json_list.collect{it[0].id} @@ -385,8 +384,26 @@ workflow WISPS { ) ch_versions = ch_versions.mix(RUN_ALPHAFOLD3.out.versions) + RUN_ALPHAFOLD3.out.top_ranked_cif + .map{it[1]} + .flatten() + .map{[["id": it.baseName.split("_")[0], "model": "alphafold3"], it]} + .set{ch_alphafold3_cif} + + RUN_ALPHAFOLD3.out.confidence + .map{it[1]} + .flatten() + .map{[["id": it.baseName.split("_")[0], "model": "alphafold3"], it]} + .set{ch_alphafold3_confidence} - RUN_ALPHAFOLD3.out.raw_pae.collect(flat: false, sort: true).multiMap{json_list -> + RUN_ALPHAFOLD3.out.summary_confidences + .map{it[1]} + .flatten() + .map{[["id": it.baseName.split("_")[0], "model": "alphafold3"], it]} + .set{ch_alphafold3_summary_confidences} + + + ch_alphafold3_summary_confidences.collect(flat: false, sort: true).multiMap{json_list -> ids: json_list.collect{it[0].id} json: json_list.collect{it[1]} }.set{ch_alphafold3_confidence_scores} @@ -409,14 +426,14 @@ workflow WISPS { .map{["id": it[0].id]} ) ) - /*.mix( - RUN_ALPHAFOLD3.out.pae.join(RUN_ALPHAFOLD3.out.top_ranked_cif) + .mix( + ch_alphafold3_confidence.join(ch_alphafold3_cif) .map{[["id": it[0].id], it, []]} .join(ch_interaction_in .filter{it[1][0].type == "protein" || it[1][1].type == "protein"} .map{["id": it[0].id]} ) - )*/ + ) .set{ch_ipsae_in} IPSAE( From d61b0c8f9e17e9300f883ebba178013fa4392922 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Mon, 6 Oct 2025 17:48:38 +1100 Subject: [PATCH 13/70] fix minor issues --- modules/local/msa_manager/split_msa.nf | 2 +- modules/local/run_alphafold3/main.nf | 2 +- workflows/wisps.nf | 15 ++++++++++----- 3 files changed, 12 insertions(+), 7 deletions(-) diff --git a/modules/local/msa_manager/split_msa.nf b/modules/local/msa_manager/split_msa.nf index db74af4..dad42e5 100644 --- a/modules/local/msa_manager/split_msa.nf +++ b/modules/local/msa_manager/split_msa.nf @@ -23,7 +23,7 @@ process SPLIT_MSA { files=(${msa.collect { "\"${it}\"" }.join(" ")}) for f in "\${files[@]}"; do - meta_id=\$(basename "\$f") + meta_id=\$(basename "\$f" ".a3m") msa_manager.py \$f -o output_msa --meta_id "\${meta_id}" done diff --git a/modules/local/run_alphafold3/main.nf b/modules/local/run_alphafold3/main.nf index 2726361..c82ecb6 100644 --- a/modules/local/run_alphafold3/main.nf +++ b/modules/local/run_alphafold3/main.nf @@ -25,7 +25,7 @@ process RUN_ALPHAFOLD3 { def prefix = task.ext.prefix ?: "${meta.id}" """ python3 /app/alphafold/run_alphafold.py \\ - --input_dir=${data} \\ + --input_dir=data/ \\ --model_dir=./params \\ --norun_data_pipeline \\ --output_dir=out/ \\ diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 1fb3cd8..19d177c 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -61,10 +61,10 @@ workflow WISPS { ch_versions // channel: [ path(versions.yml) ] ch_boltz_ccd // channel: [ path(boltz_ccd) ] ch_boltz_model // channel: [ path(model) ] - ch_colabfold_db // channel: [ path(colabfold_db) ] ch_boltz2_aff // channel: [ path(boltz2_aff) ] ch_boltz2_conf // channel: [ path(boltz2_conf) ] ch_mols // channel: [ path(mols) ] + ch_colabfold_db // channel: [ path(colabfold_db) ] ch_uniref30 // channel: [ path(uniref30) ] mmseqs_batch_size // number colabfold_model_preset @@ -215,7 +215,7 @@ workflow WISPS { ch_split_msa_in .map{it[1]} .buffer( size: mmseqs_batch_size, remainder: true ) - .map{ split_batch_id += 1; [["id" : "batch-${split_batch_id}"], it]} + .map{ split_batch_id += 1; [["id" : "batch-${split_batch_id}-${it.size()}"], it]} ) ch_versions = ch_versions.mix(SPLIT_MSA.out.versions) @@ -250,7 +250,7 @@ workflow WISPS { ch_boltz_data .map{it[0][0].id} .buffer( size: analysis_batch_size, remainder: true ) - .map{ batch_id += 1; [["id" : "batch-${batch_id}"], it]}, + .map{ batch_id += 1; [["id" : "batch-${batch_id}-${it.size()}"], it]}, ch_boltz_data .map{it[0][2].collect{it.name}} .buffer( size: analysis_batch_size, remainder: true ), @@ -282,7 +282,7 @@ workflow WISPS { boltz_batch = 0 RUN_BOLTZ( - ch_boltz_in.map{boltz_batch += 1; [["id": "batch-${boltz_batch}"], it.collect{it[1]}]}, + ch_boltz_in.map{boltz_batch += 1; [["id": "batch-${boltz_batch}-${it.size()}"], it.collect{it[1]}]}, ch_boltz_in.map{it.collect{it[2]}.flatten().findAll{it}.unique{it.toUriString()}}, ch_boltz_model, ch_boltz_ccd, @@ -371,7 +371,7 @@ workflow WISPS { .buffer( size: analysis_batch_size, remainder: true ) .map{ af3_batch += 1; - [["id": "batch-${af3_batch}"], it] + [["id": "batch-${af3_batch}-${it.size()}"], it] } .set{ ch_alphafold3_interaction_in @@ -408,6 +408,11 @@ workflow WISPS { json: json_list.collect{it[1]} }.set{ch_alphafold3_confidence_scores} + ch_boltz_pae + .join(ch_boltz_cif) + .join(ch_boltz_confidence) + .map{["id": it[0].id]} + .view() ch_colabfold_scores .join(ch_colabfold_pdb) From 0c52e7f6df5a3a6836a4b628619e4bda401705ff Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Mon, 6 Oct 2025 17:49:24 +1100 Subject: [PATCH 14/70] fix minor --- workflows/wisps.nf | 5 ----- 1 file changed, 5 deletions(-) diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 19d177c..f645389 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -408,11 +408,6 @@ workflow WISPS { json: json_list.collect{it[1]} }.set{ch_alphafold3_confidence_scores} - ch_boltz_pae - .join(ch_boltz_cif) - .join(ch_boltz_confidence) - .map{["id": it[0].id]} - .view() ch_colabfold_scores .join(ch_colabfold_pdb) From b9b452091963e327b46e3b9e8cb445b2e7f80d16 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Mon, 6 Oct 2025 18:01:37 +1100 Subject: [PATCH 15/70] fix minor for channel --- modules/local/run_alphafold3/main.nf | 2 +- workflows/wisps.nf | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/modules/local/run_alphafold3/main.nf b/modules/local/run_alphafold3/main.nf index c82ecb6..becd1be 100644 --- a/modules/local/run_alphafold3/main.nf +++ b/modules/local/run_alphafold3/main.nf @@ -10,7 +10,7 @@ process RUN_ALPHAFOLD3 { tuple val(meta), path("data/*") path "params/*" output: - tuple val(meta), path ("out/*/_model.cif") , emit: top_ranked_cif + tuple val(meta), path ("out/*/*_model.cif") , emit: top_ranked_cif tuple val(meta), path ("out/*/*_confidences.json") , emit: confidence tuple val(meta), path ("out/*/*_summary_confidences.json") , emit: summary_confidences path "versions.yml" , emit: versions diff --git a/workflows/wisps.nf b/workflows/wisps.nf index f645389..7129a75 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -366,7 +366,7 @@ workflow WISPS { af3_batch = 0 ch_alphafold3_interaction_in = Channel.empty() if ("alphafold3" in tools.split(",")){ - MSA.out.a3m.join(ch_protein_pairs.map{it[0]}) + MSA.out.json.join(ch_protein_pairs.map{it[0]}) .map{it[1]} .buffer( size: analysis_batch_size, remainder: true ) .map{ From ab0a1d1d4841119e9ba1d108d8f6814c94a0559a Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Mon, 6 Oct 2025 21:56:06 +1100 Subject: [PATCH 16/70] fix file naming --- workflows/wisps.nf | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 7129a75..07ebd90 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -235,7 +235,7 @@ workflow WISPS { ch_split_msa_out .map{ if (it[1].size() == 1){ - it[1] = [it[1], it[1]] + it[1] = [it[1][0], it[1][0]] } it } From d9eee22ac4fed4ce2fd9c14be2f8d0b43507024b Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Mon, 6 Oct 2025 23:02:44 +1100 Subject: [PATCH 17/70] update --- assets/schema_input.json | 6 +-- docs/usage.md | 37 +++++----------- nextflow_schema.json | 93 +++++++++++++++++++++++++++++++++++----- workflows/wisps.nf | 30 +++++-------- 4 files changed, 107 insertions(+), 59 deletions(-) diff --git a/assets/schema_input.json b/assets/schema_input.json index bcc9839..c57b0e9 100644 --- a/assets/schema_input.json +++ b/assets/schema_input.json @@ -13,12 +13,12 @@ "errorMessage": "Sequence name must be provided and cannot contain spaces", "meta": ["id"] }, - "fasta": { + "sequence": { "type": "string", "format": "file-path", "exists": true, "pattern": "^\\S+\\.fa(sta)?$", - "errorMessage": "Fasta file must be provided, cannot contain spaces and must have extension '.fa' or '.fasta'" + "errorMessage": "Fasta/YAML file must be provided, cannot contain spaces and must have extension '.fa' or '.fasta'" }, "type": { "type": "string", @@ -33,6 +33,6 @@ "default": "all" } }, - "required": ["id", "fasta"] + "required": ["id", "sequence"] } } diff --git a/docs/usage.md b/docs/usage.md index fccfd1c..d4d02ac 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -16,39 +16,23 @@ You will need to create a samplesheet with information about the samples you wou --input '[path to samplesheet file]' ``` -### Multiple runs of the same sample - -The `sample` identifiers have to be the same when you have re-sequenced the same sample more than once e.g. to increase sequencing depth. The pipeline will concatenate the raw reads before performing any downstream analysis. Below is an example for the same sample sequenced across 3 lanes: - -```csv title="samplesheet.csv" -sample,fastq_1,fastq_2 -CONTROL_REP1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz -CONTROL_REP1,AEG588A1_S1_L003_R1_001.fastq.gz,AEG588A1_S1_L003_R2_001.fastq.gz -CONTROL_REP1,AEG588A1_S1_L004_R1_001.fastq.gz,AEG588A1_S1_L004_R2_001.fastq.gz -``` - ### Full samplesheet -The pipeline will auto-detect whether a sample is single- or paired-end using the information provided in the samplesheet. The samplesheet can have as many columns as you desire, however, there is a strict requirement for the first 3 columns to match those defined in the table below. - -A final samplesheet file consisting of both single- and paired-end data may look something like the one below. This is for 6 samples, where `TREATMENT_REP3` has been sequenced twice. +An example of the sample sheet used for the pipeline is shown below: ```csv title="samplesheet.csv" -sample,fastq_1,fastq_2 -CONTROL_REP1,AEG588A1_S1_L002_R1_001.fastq.gz,AEG588A1_S1_L002_R2_001.fastq.gz -CONTROL_REP2,AEG588A2_S2_L002_R1_001.fastq.gz,AEG588A2_S2_L002_R2_001.fastq.gz -CONTROL_REP3,AEG588A3_S3_L002_R1_001.fastq.gz,AEG588A3_S3_L002_R2_001.fastq.gz -TREATMENT_REP1,AEG588A4_S4_L003_R1_001.fastq.gz, -TREATMENT_REP2,AEG588A5_S5_L003_R1_001.fastq.gz, -TREATMENT_REP3,AEG588A6_S6_L003_R1_001.fastq.gz, -TREATMENT_REP3,AEG588A6_S6_L004_R1_001.fastq.gz, +id,sequence,group,type +S1,S1.fasta,A,protein +S2,Sample2.fasta,B,protein +S3,S3.yaml,A,rna ``` | Column | Description | | --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `sample` | Custom sample name. This entry will be identical for multiple sequencing libraries/runs from the same sample. Spaces in sample names are automatically converted to underscores (`_`). | -| `fastq_1` | Full path to FastQ file for Illumina short reads 1. File has to be gzipped and have the extension ".fastq.gz" or ".fq.gz". | -| `fastq_2` | Full path to FastQ file for Illumina short reads 2. File has to be gzipped and have the extension ".fastq.gz" or ".fq.gz". | +| `id` | The `id` identifiers have to be unique in the sample sheet and **must not** have an underscore (`_`). | +| `sequence` | Full path to Fasta/YAML file for sample seqeuence. File has to have the extension ".fasta", ".fa" or "yaml". | +| `type` | The sequence type, can be either protein, rna . It is an optional column, by default it will be consdred as protein. | +| `group` | it is a way to group samnples to create custom interactions. It is an optional column, if not provided, the inteactions will be `aa-all' which means all sample against all samples. | An [example samplesheet](../assets/samplesheet.csv) has been provided with the pipeline. @@ -57,7 +41,7 @@ An [example samplesheet](../assets/samplesheet.csv) has been provided with the p The typical command for running the pipeline is as follows: ```bash -nextflow run nf-core/wisps --input ./samplesheet.csv --outdir ./results --genome GRCh37 -profile docker +nextflow run nf-core/wisps --input ./samplesheet.csv --outdir ./results -profile docker ``` This will launch the pipeline with the `docker` configuration profile. See below for more information about profiles. @@ -90,7 +74,6 @@ with: ```yaml title="params.yaml" input: './samplesheet.csv' outdir: './results/' -genome: 'GRCh37' <...> ``` diff --git a/nextflow_schema.json b/nextflow_schema.json index e59345f..7625b99 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -31,19 +31,38 @@ }, "mode": { "type": "string", - "default": "alphafold2", - "description": "Specifies the mode in which the pipeline will be run. mode can be any combination of ['alphafold2', 'alphafold3', 'colabfold', 'esmfold', 'rosettafold_all_atom', 'boltz', 'helixfold3'] separated by a comma (',') with no spaces.", + "default": "all-all", + "description": "Specifies the interactions to be created. You can use all-all, or group-group using teh group column in the samplesheet. You can use mu;ltiple group-group separated by a comma (',') with no spaces.", "fa_icon": "fas fa-cogs", - "errorMessage": "Mode must be a comma-separated list containing any combination of 'alphafold2', 'alphafold3', 'colabfold', 'esmfold', 'rosettafold_all_atom', 'boltz', or 'helixfold3' with no spaces." + "errorMessage": "Check the documenation for more details on this." }, - "mmseq_batch_size": { + "tools": { + "type": "string", + "default": "boltz,colabfold", + "description": "Specifies the models to be run. tools can be any combination of ['alphafold3', 'colabfold', 'boltz'] separated by a comma (',') with no spaces.", + "fa_icon": "fas fa-cogs", + "errorMessage": "Tools must be a comma-separated list containing any combination of 'alphafold3', 'colabfold', or 'boltz' with no spaces." + }, + "mmseqs_batch_size": { "type": "integer", + "default": 10000, "description": "Number of samples in each mmseq run (batching leads to higher performance time in total.)", "fa_icon": "fas fa-microchip" }, + "analysis_batch_size": { + "type": "integer", + "default": 10000, + "description": "Number of samples to be processes in teh analysis after multiple single alignment", + "fa_icon": "fas fa-microchip" + }, "use_gpu": { "type": "boolean", - "description": "Run on CPUs (default) or GPUs", + "description": "Run on CPUs (default) or GPUs for the models", + "fa_icon": "fas fa-microchip" + }, + "mmseqs_gpu": { + "type": "boolean", + "description": "Run mmseqs on CPUs (default) or GPUs", "fa_icon": "fas fa-microchip" }, "email": { @@ -60,7 +79,7 @@ } } }, - "dbs_options": { + "dbs_weights_ptions": { "title": "Databases options", "type": "object", "fa_icon": "fas fa-terminal", @@ -119,19 +138,68 @@ "default": "null/params/boltz2_aff.ckpt", "description": "Path to boltz affinity file" }, - "boltz2_conf_path": { + "boltz2_conf": { "type": "string", "default": "null/params/boltz2_conf.ckpt", "description": "Path to boltz-2 conf file" }, - "boltz2_mols_path": { + "boltz2_mols": { "type": "string", "default": "null/params/mols/", "description": "Path to boltz-2 mols" + }, + "alphafold3_params": { + "type": "string", + "default": "null/params//", + "description": "Path to Alphafold3 params" } } }, - + "models_options": { + "title": "Models options", + "type": "object", + "fa_icon": "fas fa-terminal", + "description": "Customise all parameters for the models.", + "required": [], + "properties": { + "colabfold_num_recycles": { + "type": "integer", + "default": 3, + "description": "Number of recycles for ColabFold", + "fa_icon": "fas fa-recycle", + "minimum": 1, + "maximum": 20, + "errorMessage": "Number of recycles must be a whole number between 1 and 20" + }, + "colabfold_model_preset": { + "type": "string", + "default": "alphafold2_multimer_v3", + "description": "Model preset for 'colabfold' mode", + "enum": [ + "alphafold2_ptm", + "alphafold2_multimer_v1", + "alphafold2_multimer_v2", + "alphafold2_multimer_v3" + ], + "fa_icon": "fas fa-stream" + }, + "ipsae_pae_cutoff": { + "type": "integer", + "default": 10, + "description": "The pae cutoff for ipsae.", + "fa_icon": "fas fa-recycle", + "errorMessage": "The pae cutoff for ipsae." + },"ipsae_dist_cutoff": { + "type": "integer", + "default": 10, + "description": "The dist cutoff for ipsae.", + "fa_icon": "fas fa-recycle", + "errorMessage": "" + } + + + } + }, "institutional_config_options": { "title": "Institutional config options", "type": "object", @@ -276,7 +344,12 @@ { "$ref": "#/$defs/input_output_options" }, - + { + "$ref": "#/$defs/dbs_weights_ptions" + }, + { + "$ref": "#/$defs/models_options" + }, { "$ref": "#/$defs/institutional_config_options" }, diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 07ebd90..75b4d1a 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -56,21 +56,21 @@ include { getYamlSequences } from '../subworkflows/local/msa' workflow WISPS { take: - ch_samplesheet // channel: samplesheet read from --input + ch_samplesheet mode - ch_versions // channel: [ path(versions.yml) ] - ch_boltz_ccd // channel: [ path(boltz_ccd) ] - ch_boltz_model // channel: [ path(model) ] - ch_boltz2_aff // channel: [ path(boltz2_aff) ] - ch_boltz2_conf // channel: [ path(boltz2_conf) ] - ch_mols // channel: [ path(mols) ] - ch_colabfold_db // channel: [ path(colabfold_db) ] - ch_uniref30 // channel: [ path(uniref30) ] - mmseqs_batch_size // number + ch_versions + ch_boltz_ccd + ch_boltz_model + ch_boltz2_aff + ch_boltz2_conf + ch_mols + ch_colabfold_db + ch_uniref30 + mmseqs_batch_size colabfold_model_preset ch_colabfold_params num_recycles - ch_alphafold3_params // channel: path(alphafold2_params) + ch_alphafold3_params tools ch_multiqc_config ch_multiqc_custom_config @@ -130,8 +130,6 @@ workflow WISPS { .join(ch_unique_pairs) .set{ch_interaction_in} - //ch_interaction_in.view() - ch_interaction_in .filter{it[1][0].type == "protein" && it[1][1].type == "protein"} .collectFile{ @@ -171,9 +169,6 @@ workflow WISPS { ) ch_versions = ch_versions.mix(MSA.out.versions) - //MSA.out.json.view() - //ch_interaction_in.view() - // Prepare interactions for boltz ch_boltz_data = Channel.empty() ch_split_msa_in = Channel.empty() @@ -278,7 +273,6 @@ workflow WISPS { .buffer( size: analysis_batch_size, remainder: true ) .set{ch_boltz_in} - //ch_boltz_in.view() boltz_batch = 0 RUN_BOLTZ( @@ -331,7 +325,6 @@ workflow WISPS { ch_colabfold_interaction_in } } - //ch_colabfold_interaction_in.view() COLABFOLD_BATCH( ch_colabfold_interaction_in, @@ -484,7 +477,6 @@ workflow WISPS { ch_multiqc_files = ch_multiqc_files.mix(ch_collated_versions) ch_multiqc_files = ch_multiqc_files .mix(COLLECT_CONFIDENCE.out.confidence.map{it[1]}) - //ch_multiqc_files.view() MULTIQC ( ch_multiqc_files.collect(sort: true), ch_multiqc_config.collect() From cb7cee8589fcd01ff93068069be93fef4b7a4f58 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Tue, 7 Oct 2025 10:41:03 +1100 Subject: [PATCH 18/70] formatting --- modules/local/collect_confidence.nf | 2 +- modules/local/prepare_interactions.nf | 2 +- nextflow.config | 11 +++++++++++ 3 files changed, 13 insertions(+), 2 deletions(-) diff --git a/modules/local/collect_confidence.nf b/modules/local/collect_confidence.nf index d36c20e..bf9b5ad 100644 --- a/modules/local/collect_confidence.nf +++ b/modules/local/collect_confidence.nf @@ -5,7 +5,7 @@ process COLLECT_CONFIDENCE { conda "${moduleDir}/environment.yml" container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - 'quay.io/biocontainers/python:3.8.3' }" + 'biocontainers/python:3.8.3' }" input: tuple val(meta), val(samples) diff --git a/modules/local/prepare_interactions.nf b/modules/local/prepare_interactions.nf index c8189dd..da41840 100644 --- a/modules/local/prepare_interactions.nf +++ b/modules/local/prepare_interactions.nf @@ -5,7 +5,7 @@ process PREPARE_INTERACTIONS { conda "${moduleDir}/environment.yml" container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - 'quay.io/biocontainers/python:3.8.3' }" + 'biocontainers/python:3.8.3' }" input: tuple val(meta), val(ids) diff --git a/nextflow.config b/nextflow.config index 4b641ce..f8367ed 100644 --- a/nextflow.config +++ b/nextflow.config @@ -24,6 +24,17 @@ params { ipsae_pae_cutoff = 10 ipsae_dist_cutoff = 10 + boltz_ccd = 'https://huggingface.co/boltz-community/boltz-1/resolve/main/ccd.pkl' + boltz_model = 'https://huggingface.co/boltz-community/boltz-1/resolve/main/boltz1_conf.ckpt' + boltz2_aff = 'https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_aff.ckpt' + boltz2_conf = 'https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_conf.ckpt' + boltz2_mols = null // extract this file locally: 'https://huggingface.co/boltz-community/boltz-2/resolve/main/mols.tar' + + colabfold_db = null + uniref30 = null + colabfold_alphafold2_params = null + alphafold3_params = null + // MultiQC options multiqc_config = null multiqc_title = null From 3b58a365203bf39c015898f72b42d855b555be4a Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Tue, 7 Oct 2025 11:36:13 +1100 Subject: [PATCH 19/70] cleaning --- .nf-core.yml | 12 +- .pre-commit-config.yaml | 7 + CITATIONS.md | 2 - README.md | 1 - bin/ipsae.py | 80 +- bin/latest.py | 787 ----------------- bin/zt-search.py | 802 ------------------ conf/gadi.config | 9 +- conf/modules.config | 4 +- conf/test.config | 2 +- conf/test_gadi.config | 13 +- docs/output.md | 3 - docs/usage.md | 12 +- main.nf | 4 +- modules/local/colabfold_batch/main.nf | 4 +- modules/local/collect_confidence.nf | 14 +- modules/local/mmseqs_colabfoldsearch/main.nf | 4 +- modules/local/msa_manager/split_msa.nf | 4 +- modules/local/prepare_interactions.nf | 10 +- modules/local/run_alphafold3/main.nf | 4 +- modules/local/run_boltz/main.nf | 4 +- .../nf-core/multiqc/tests/main.nf.test.snap | 2 +- nextflow.config | 6 +- nextflow_schema.json | 18 +- subworkflows/local/msa.nf | 18 +- .../local/utils_nfcore_wisps_pipeline/main.nf | 6 +- .../tests/main.function.nf.test.snap | 2 +- .../tests/main.function.nf.test.snap | 2 +- .../tests/main.workflow.nf.test.snap | 2 +- .../nf-core/utils_nfschema_plugin/main.nf | 1 - .../tests/nextflow.config | 2 +- workflows/wisps.nf | 64 +- 32 files changed, 154 insertions(+), 1751 deletions(-) delete mode 100644 bin/latest.py delete mode 100755 bin/zt-search.py diff --git a/.nf-core.yml b/.nf-core.yml index 10d202b..d6dc0bc 100644 --- a/.nf-core.yml +++ b/.nf-core.yml @@ -1,10 +1,10 @@ bump_version: null lint: files_exist: - - conf/igenomes.config - - conf/igenomes_ignored.config - - conf/igenomes.config - - conf/igenomes_ignored.config + - conf/igenomes.config + - conf/igenomes_ignored.config + - conf/igenomes.config + - conf/igenomes_ignored.config nf_core_version: 3.0.2 org_path: null repository_type: pipeline @@ -17,7 +17,7 @@ template: org: nf-core outdir: . skip_features: - - igenomes - - fastqc + - igenomes + - fastqc version: 1.0.0dev update: null diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 9e9f0e1..13f7acf 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -11,3 +11,10 @@ repos: hooks: - id: editorconfig-checker alias: ec + - repo: https://github.com/pre-commit/pre-commit-hooks + rev: v4.5.0 + hooks: + - id: trailing-whitespace + - id: end-of-file-fixer + - id: check-yaml + - id: check-json diff --git a/CITATIONS.md b/CITATIONS.md index 18a8064..6c0bab4 100644 --- a/CITATIONS.md +++ b/CITATIONS.md @@ -10,8 +10,6 @@ ## Pipeline tools - - - [MultiQC](https://pubmed.ncbi.nlm.nih.gov/27312411/) > Ewels P, Magnusson M, Lundin S, Käller M. MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics. 2016 Oct 1;32(19):3047-8. doi: 10.1093/bioinformatics/btw354. Epub 2016 Jun 16. PubMed PMID: 27312411; PubMed Central PMCID: PMC5039924. diff --git a/README.md b/README.md index d69d77c..28b6924 100644 --- a/README.md +++ b/README.md @@ -31,7 +31,6 @@ workflows use the "tube map" design for that. See https://nf-co.re/docs/contributing/design_guidelines#examples for examples. --> - 2. Present QC for raw reads ([`MultiQC`](http://multiqc.info/)) ## Usage diff --git a/bin/ipsae.py b/bin/ipsae.py index bca9b42..dd8ad42 100755 --- a/bin/ipsae.py +++ b/bin/ipsae.py @@ -85,7 +85,7 @@ else: print("Wrong PDB or PAE file type ", pdb_path) sys.exit() - + file_path = path_stem + ".txt" file2_path = path_stem + "_byres.txt" pml_path = path_stem + ".pml" @@ -97,7 +97,7 @@ # Define the ptm and d0 functions def ptm_func(x,d0): - return 1.0/(1+(x/d0)**2.0) + return 1.0/(1+(x/d0)**2.0) ptm_func_vec=np.vectorize(ptm_func) # vector version # Define the d0 functions for numbers and arrays; minimum value = 1.0; from Yang and Skolnick, PROTEINS: Structure, Function, and Bioinformatics 57:702–710 (2004) @@ -167,12 +167,12 @@ def parse_cif_atom_line(line,fielddict): #HETATM 1307 C C . TPO A 1 160 ? -2.115 -11.668 12.263 1.00 96.19 160 A 1 #HETATM 1308 O O . TPO A 1 160 ? -1.790 -11.556 11.113 1.00 95.75 160 A 1 # ... - #HETATM 2608 P PG . ATP C 3 . ? -6.858 4.182 10.275 1.00 84.94 1 C 1 - #HETATM 2609 O O1G . ATP C 3 . ? -6.178 5.238 11.074 1.00 75.56 1 C 1 - #HETATM 2610 O O2G . ATP C 3 . ? -5.889 3.166 9.748 1.00 75.15 1 C 1 + #HETATM 2608 P PG . ATP C 3 . ? -6.858 4.182 10.275 1.00 84.94 1 C 1 + #HETATM 2609 O O1G . ATP C 3 . ? -6.178 5.238 11.074 1.00 75.56 1 C 1 + #HETATM 2610 O O2G . ATP C 3 . ? -5.889 3.166 9.748 1.00 75.15 1 C 1 # ... - #HETATM 2639 MG MG . MG D 4 . ? -7.262 2.709 4.825 1.00 91.47 1 D 1 - #HETATM 2640 MG MG . MG E 5 . ? -4.994 2.251 8.755 1.00 85.96 1 E 1 + #HETATM 2639 MG MG . MG D 4 . ? -7.262 2.709 4.825 1.00 91.47 1 D 1 + #HETATM 2640 MG MG . MG E 5 . ? -4.994 2.251 8.755 1.00 85.96 1 E 1 # Boltz1 mmcif files (in non-standard order)) @@ -212,7 +212,7 @@ def parse_cif_atom_line(line,fielddict): #HETATM 2665 O O1B . ATP . 1 ? C -7.04640 8.36577 -7.14326 1 3 C ATP 1 1 #HETATM 2666 O O2B . ATP . 1 ? C -5.79036 7.13926 -5.33995 1 3 C ATP 1 1 - + linelist = line.split() atom_num = linelist[ fielddict['id'] ] atom_name = linelist[ fielddict['label_atom_id'] ] @@ -249,7 +249,7 @@ def parse_cif_atom_line(line,fielddict): def contiguous_ranges(numbers): if not numbers: # Check if the set is empty return - + sorted_numbers = sorted(numbers) # Sort the numbers start = sorted_numbers[0] end = start @@ -267,7 +267,7 @@ def format_range(start, end): else: ranges.append(format_range(start, end)) start = end = number - + # Append the last range after the loop ranges.append(format_range(start, end)) @@ -291,7 +291,7 @@ def init_chainpairdict_set(chainlist): def classify_chains(chains, residue_types): nuc_residue_set = {"DA", "DC", "DT", "DG", "A", "C", "U", "G"} chain_types = {} - + # Get unique chains and iterate over them unique_chains = np.unique(chains) for chain in unique_chains: @@ -301,10 +301,10 @@ def classify_chains(chains, residue_types): chain_residues = residue_types[indices] # Count nucleic acid residues nuc_count = sum(residue in nuc_residue_set for residue in chain_residues) - + # Determine if the chain is a nucleic acid or protein chain_types[chain] = 'nucleic_acid' if nuc_count > 0 else 'protein' - + return chain_types @@ -319,7 +319,7 @@ def classify_chains(chains, residue_types): # For af3 and boltz1: need mask to identify CA atom tokens in plddt vector and pae matrix; # Skip ligand atom tokens and non-CA-atom tokens in PTMs (those not in residue_set) -token_mask=list() +token_mask=list() residue_set= {"ALA", "ARG", "ASN", "ASP", "CYS", "GLN", "GLU", "GLY", "HIS", "ILE", "LEU", "LYS", "MET", "PHE", "PRO", @@ -336,7 +336,7 @@ def classify_chains(chains, residue_types): (atomsite,fieldname)=line.split(".") atomsitefield_dict[fieldname]=atomsitefield_num atomsitefield_num += 1 - + if line.startswith("ATOM") or line.startswith("HETATM"): if cif: atom=parse_cif_atom_line(line, atomsitefield_dict) @@ -395,13 +395,13 @@ def classify_chains(chains, residue_types): chain_pair_type[chain1][chain2]='nucleic_acid' else: chain_pair_type[chain1][chain2]='protein' - + # Calculate distance matrix using NumPy broadcasting distances = np.sqrt(((coordinates[:, np.newaxis, :] - coordinates[np.newaxis, :, :])**2).sum(axis=2)) # Load AF2, AF3, or BOLTZ1 data and extract plddt and pae_matrix (and ptm_matrix if available) if af2: - + if os.path.exists(pae_file_path): if pae_file_path.endswith('.pkl'): @@ -409,35 +409,35 @@ def classify_chains(chains, residue_types): else: with open(pae_file_path, 'r') as file: data = json.load(file) - + if 'iptm' in data: iptm_af2 = float(data['iptm']) else: iptm_af2=-1.0 if 'ptm' in data: ptm_af2 = float(data['ptm']) else: ptm_af2=-1.0 - + if 'plddt' in data: plddt = np.array(data['plddt']) cb_plddt = np.array(data['plddt']) # for pDockQ else: plddt = np.zeros(numres) cb_plddt = np.zeros(numres) - + if 'pae' in data: pae_matrix = np.array(data['pae']) elif 'predicted_aligned_error' in data: pae_matrix=np.array(data['predicted_aligned_error']) - + else: print("AF2 PAE file does not exist: ", pae_file_path) sys.exit() - + if boltz1: # Boltz1 filenames: # AURKA_TPX2_model_0.cif # confidence_AURKA_TPX2_model_0.json # pae_AURKA_TPX2_model_0.npz # plddt_AURKA_TPX2_model_0.npz - + plddt_file_path=pae_file_path.replace("pae","plddt") if os.path.exists(plddt_file_path): @@ -448,7 +448,7 @@ def classify_chains(chains, residue_types): else: plddt = np.zeros(ntokens) cb_plddt = np.zeros(ntokens) - + if os.path.exists(pae_file_path): data_pae = np.load(pae_file_path) pae_matrix_boltz1=np.array(data_pae['pae']) @@ -457,7 +457,7 @@ def classify_chains(chains, residue_types): else: print("Boltz1 PAE file does not exist: ", pae_file_path) sys.exit() - + summary_file_path=pae_file_path.replace("pae","confidence") summary_file_path=summary_file_path.replace(".npz",".json") iptm_boltz1= {chain1: {chain2: 0 for chain2 in unique_chains if chain1 != chain2} for chain1 in unique_chains} @@ -494,7 +494,7 @@ def classify_chains(chains, residue_types): atom_plddts=np.array(data['atom_plddts']) plddt=atom_plddts[CA_atom_num] # pull out residue plddts from Calpha atoms cb_plddt=atom_plddts[CB_atom_num] # pull out residue plddts from Cbeta atoms for pDockQ - + # Get pairwise residue PAE matrix by identifying one token per protein residue. # Modified residues have separate tokens for each atom, so need to pull out Calpha atom as token # Skip ligands @@ -503,7 +503,7 @@ def classify_chains(chains, residue_types): else: print("no PAE data in AF3 json file; quitting") sys.exit() - + # Set pae_matrix for AF3 from subset of full PAE matrix from json file token_array=np.array(token_mask) pae_matrix = pae_matrix_af3[np.ix_(token_array.astype(bool), token_array.astype(bool))] @@ -537,7 +537,7 @@ def classify_chains(chains, residue_types): # ipsae_d0chn = calculate ipsae from PAEs with PAE cutoff; d0 = numres in chain pair = len(chain1) + len(chain2) # ipsae_d0dom = calculate ipsae from PAEs with PAE cutoff; d0 from number of residues in chain1 and chain2 that have interchain PAEB is different from B->A) @@ -618,7 +618,7 @@ def classify_chains(chains, residue_types): for residue in chain2residues: pDockQ_unique_residues[chain1][chain2].add(residue) - + if npairs>0: nres=len(list(pDockQ_unique_residues[chain1][chain2])) mean_plddt= cb_plddt[ list(pDockQ_unique_residues[chain1][chain2])].mean() @@ -629,7 +629,7 @@ def classify_chains(chains, residue_types): x=0.0 pDockQ[chain1][chain2]=0.0 nres=0 - + # pDockQ2 for chain1 in unique_chains: @@ -647,7 +647,7 @@ def classify_chains(chains, residue_types): pae_list=pae_matrix[i][valid_pairs] pae_list_ptm=ptm_func_vec(pae_list,10.0) sum += pae_list_ptm.sum() - + if npairs>0: nres=len(list(pDockQ_unique_residues[chain1][chain2])) mean_plddt= cb_plddt[ list(pDockQ_unique_residues[chain1][chain2])].mean() @@ -659,16 +659,16 @@ def classify_chains(chains, residue_types): x=0.0 nres=0 pDockQ2[chain1][chain2]=0.0 - + # LIS for chain1 in unique_chains: for chain2 in unique_chains: if chain1==chain2: continue - + mask = (chains[:, None] == chain1) & (chains[None, :] == chain2) # Select residues for (chain1, chain2) selected_pae = pae_matrix[mask] # Get PAE values for this pair - + if selected_pae.size > 0: # Ensure we have values valid_pae = selected_pae[selected_pae <= 12] # Apply the threshold if valid_pae.size > 0: @@ -715,7 +715,7 @@ def classify_chains(chains, residue_types): for j in np.where(valid_pairs_ipsae)[0]: jresnum=residues[j]['resnum'] unique_residues_chain2[chain1][chain2].add(jresnum) - + # Track unique residues contributing to iptm in interface valid_pairs = (chains == chain2) & (pae_matrix[i] < pae_cutoff) & (distances[i] < dist_cutoff) dist_valid_pair_counts[chain1][chain2] += np.sum(valid_pairs) @@ -749,7 +749,7 @@ def classify_chains(chains, residue_types): n0res_byres[chain1][chain2] = n0res_byres_all d0res_byres[chain1][chain2] = d0res_byres_all - + for i in range(numres): if chains[i] != chain1: continue @@ -778,7 +778,7 @@ def classify_chains(chains, residue_types): f'{ipsae_d0res_byres[chain1][chain2][i]:8.4f}\n' ) OUT2.write(outstring) - + # Compute interchain ipTM and ipSAE for each chain pair for chain1 in unique_chains: for chain2 in unique_chains: @@ -861,7 +861,7 @@ def classify_chains(chains, residue_types): d0res_max[chain1][chain2]=maxd0 d0res_max[chain2][chain1]=maxd0 - + chaincolor={'A':'magenta', 'B':'marine', 'C':'lime', 'D':'orange', 'E':'yellow', 'F':'cyan', 'G':'lightorange', 'H':'pink', 'I':'deepteal', 'J':'forest', 'K':'lightblue', 'L':'slate', @@ -905,7 +905,7 @@ def classify_chains(chains, residue_types): if af2: iptm_af = iptm_af2 # same for all chain pairs in entry if af3: iptm_af = iptm_af3[chain1][chain2] # symmetric value for each chain pair if boltz1: iptm_af=iptm_boltz1[chain1][chain2] - + outstring=f'{chain1} {chain2} {pae_string:3} {dist_string:3} {"asym":5} ' + ( f'{ipsae_d0res_asym[chain1][chain2]:8.6f} ' f'{ipsae_d0chn_asym[chain1][chain2]:8.6f} ' @@ -963,7 +963,7 @@ def classify_chains(chains, residue_types): f'{pdb_stem}\n') OUT.write(outstring) PML.write("# " + outstring) - + chain_pair= f'color_{chain1}_{chain2}' chain1_residues = f'chain {chain1} and resi {contiguous_ranges(unique_residues_chain1[chain1][chain2])}' chain2_residues = f'chain {chain2} and resi {contiguous_ranges(unique_residues_chain2[chain1][chain2])}' diff --git a/bin/latest.py b/bin/latest.py deleted file mode 100644 index d2b4651..0000000 --- a/bin/latest.py +++ /dev/null @@ -1,787 +0,0 @@ -#!/opt/miniforge/bin/python3 -""" -#!/usr/local/bin/python3 - -Functionality for running mmseqs locally. Takes in a fasta file, outputs final.a3m -""" -import logging -import math -import os -import shutil -import subprocess -import json -from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter -from pathlib import Path -from typing import List, Optional, Tuple, Union, Dict -import random - -from input import get_queries, msa_to_str, safe_filename -from utils import AF3Utils - - -logger = logging.getLogger(__name__) - -MODULE_OUTPUT_POS = { - "align": 4, - "convertalis": 4, - "expandaln": 5, - "filterresult": 4, - "lndb": 2, - "mergedbs": 2, - "mvdb": 2, - "pairaln": 4, - "result2msa": 4, - "search": 3, -} - -def rename_output(queries_unique, ext, base): - for job_number, (raw_jobname, query_sequences, query_seqs_cardinality, other_molecules) in enumerate(queries_unique): - os.rename( - base.joinpath(f"{job_number}.{ext}"), - base.joinpath(f"{safe_filename(raw_jobname)}.{ext}"), - ) - -def expand_db(db_path, seq_map, overwrite=True): - index_data = [] - with open(f"{db_path}.index", "r") as in_f: - for line in in_f: - index_data.append([int(x) for x in line.strip().split()]) - - new_index = "" - offset = 0 - seq_itr = 0 - with open(f"{db_path}-tmp", "wb") as out_file: - for seqs in seq_map: - for seq_index in seqs: - start_byte = index_data[seq_index][1] - byte_cnt = index_data[seq_index][2] - with open(f"{db_path}", "rb") as f: - f.seek(start_byte) - out_file.write(f.read(byte_cnt)) - new_index += f"{seq_itr}\t{offset}\t{byte_cnt}\n" - offset += byte_cnt - seq_itr += 1 - - with open(f"{db_path}-tmp.index", "w") as out_f: - out_f.write(new_index) - - if overwrite: - os.rename(f"{db_path}-tmp.index", f"{db_path}.index") - os.rename(f"{db_path}-tmp", f"{db_path}") - -def run_mmseqs(mmseqs: Path, params: List[Union[str, Path]]): - module = params[0] - if module in MODULE_OUTPUT_POS: - output_pos = MODULE_OUTPUT_POS[module] - output_path = Path(params[output_pos]).with_suffix('.dbtype') - if output_path.exists(): - logger.info(f"Skipping {module} because {output_path} already exists") - return - - params_log = " ".join(str(i) for i in params) - logger.info(f"Running {mmseqs} {params_log}") - # hide MMseqs2 verbose paramters list that clogs up the log - os.environ["MMSEQS_CALL_DEPTH"] = "1" - os.environ["MMSEQS_FORCE_MERGE"] = "True" - subprocess.check_call([mmseqs] + params) - - -def mmseqs_search_monomer( - dbbase: Path, - base: Path, - uniref_db: Path = Path("uniref30_2302_db"), - template_db: Path = Path(""), # Unused by default - metagenomic_db: Path = Path("colabfold_envdb_202108_db"), - mmseqs: Path = Path("mmseqs"), - use_env: bool = True, - use_templates: bool = False, - filter: bool = True, - expand_eval: float = math.inf, - align_eval: int = 10, - diff: int = 3000, - qsc: float = -20.0, - max_accept: int = 1000000, - prefilter_mode: int = 0, - s: float = 8, - db_load_mode: int = 2, - threads: int = 32, - gpu: int = 0, - gpu_server: int = 0, - unpack: bool = True, -): - """Run mmseqs with a local colabfold database set - - db1: uniprot db (UniRef30) - db2: Template (unused by default) - db3: metagenomic db (colabfold_envdb_202108 or bfd_mgy_colabfold, the former is preferred) - """ - if filter: - # 0.1 was not used in benchmarks due to POSIX shell bug in line above - # EXPAND_EVAL=0.1 - align_eval = 10 - qsc = 0.8 - max_accept = 100000 - - used_dbs = [uniref_db] - if use_templates: - used_dbs.append(template_db) - if use_env: - used_dbs.append(metagenomic_db) - - for db in used_dbs: - if not dbbase.joinpath(f"{db}.dbtype").is_file(): - raise FileNotFoundError(f"Database {db} does not exist") - if ( - ( - not dbbase.joinpath(f"{db}.idx").is_file() - and not dbbase.joinpath(f"{db}.idx.index").is_file() - ) - or os.environ.get("MMSEQS_IGNORE_INDEX", False) - ): - logger.info("Search does not use index") - db_load_mode = 0 - dbSuffix1 = "_seq" - dbSuffix2 = "_aln" - dbSuffix3 = "" - else: - dbSuffix1 = ".idx" - dbSuffix2 = ".idx" - dbSuffix3 = ".idx" - - search_param = ["--num-iterations", "3", "--db-load-mode", str(db_load_mode), "-a", "-e", "0.1", "--max-seqs", "10000"] - template_search_param = [] - if gpu: - search_param += ["--gpu", str(gpu), "--prefilter-mode", "1"] # gpu version only supports ungapped prefilter currently - template_search_param += ["--gpu", str(gpu), "--prefilter-mode", "1"] - else: - search_param += ["--prefilter-mode", str(prefilter_mode)] - template_search_param += ["-s", "7.5", "--prefilter-mode", str(prefilter_mode)] - if s is not None: # sensitivy can only be set for non-gpu version, gpu version runs at max sensitivity - search_param += ["-s", "{:.1f}".format(s)] - else: - search_param += ["--k-score", "'seq:96,prof:80'"] - if gpu_server: - search_param += ["--gpu-server", str(gpu_server)] - - filter_param = ["--filter-msa", str(filter), "--filter-min-enable", "1000", "--diff", str(diff), "--qid", "0.0,0.2,0.4,0.6,0.8,1.0", "--qsc", "0", "--max-seq-id", "0.95",] - expand_param = ["--expansion-mode", "0", "-e", str(expand_eval), "--expand-filter-clusters", str(filter), "--max-seq-id", "0.95",] - - if not base.joinpath("uniref.a3m").with_suffix('.a3m.dbtype').exists(): - run_mmseqs(mmseqs, ["search", base.joinpath("qdb"), dbbase.joinpath(uniref_db), base.joinpath("res"), base.joinpath("tmp"), "--threads", str(threads)] + search_param) - os.mkdir(base.joinpath("kept_data")) - run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/profile_1"), base.joinpath("prof_res")]) - run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/aln_1"), base.joinpath("kept_data/aln_1")]) - run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/aln_0"), base.joinpath("kept_data/aln_0")]) - #run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/profile_0"), base.joinpath("kept_data/profile_0")]) - #exit() - run_mmseqs(mmseqs, ["lndb", base.joinpath("qdb_h"), base.joinpath("prof_res_h")]) - - run_mmseqs(mmseqs, ["expandaln", base.joinpath("qdb"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), base.joinpath("res"), dbbase.joinpath(f"{uniref_db}{dbSuffix2}"), base.joinpath("res_exp"), "--db-load-mode", str(db_load_mode), "--threads", str(threads)] + expand_param) - run_mmseqs(mmseqs, ["align", base.joinpath("prof_res"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), base.joinpath("res_exp"), base.joinpath("res_exp_realign"), "--db-load-mode", str(db_load_mode), "-e", str(align_eval), "--max-accept", str(max_accept), "--threads", str(threads), "--alt-ali", "10", "-a"]) - run_mmseqs(mmseqs, ["filterresult", base.joinpath("qdb"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), - base.joinpath("res_exp_realign"), base.joinpath("res_exp_realign_filter"), "--db-load-mode", - str(db_load_mode), "--qid", "0", "--qsc", str(qsc), "--diff", "0", "--threads", - str(threads), "--max-seq-id", "1.0", "--filter-min-enable", "100"]) - run_mmseqs(mmseqs, ["result2msa", base.joinpath("qdb"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), - base.joinpath("res_exp_realign_filter"), base.joinpath("uniref.a3m"), "--msa-format-mode", - "6", "--db-load-mode", str(db_load_mode), "--threads", str(threads)] + filter_param) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign_filter")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp")]) - #run_mmseqs(mmseqs, ["rmdb", base.joinpath("res")]) - - else: - logger.info(f"Skipping {uniref_db} search because uniref.a3m already exists") - - if use_env and not base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m").with_suffix('.a3m.dbtype').exists(): - run_mmseqs(mmseqs, ["search", base.joinpath("prof_res"), dbbase.joinpath(metagenomic_db), base.joinpath("res_env"), - base.joinpath("tmp3"), "--threads", str(threads)] + search_param) - run_mmseqs(mmseqs, ["expandaln", base.joinpath("prof_res"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), base.joinpath("res_env"), - dbbase.joinpath(f"{metagenomic_db}{dbSuffix2}"), base.joinpath("res_env_exp"), "-e", str(expand_eval), - "--expansion-mode", "0", "--db-load-mode", str(db_load_mode), "--threads", str(threads)]) - run_mmseqs(mmseqs, ["align", base.joinpath("tmp3/latest/profile_1"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), - base.joinpath("res_env_exp"), base.joinpath("res_env_exp_realign"), "--db-load-mode", - str(db_load_mode), "-e", str(align_eval), "--max-accept", str(max_accept), "--threads", - str(threads), "--alt-ali", "10", "-a"]) - run_mmseqs(mmseqs, ["filterresult", base.joinpath("qdb"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), - base.joinpath("res_env_exp_realign"), base.joinpath("res_env_exp_realign_filter"), - "--db-load-mode", str(db_load_mode), "--qid", "0", "--qsc", str(qsc), "--diff", "0", - "--max-seq-id", "1.0", "--threads", str(threads), "--filter-min-enable", "100"]) - run_mmseqs(mmseqs, ["result2msa", base.joinpath("qdb"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), - base.joinpath("res_env_exp_realign_filter"), - base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m"), "--msa-format-mode", "6", - "--db-load-mode", str(db_load_mode), "--threads", str(threads)] + filter_param) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env_exp_realign_filter")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env_exp_realign")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env_exp")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env")]) - elif use_env: - logger.info(f"Skipping {metagenomic_db} search because bfd.mgnify30.metaeuk30.smag30.a3m already exists") - - if use_templates and not base.joinpath(f"{template_db}.m8").with_suffix('.m8.dbtype').exists(): - run_mmseqs(mmseqs, ["search", base.joinpath("prof_res"), dbbase.joinpath(template_db), base.joinpath("res_pdb"), - base.joinpath("tmp2"), "--db-load-mode", str(db_load_mode), "--threads", str(threads), "-a", "-e", "0.1"] + template_search_param) - run_mmseqs(mmseqs, ["convertalis", base.joinpath("prof_res"), dbbase.joinpath(f"{template_db}{dbSuffix3}"), base.joinpath("res_pdb"), - base.joinpath(f"{template_db}"), "--format-output", - "query,target,fident,alnlen,mismatch,gapopen,qstart,qend,tstart,tend,evalue,bits,cigar", - "--db-output", "1", - "--db-load-mode", str(db_load_mode), "--threads", str(threads)]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_pdb")]) - elif use_templates: - logger.info(f"Skipping {template_db} search because {template_db}.m8 already exists") - - if use_env: - run_mmseqs(mmseqs, ["mergedbs", base.joinpath("qdb"), base.joinpath("final.a3m"), base.joinpath("uniref.a3m"), base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("uniref.a3m")]) - else: - run_mmseqs(mmseqs, ["mvdb", base.joinpath("uniref.a3m"), base.joinpath("final.a3m")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("uniref.a3m")]) - - if unpack: - run_mmseqs(mmseqs, ["unpackdb", base.joinpath("final.a3m"), base.joinpath("."), "--unpack-name-mode", "0", "--unpack-suffix", ".a3m"]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("final.a3m")]) - - if use_templates: - run_mmseqs(mmseqs, ["unpackdb", base.joinpath(f"{template_db}"), base.joinpath("."), "--unpack-name-mode", "0", "--unpack-suffix", ".m8"]) - if base.joinpath(f"{template_db}").exists(): - run_mmseqs(mmseqs, ["rmdb", base.joinpath(f"{template_db}")]) - - #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) - #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) - shutil.rmtree(base.joinpath("tmp")) - if use_templates: - shutil.rmtree(base.joinpath("tmp2")) - if use_env: - shutil.rmtree(base.joinpath("tmp3")) - -def mmseqs_search_pair( - dbbase: Path, - base: Path, - uniref_db: Path = Path("uniref30_2302_db"), - spire_db: Path = Path("spire_ctg10_2401_db"), - mmseqs: Path = Path("mmseqs"), - pair_env: bool = True, - prefilter_mode: int = 0, - s: float = 8, - threads: int = 64, - gpu: bool = False, - gpu_server: bool = False, - db_load_mode: int = 2, - pairing_strategy: int = 0, - unpack: bool = True, - seq_map: list=[], -): - if not dbbase.joinpath(f"{uniref_db}.dbtype").is_file(): - raise FileNotFoundError(f"Database {uniref_db} does not exist") - if ( - ( - not dbbase.joinpath(f"{uniref_db}.idx").is_file() - and not dbbase.joinpath(f"{uniref_db}.idx.index").is_file() - ) - or os.environ.get("MMSEQS_IGNORE_INDEX", False) - ): - logger.info("Search does not use index") - db_load_mode = 0 - dbSuffix1 = "_seq" - dbSuffix2 = "_aln" - else: - dbSuffix1 = ".idx" - dbSuffix2 = ".idx" - - if pair_env: - db = spire_db - output = ".env.paired.a3m" - else: - db = uniref_db - output = ".paired.a3m" - - # fmt: off - # @formatter:off - search_param = ["--num-iterations", "3", "--db-load-mode", str(db_load_mode), "-a", "-e", "0.1", "--max-seqs", "10000",] - if gpu: - search_param += ["--gpu", str(gpu), "--prefilter-mode", "1"] # gpu version only supports ungapped prefilter currently - else: - search_param += ["--prefilter-mode", str(prefilter_mode)] - if s is not None: # sensitivy can only be set for non-gpu version, gpu version runs at max sensitivity - search_param += ["-s", "{:.1f}".format(s)] - else: - search_param += ["--k-score", "'seq:96,prof:80'"] - if gpu_server: - search_param += ["--gpu-server", str(gpu_server)] - expand_param = ["--expansion-mode", "0", "-e", "inf", "--expand-filter-clusters", "0", "--max-seq-id", "0.95",] - - if db != uniref_db: - # cleaning - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) - - run_mmseqs(mmseqs, ["search", base.joinpath("qdb"), dbbase.joinpath(db), base.joinpath("res"), base.joinpath("tmp"), "--threads", str(threads),] + search_param,) - run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/profile_1"), base.joinpath("prof_res")]) - run_mmseqs(mmseqs, ["lndb", base.joinpath("qdb_h"), base.joinpath("prof_res_h")]) - else: - os.makedirs(base.joinpath("tmp/latest")) - run_mmseqs(mmseqs, ["mvdb", base.joinpath("kept_data/aln_0"), base.joinpath("tmp/latest/aln_0")]) - run_mmseqs(mmseqs, ["mvdb", base.joinpath("kept_data/aln_1"), base.joinpath("tmp/latest/aln_1")]) - #run_mmseqs(mmseqs, ["mvdb", base.joinpath("kept_data/profile_0"), base.joinpath("tmp/latest/profile_0")]) - shutil.rmtree(base.joinpath("kept_data")) - - run_mmseqs(mmseqs, ["expandaln", base.joinpath("qdb"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res"), dbbase.joinpath(f"{db}{dbSuffix2}"), base.joinpath("res_exp"), "--db-load-mode", str(db_load_mode), "--threads", str(threads),] + expand_param,) - run_mmseqs(mmseqs, ["align", base.joinpath("prof_res"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res_exp"), base.joinpath("res_exp_realign"), "--db-load-mode", str(db_load_mode), "-e", "0.001", "--max-accept", "1000000", "--threads", str(threads),],) - - # Added by Ziad - #shutil.copy(base.joinpath("res_exp_realign"), base.joinpath("res_exp_realign-minimal")) - #shutil.copy(base.joinpath("res_exp_realign.index"), base.joinpath("res_exp_realign-minimal.index")) - #exit() - run_mmseqs(mmseqs, ["cpdb", base.joinpath("qdb"), base.joinpath("qdb-minimal")]) - - for merged_db in [base.joinpath("res_exp_realign"), base.joinpath("tmp/latest/aln_0"), base.joinpath("tmp/latest/aln_1")]: - print(f"merging {merged_db}") - expand_db(merged_db, seq_map, True) - - os.rename(base.joinpath("original-query.fas"), base.joinpath("query.fas")) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("qdb")]) - query_file = base.joinpath("query.fas") - run_mmseqs( - mmseqs, - ["createdb", query_file, base.joinpath("qdb"), "--shuffle", "0", "--dbtype", "1"], - ) - shutil.copy(base.joinpath("org-qdb.lookup"), base.joinpath("qdb.lookup")) - - - # create profile - prof_param = f"--sub-mat aa:blosum62.out,nucl:nucleotide.out -e 0.1 --mask-profile 1 --e-profile 0.1 --comp-bias-corr 1 --comp-bias-corr-scale 1 --wg 0 --allow-deletion 0 --filter-msa 1 --filter-min-enable 0 --max-seq-id 0.9 --qid 0.0 --qsc -20 --cov 0 --diff 1000 --pseudo-cnt-mode 0 --pca substitution:1.100,context:1.400 --pcb substitution:4.100,context:5.800 --db-load-mode 0 --gap-open aa:11,nucl:5 --gap-extend aa:1,nucl:2 --threads {threads} --compressed 0 -v 3 --profile-output-mode 0" - run_mmseqs( - mmseqs, - ["result2profile", base.joinpath("qdb"), dbbase.joinpath(db), - base.joinpath("tmp/latest/aln_0"), base.joinpath("tmp/latest/profile_0")] + prof_param.split(), - ) - run_mmseqs( - mmseqs, - ["result2profile", base.joinpath("tmp/latest/profile_0"), dbbase.joinpath(db), - base.joinpath("tmp/latest/aln_1"), base.joinpath("prof_res")] + prof_param.split(), - ) - - ### - - run_mmseqs(mmseqs, ["pairaln", base.joinpath("qdb"), dbbase.joinpath(f"{db}"), base.joinpath("res_exp_realign"), base.joinpath("res_exp_realign_pair"), "--db-load-mode", str(db_load_mode), "--pairing-mode", str(pairing_strategy), "--pairing-dummy-mode", "0", "--threads", str(threads), ],) - - run_mmseqs(mmseqs, ["align", base.joinpath("prof_res"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res_exp_realign_pair"), base.joinpath("res_exp_realign_pair_bt"), "--db-load-mode", str(db_load_mode), "-e", "inf", "-a", "--threads", str(threads), ],) - run_mmseqs(mmseqs, ["pairaln", base.joinpath("qdb"), dbbase.joinpath(f"{db}"), base.joinpath("res_exp_realign_pair_bt"), base.joinpath("res_final"), "--db-load-mode", str(db_load_mode), "--pairing-mode", str(pairing_strategy), "--pairing-dummy-mode", "1", "--threads", str(threads),],) - run_mmseqs(mmseqs, ["result2msa", base.joinpath("qdb"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res_final"), base.joinpath("pair.a3m"), "--db-load-mode", str(db_load_mode), "--msa-format-mode", "5", "--threads", str(threads),],) - - if unpack: - run_mmseqs(mmseqs, ["unpackdb", base.joinpath("pair.a3m"), base.joinpath("."), "--unpack-name-mode", "0", "--unpack-suffix", output,],) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("pair.a3m")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign_pair")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign_pair_bt")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_final")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) - shutil.rmtree(base.joinpath("tmp")) - # @formatter:on - # fmt: on - -def main(): - parser = ArgumentParser(formatter_class=ArgumentDefaultsHelpFormatter) - parser.add_argument( - "query", - type=Path, - help="fasta files with the queries.", - ) - parser.add_argument( - "dbbase", - type=Path, - help="The path to the database and indices you downloaded and created with setup_databases.sh", - ) - parser.add_argument( - "base", type=Path, help="Directory for the results (and intermediate files)" - ) - parser.add_argument( - "--prefilter-mode", - type=int, - default=0, - choices=[0, 1, 2], - help="Prefiltering algorithm to use: 0: k-mer (high-mem), 1: ungapped (high-cpu), 2: exhaustive (no prefilter, very slow). See wiki for more details: https://github.com/sokrypton/ColabFold/wiki#colabfold_search", - ) - parser.add_argument( - "-s", - type=float, - default=None, - help="MMseqs2 sensitivity. Lowering this will result in a much faster search but possibly sparser MSAs. By default, the k-mer threshold is directly set to the same one of the server, which corresponds to a sensitivity of ~8.", - ) - # dbs are uniref, templates and environmental - # We normally don't use templates - parser.add_argument( - "--db1", type=Path, default=Path("uniref30_2302_db"), help="UniRef database" - ) - parser.add_argument("--db2", type=Path, default=Path(""), help="Templates database") - parser.add_argument( - "--db3", - type=Path, - default=Path("colabfold_envdb_202108_db"), - help="Environmental database", - ) - parser.add_argument("--db4", type=Path, default=Path("spire_ctg10_2401_db"), help="Environmental pairing database") - - # poor man's boolean arguments - parser.add_argument( - "--use-env", type=int, default=1, choices=[0, 1], help="Use --db3" - ) - parser.add_argument( - "--use-env-pairing", type=int, default=0, choices=[0, 1], help="Use --db4" - ) - parser.add_argument( - "--use-templates", type=int, default=0, choices=[0, 1], help="Use --db2" - ) - parser.add_argument( - "--filter", - type=int, - default=1, - choices=[0, 1], - help="Filter the MSA by pre-defined align_eval, qsc, max_accept", - ) - - # mmseqs params - parser.add_argument( - "--mmseqs", - type=Path, - default=Path("mmseqs"), - help="Location of the mmseqs binary.", - ) - parser.add_argument( - "--expand-eval", - type=float, - default=math.inf, - help="e-val threshold for 'expandaln'.", - ) - parser.add_argument( - "--align-eval", type=int, default=10, help="e-val threshold for 'align'." - ) - parser.add_argument( - "--diff", - type=int, - default=3000, - help="filterresult - Keep at least this many seqs in each MSA block.", - ) - parser.add_argument( - "--qsc", - type=float, - default=-20.0, - help="filterresult - reduce diversity of output MSAs using min score thresh.", - ) - parser.add_argument( - "--max-accept", - type=int, - default=1000000, - help="align - Maximum accepted alignments before alignment calculation for a query is stopped.", - ) - parser.add_argument( - "--pairing_strategy", type=int, default=0, help="pairaln - Pairing strategy." - ) - parser.add_argument( - "--db-load-mode", - type=int, - default=0, - help="Database preload mode 0: auto, 1: fread, 2: mmap, 3: mmap+touch", - ) - parser.add_argument( - "--unpack", type=int, default=1, choices=[0, 1], help="Unpack results to loose files or keep MMseqs2 databases." - ) - parser.add_argument( - "--threads", type=int, default=64, help="Number of threads to use." - ) - parser.add_argument( - "--gpu", type=int, default=0, choices=[0, 1], help="Whether to use GPU (1) or not (0). Control number of GPUs with CUDA_VISIBLE_DEVICES env var." - ) - parser.add_argument( - "--gpu-server", type=int, default=0, choices=[0, 1], help="Whether to use GPU server (1) or not (0)" - ) - - # AlphaFold3 relevant params - parser.add_argument( - "--af3-json", action="store_true", help="Generate input JSON for AlphaFold3 from the provided FASTA/A3M file." - ) - parser.add_argument( - "--af3-msa-as-path", action="store_true", help="Save MSA as a file path instead of a string in the JSON." - ) - args = parser.parse_args() - - logging.basicConfig(level = logging.INFO) - - queries, is_complex = get_queries(args.query, None) - - monomor_seqs = set() - multimer_seqs = set() - queries_unique = [] - overall_unique_seqs = [] - seq_map = [] - for job_number, (raw_jobname, query_sequences, a3m_lines, other_molecules) in enumerate(queries): - # remove duplicates before searching - query_sequences = ( - [query_sequences] if isinstance(query_sequences, str) else query_sequences - ) - if len(query_sequences) == 1: - monomor_seqs.add(query_sequences[0]) - else: - multimer_seqs.update(query_sequences) - - query_seqs_unique = [] - for x in query_sequences: - if x not in query_seqs_unique: - query_seqs_unique.append(x) - - if x not in overall_unique_seqs: - overall_unique_seqs.append(x) - - - query_seqs_cardinality = [0] * len(query_seqs_unique) - for seq in query_sequences: - seq_idx = query_seqs_unique.index(seq) - query_seqs_cardinality[seq_idx] += 1 - - queries_unique.append([raw_jobname, query_seqs_unique, query_seqs_cardinality, other_molecules]) - # Ziad added - - monomor_seqs = monomor_seqs.difference(multimer_seqs) - - for job_number, (raw_jobname, query_sequences, a3m_lines, other_molecules) in enumerate(queries): - seq_map.append([]) - query_seqs_unique = [] - query_sequences = ( - [query_sequences] if isinstance(query_sequences, str) else query_sequences - ) - for x in query_sequences: - if x not in query_seqs_unique: - query_seqs_unique.append(x) - seq_map[job_number].append(overall_unique_seqs.index(x)) - - args.base.mkdir(exist_ok=True, parents=True) - - query_file = args.base.joinpath("original-query.fas") - with query_file.open("w") as f: - for job_number, ( - raw_jobname, - query_sequences, - query_seqs_cardinality, - _ - ) in enumerate(queries_unique): - for j, seq in enumerate(query_sequences): - # The header of first sequence set as 101 - query_seq_headername = 101 + j - f.write(f">{query_seq_headername}\n{seq}\n") - - query_file = args.base.joinpath("query.fas") - with query_file.open("w") as f: - for j, seq in enumerate(overall_unique_seqs): - # The header of first sequence set as 101 - query_seq_headername = 101 + j - f.write(f">{query_seq_headername}\n{seq}\n") - - run_mmseqs( - args.mmseqs, - ["createdb", query_file, args.base.joinpath("qdb"), "--shuffle", "0", "--dbtype", "1"], - ) - with args.base.joinpath("qdb.lookup").open("w") as f: - id = 0 - file_number = 0 - for job_number, ( - raw_jobname, - query_sequences, - query_seqs_cardinality, - _ - ) in enumerate(queries_unique): - for seq in query_sequences: - raw_jobname_first = raw_jobname.split()[0] - f.write(f"{id}\t{raw_jobname_first}\t{file_number}\n") - id += 1 - file_number += 1 - shutil.copy(args.base.joinpath("qdb.lookup"), args.base.joinpath("org-qdb.lookup")) - - mmseqs_search_monomer( - mmseqs=args.mmseqs, - dbbase=args.dbbase, - base=args.base, - uniref_db=args.db1, - template_db=args.db2, - metagenomic_db=args.db3, - use_env=args.use_env, - use_templates=args.use_templates, - filter=args.filter, - expand_eval=args.expand_eval, - align_eval=args.align_eval, - diff=args.diff, - qsc=args.qsc, - max_accept=args.max_accept, - prefilter_mode=args.prefilter_mode, - s=args.s, - db_load_mode=args.db_load_mode, - threads=args.threads, - gpu=args.gpu, - gpu_server=args.gpu_server, - unpack=args.unpack, - ) - ## - #exit() - for seq_id in range(len(overall_unique_seqs)): - shutil.copy(args.base.joinpath(f"{seq_id}.a3m"), args.base.joinpath(f"u-{seq_id}.a3m")) - seq_itr = 0 - for seqs in seq_map: - for j, seq_index in enumerate(seqs): - #if seq_index == seq_id: - a3m_content = open(args.base.joinpath(f"u-{seq_index}.a3m"), "r").readlines() - header = a3m_content[0] - new_header = f">{101 + j}\n" - with open(args.base.joinpath(f"{seq_itr}.a3m"), "w") as out_f: - for line in a3m_content: - out_f.write(line.replace(header, new_header)) - seq_itr += 1 - - #exit() - for seq_id in range(len(overall_unique_seqs)): - os.remove(args.base.joinpath(f"u-{seq_id}.a3m")) - ## finish monomors and keep going for hybrid batch - ## - if is_complex is True: - mmseqs_search_pair( - mmseqs=args.mmseqs, - dbbase=args.dbbase, - base=args.base, - uniref_db=args.db1, - prefilter_mode=args.prefilter_mode, - s=args.s, - db_load_mode=args.db_load_mode, - threads=args.threads, - gpu=args.gpu, - gpu_server=args.gpu_server, - pairing_strategy=args.pairing_strategy, - pair_env=False, - unpack=args.unpack, - seq_map=seq_map - ) - #exit() - if args.use_env_pairing: - mmseqs_search_pair( - mmseqs=args.mmseqs, - dbbase=args.dbbase, - base=args.base, - uniref_db=args.db1, - spire_db=args.db4, - prefilter_mode=args.prefilter_mode, - s=args.s, - db_load_mode=args.db_load_mode, - threads=args.threads, - gpu=args.gpu, - gpu_server=args.gpu_server, - pairing_strategy=args.pairing_strategy, - pair_env=True, - unpack=args.unpack, - ) - #exit() - if args.unpack or args.af3_json: - id = 0 - for job_number, ( - raw_jobname, - query_sequences, - query_seqs_cardinality, - other_molecules, - ) in enumerate(queries_unique): - unpaired_msa = [] - paired_msa = None - if len(query_seqs_cardinality) > 1: - paired_msa = [] - for seq in query_sequences: - with args.base.joinpath(f"{id}.a3m").open("r") as f: - unpaired_msa.append(f.read()) - if args.af3_json: - args.base.joinpath(f"{id}.a3m").unlink() - - if args.use_env_pairing: - with open(args.base.joinpath(f"{id}.paired.a3m"), 'a') as file_pair: - with open(args.base.joinpath(f"{id}.env.paired.a3m"), 'r') as file_pair_env: - while chunk := file_pair_env.read(10 * 1024 * 1024): - file_pair.write(chunk) - if args.unpack: - args.base.joinpath(f"{id}.env.paired.a3m").unlink() - - if len(query_seqs_cardinality) > 1: - with args.base.joinpath(f"{id}.paired.a3m").open("r") as f: - paired_msa.append(f.read()) - if args.unpack: - args.base.joinpath(f"{id}.paired.a3m").unlink() - #os.remove(args.base.joinpath(f"{id}.a3m")) - id += 1 - - if args.af3_json: - af3 = AF3Utils(raw_jobname, query_sequences, query_seqs_cardinality, unpaired_msa, paired_msa, other_molecules) - with open(args.base.joinpath(f"{job_number}.json"), 'w') as f: - f.write(json.dumps(af3.content, indent=4)) - - if args.unpack: - msa = msa_to_str( - unpaired_msa, paired_msa, query_sequences, query_seqs_cardinality - ) - args.base.joinpath(f"{job_number}.a3m").write_text(msa) - #exit() - #os.remove(args.base.joinpath("res_exp_realign-minimal.index")) - #os.remove(args.base.joinpath("res_exp_realign-minimal")) - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("res_exp_realign-minimal")]) - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb-minimal")]) - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb-minimal_h")]) - - - - else: - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("res")]) - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("prof_res")]) - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("prof_res_h")]) - os.remove(args.base.joinpath("original-query.fas")) - - if args.af3_json: - id = 0 - for job_number, (raw_jobname, query_sequences, query_seqs_cardinality, other_molecules) in enumerate(queries_unique): - unpaired_msa = [] - for seq in query_sequences: - with args.base.joinpath(f"{id}.a3m").open("r") as f: - unpaired_msa.append(f.read()) - os.remove(args.base.joinpath(f"{id}.a3m")) - id += 1 - - # Create AF3Utils object and write JSON - af3 = AF3Utils(raw_jobname, query_sequences, query_seqs_cardinality, unpaired_msa, None, other_molecules) - with open(args.base.joinpath(f"{job_number}.json"), 'w') as f: - f.write(json.dumps(af3.content, indent=4)) - - if args.unpack: - # rename a3m files - rename_output(queries_unique, "a3m", args.base) - - # rename m8 files - if args.use_templates: - id = 0 - for raw_jobname, query_sequences, query_seqs_cardinality, _ in queries_unique: - with args.base.joinpath(f"{safe_filename(raw_jobname)}_{args.db2}.m8").open( - "w" - ) as f: - for _ in range(len(query_seqs_cardinality)): - with args.base.joinpath(f"{id}.m8").open("r") as g: - f.write(g.read()) - os.remove(args.base.joinpath(f"{id}.m8")) - id += 1 - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb")]) - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb_h")]) - - if args.af3_json: - # rename json files - rename_output(queries_unique, "json", args.base) - - query_file.unlink() - os.remove(args.base.joinpath("org-qdb.lookup")) - - -if __name__ == "__main__": - main() diff --git a/bin/zt-search.py b/bin/zt-search.py deleted file mode 100755 index 5026066..0000000 --- a/bin/zt-search.py +++ /dev/null @@ -1,802 +0,0 @@ -#!/opt/miniforge/bin/python3 -""" -#!/usr/local/bin/python3 - -Functionality for running mmseqs locally. Takes in a fasta file, outputs final.a3m -""" -import logging -import math -import os -import shutil -import subprocess -import json -from argparse import ArgumentParser, ArgumentDefaultsHelpFormatter -from pathlib import Path -from typing import List, Optional, Tuple, Union, Dict -import random - -from input import get_queries, msa_to_str, safe_filename -from utils import AF3Utils - - -logger = logging.getLogger(__name__) - -MODULE_OUTPUT_POS = { - "align": 4, - "convertalis": 4, - "expandaln": 5, - "filterresult": 4, - "lndb": 2, - "mergedbs": 2, - "mvdb": 2, - "pairaln": 4, - "result2msa": 4, - "search": 3, -} - -def rename_output(queries_unique, ext, base): - for job_number, (raw_jobname, query_sequences, query_seqs_cardinality, other_molecules) in enumerate(queries_unique): - os.rename( - base.joinpath(f"{job_number}.{ext}"), - base.joinpath(f"{safe_filename(raw_jobname)}.{ext}"), - ) - -def expand_db(db_path, seq_map, overwrite=True): - index_data = [] - with open(f"{db_path}.index", "r") as in_f: - for line in in_f: - index_data.append([int(x) for x in line.strip().split()]) - - print(index_data) - new_index = "" - offset = 0 - seq_itr = 0 - with open(f"{db_path}-tmp", "wb") as out_file: - for seqs in seq_map: - for seq_index in seqs: - start_byte = index_data[seq_index][1] - byte_cnt = index_data[seq_index][2] - print(start_byte, byte_cnt, index_data[seq_index]) - with open(f"{db_path}", "rb") as f: - f.seek(start_byte) - out_file.write(f.read(byte_cnt)) - new_index += f"{seq_itr}\t{offset}\t{byte_cnt}\n" - offset += index_data[seq_index][2] - seq_itr += 1 - - with open(f"{db_path}-tmp.index", "w") as out_f: - out_f.write(new_index) - - if overwrite: - os.rename(f"{db_path}-tmp.index", f"{db_path}.index") - os.rename(f"{db_path}-tmp", f"{db_path}") - -def run_mmseqs(mmseqs: Path, params: List[Union[str, Path]]): - module = params[0] - if module in MODULE_OUTPUT_POS: - output_pos = MODULE_OUTPUT_POS[module] - output_path = Path(params[output_pos]).with_suffix('.dbtype') - if output_path.exists(): - logger.info(f"Skipping {module} because {output_path} already exists") - return - - params_log = " ".join(str(i) for i in params) - logger.info(f"Running {mmseqs} {params_log}") - # hide MMseqs2 verbose paramters list that clogs up the log - os.environ["MMSEQS_CALL_DEPTH"] = "1" - os.environ["MMSEQS_FORCE_MERGE"] = "True" - subprocess.check_call([mmseqs] + params) - - -def mmseqs_search_monomer( - dbbase: Path, - base: Path, - uniref_db: Path = Path("uniref30_2302_db"), - template_db: Path = Path(""), # Unused by default - metagenomic_db: Path = Path("colabfold_envdb_202108_db"), - mmseqs: Path = Path("mmseqs"), - use_env: bool = True, - use_templates: bool = False, - filter: bool = True, - expand_eval: float = math.inf, - align_eval: int = 10, - diff: int = 3000, - qsc: float = -20.0, - max_accept: int = 1000000, - prefilter_mode: int = 0, - s: float = 8, - db_load_mode: int = 2, - threads: int = 32, - gpu: int = 0, - gpu_server: int = 0, - unpack: bool = True, -): - """Run mmseqs with a local colabfold database set - - db1: uniprot db (UniRef30) - db2: Template (unused by default) - db3: metagenomic db (colabfold_envdb_202108 or bfd_mgy_colabfold, the former is preferred) - """ - if filter: - # 0.1 was not used in benchmarks due to POSIX shell bug in line above - # EXPAND_EVAL=0.1 - align_eval = 10 - qsc = 0.8 - max_accept = 100000 - - used_dbs = [uniref_db] - if use_templates: - used_dbs.append(template_db) - if use_env: - used_dbs.append(metagenomic_db) - - for db in used_dbs: - if not dbbase.joinpath(f"{db}.dbtype").is_file(): - raise FileNotFoundError(f"Database {db} does not exist") - if ( - ( - not dbbase.joinpath(f"{db}.idx").is_file() - and not dbbase.joinpath(f"{db}.idx.index").is_file() - ) - or os.environ.get("MMSEQS_IGNORE_INDEX", False) - ): - logger.info("Search does not use index") - db_load_mode = 0 - dbSuffix1 = "_seq" - dbSuffix2 = "_aln" - dbSuffix3 = "" - else: - dbSuffix1 = ".idx" - dbSuffix2 = ".idx" - dbSuffix3 = ".idx" - - search_param = ["--num-iterations", "3", "--db-load-mode", str(db_load_mode), "-a", "-e", "0.1", "--max-seqs", "10000"] - template_search_param = [] - if gpu: - search_param += ["--gpu", str(gpu), "--prefilter-mode", "1"] # gpu version only supports ungapped prefilter currently - template_search_param += ["--gpu", str(gpu), "--prefilter-mode", "1"] - else: - search_param += ["--prefilter-mode", str(prefilter_mode)] - template_search_param += ["-s", "7.5", "--prefilter-mode", str(prefilter_mode)] - if s is not None: # sensitivy can only be set for non-gpu version, gpu version runs at max sensitivity - search_param += ["-s", "{:.1f}".format(s)] - else: - search_param += ["--k-score", "'seq:96,prof:80'"] - if gpu_server: - search_param += ["--gpu-server", str(gpu_server)] - - filter_param = ["--filter-msa", str(filter), "--filter-min-enable", "1000", "--diff", str(diff), "--qid", "0.0,0.2,0.4,0.6,0.8,1.0", "--qsc", "0", "--max-seq-id", "0.95",] - expand_param = ["--expansion-mode", "0", "-e", str(expand_eval), "--expand-filter-clusters", str(filter), "--max-seq-id", "0.95",] - - if not base.joinpath("uniref.a3m").with_suffix('.a3m.dbtype').exists(): - run_mmseqs(mmseqs, ["search", base.joinpath("qdb"), dbbase.joinpath(uniref_db), base.joinpath("res"), base.joinpath("tmp"), "--threads", str(threads)] + search_param) - os.mkdir(base.joinpath("kept_data")) - run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/profile_1"), base.joinpath("prof_res")]) - run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/aln_1"), base.joinpath("kept_data/aln_1")]) - run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/aln_0"), base.joinpath("kept_data/aln_0")]) - #run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/profile_0"), base.joinpath("kept_data/profile_0")]) - #exit() - run_mmseqs(mmseqs, ["lndb", base.joinpath("qdb_h"), base.joinpath("prof_res_h")]) - - run_mmseqs(mmseqs, ["expandaln", base.joinpath("qdb"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), base.joinpath("res"), dbbase.joinpath(f"{uniref_db}{dbSuffix2}"), base.joinpath("res_exp"), "--db-load-mode", str(db_load_mode), "--threads", str(threads)] + expand_param) - run_mmseqs(mmseqs, ["align", base.joinpath("prof_res"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), base.joinpath("res_exp"), base.joinpath("res_exp_realign"), "--db-load-mode", str(db_load_mode), "-e", str(align_eval), "--max-accept", str(max_accept), "--threads", str(threads), "--alt-ali", "10", "-a"]) - run_mmseqs(mmseqs, ["filterresult", base.joinpath("qdb"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), - base.joinpath("res_exp_realign"), base.joinpath("res_exp_realign_filter"), "--db-load-mode", - str(db_load_mode), "--qid", "0", "--qsc", str(qsc), "--diff", "0", "--threads", - str(threads), "--max-seq-id", "1.0", "--filter-min-enable", "100"]) - run_mmseqs(mmseqs, ["result2msa", base.joinpath("qdb"), dbbase.joinpath(f"{uniref_db}{dbSuffix1}"), - base.joinpath("res_exp_realign_filter"), base.joinpath("uniref.a3m"), "--msa-format-mode", - "6", "--db-load-mode", str(db_load_mode), "--threads", str(threads)] + filter_param) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign_filter")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp")]) - #run_mmseqs(mmseqs, ["rmdb", base.joinpath("res")]) - - else: - logger.info(f"Skipping {uniref_db} search because uniref.a3m already exists") - - if use_env and not base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m").with_suffix('.a3m.dbtype').exists(): - run_mmseqs(mmseqs, ["search", base.joinpath("prof_res"), dbbase.joinpath(metagenomic_db), base.joinpath("res_env"), - base.joinpath("tmp3"), "--threads", str(threads)] + search_param) - run_mmseqs(mmseqs, ["expandaln", base.joinpath("prof_res"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), base.joinpath("res_env"), - dbbase.joinpath(f"{metagenomic_db}{dbSuffix2}"), base.joinpath("res_env_exp"), "-e", str(expand_eval), - "--expansion-mode", "0", "--db-load-mode", str(db_load_mode), "--threads", str(threads)]) - run_mmseqs(mmseqs, ["align", base.joinpath("tmp3/latest/profile_1"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), - base.joinpath("res_env_exp"), base.joinpath("res_env_exp_realign"), "--db-load-mode", - str(db_load_mode), "-e", str(align_eval), "--max-accept", str(max_accept), "--threads", - str(threads), "--alt-ali", "10", "-a"]) - run_mmseqs(mmseqs, ["filterresult", base.joinpath("qdb"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), - base.joinpath("res_env_exp_realign"), base.joinpath("res_env_exp_realign_filter"), - "--db-load-mode", str(db_load_mode), "--qid", "0", "--qsc", str(qsc), "--diff", "0", - "--max-seq-id", "1.0", "--threads", str(threads), "--filter-min-enable", "100"]) - run_mmseqs(mmseqs, ["result2msa", base.joinpath("qdb"), dbbase.joinpath(f"{metagenomic_db}{dbSuffix1}"), - base.joinpath("res_env_exp_realign_filter"), - base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m"), "--msa-format-mode", "6", - "--db-load-mode", str(db_load_mode), "--threads", str(threads)] + filter_param) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env_exp_realign_filter")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env_exp_realign")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env_exp")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_env")]) - elif use_env: - logger.info(f"Skipping {metagenomic_db} search because bfd.mgnify30.metaeuk30.smag30.a3m already exists") - - if use_templates and not base.joinpath(f"{template_db}.m8").with_suffix('.m8.dbtype').exists(): - run_mmseqs(mmseqs, ["search", base.joinpath("prof_res"), dbbase.joinpath(template_db), base.joinpath("res_pdb"), - base.joinpath("tmp2"), "--db-load-mode", str(db_load_mode), "--threads", str(threads), "-a", "-e", "0.1"] + template_search_param) - run_mmseqs(mmseqs, ["convertalis", base.joinpath("prof_res"), dbbase.joinpath(f"{template_db}{dbSuffix3}"), base.joinpath("res_pdb"), - base.joinpath(f"{template_db}"), "--format-output", - "query,target,fident,alnlen,mismatch,gapopen,qstart,qend,tstart,tend,evalue,bits,cigar", - "--db-output", "1", - "--db-load-mode", str(db_load_mode), "--threads", str(threads)]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_pdb")]) - elif use_templates: - logger.info(f"Skipping {template_db} search because {template_db}.m8 already exists") - - if use_env: - run_mmseqs(mmseqs, ["mergedbs", base.joinpath("qdb"), base.joinpath("final.a3m"), base.joinpath("uniref.a3m"), base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("bfd.mgnify30.metaeuk30.smag30.a3m")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("uniref.a3m")]) - else: - run_mmseqs(mmseqs, ["mvdb", base.joinpath("uniref.a3m"), base.joinpath("final.a3m")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("uniref.a3m")]) - - if unpack: - run_mmseqs(mmseqs, ["unpackdb", base.joinpath("final.a3m"), base.joinpath("."), "--unpack-name-mode", "0", "--unpack-suffix", ".a3m"]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("final.a3m")]) - - if use_templates: - run_mmseqs(mmseqs, ["unpackdb", base.joinpath(f"{template_db}"), base.joinpath("."), "--unpack-name-mode", "0", "--unpack-suffix", ".m8"]) - if base.joinpath(f"{template_db}").exists(): - run_mmseqs(mmseqs, ["rmdb", base.joinpath(f"{template_db}")]) - - #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) - #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) - shutil.rmtree(base.joinpath("tmp")) - if use_templates: - shutil.rmtree(base.joinpath("tmp2")) - if use_env: - shutil.rmtree(base.joinpath("tmp3")) - -def mmseqs_search_pair( - dbbase: Path, - base: Path, - uniref_db: Path = Path("uniref30_2302_db"), - spire_db: Path = Path("spire_ctg10_2401_db"), - mmseqs: Path = Path("mmseqs"), - pair_env: bool = True, - prefilter_mode: int = 0, - s: float = 8, - threads: int = 64, - gpu: bool = False, - gpu_server: bool = False, - db_load_mode: int = 2, - pairing_strategy: int = 0, - unpack: bool = True, - seq_map: list=[], -): - if not dbbase.joinpath(f"{uniref_db}.dbtype").is_file(): - raise FileNotFoundError(f"Database {uniref_db} does not exist") - if ( - ( - not dbbase.joinpath(f"{uniref_db}.idx").is_file() - and not dbbase.joinpath(f"{uniref_db}.idx.index").is_file() - ) - or os.environ.get("MMSEQS_IGNORE_INDEX", False) - ): - logger.info("Search does not use index") - db_load_mode = 0 - dbSuffix1 = "_seq" - dbSuffix2 = "_aln" - else: - dbSuffix1 = ".idx" - dbSuffix2 = ".idx" - - if pair_env: - db = spire_db - output = ".env.paired.a3m" - else: - db = uniref_db - output = ".paired.a3m" - - # fmt: off - # @formatter:off - search_param = ["--num-iterations", "3", "--db-load-mode", str(db_load_mode), "-a", "-e", "0.1", "--max-seqs", "10000",] - if gpu: - search_param += ["--gpu", str(gpu), "--prefilter-mode", "1"] # gpu version only supports ungapped prefilter currently - else: - search_param += ["--prefilter-mode", str(prefilter_mode)] - if s is not None: # sensitivy can only be set for non-gpu version, gpu version runs at max sensitivity - search_param += ["-s", "{:.1f}".format(s)] - else: - search_param += ["--k-score", "'seq:96,prof:80'"] - if gpu_server: - search_param += ["--gpu-server", str(gpu_server)] - expand_param = ["--expansion-mode", "0", "-e", "inf", "--expand-filter-clusters", "0", "--max-seq-id", "0.95",] - - if db != uniref_db: - # cleaning - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) - - run_mmseqs(mmseqs, ["search", base.joinpath("qdb"), dbbase.joinpath(db), base.joinpath("res"), base.joinpath("tmp"), "--threads", str(threads),] + search_param,) - run_mmseqs(mmseqs, ["mvdb", base.joinpath("tmp/latest/profile_1"), base.joinpath("prof_res")]) - run_mmseqs(mmseqs, ["lndb", base.joinpath("qdb_h"), base.joinpath("prof_res_h")]) - else: - os.makedirs(base.joinpath("tmp/latest")) - run_mmseqs(mmseqs, ["mvdb", base.joinpath("kept_data/aln_0"), base.joinpath("tmp/latest/aln_0")]) - run_mmseqs(mmseqs, ["mvdb", base.joinpath("kept_data/aln_1"), base.joinpath("tmp/latest/aln_1")]) - #run_mmseqs(mmseqs, ["mvdb", base.joinpath("kept_data/profile_0"), base.joinpath("tmp/latest/profile_0")]) - shutil.rmtree(base.joinpath("kept_data")) - - run_mmseqs(mmseqs, ["expandaln", base.joinpath("qdb"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res"), dbbase.joinpath(f"{db}{dbSuffix2}"), base.joinpath("res_exp"), "--db-load-mode", str(db_load_mode), "--threads", str(threads),] + expand_param,) - run_mmseqs(mmseqs, ["align", base.joinpath("prof_res"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res_exp"), base.joinpath("res_exp_realign"), "--db-load-mode", str(db_load_mode), "-e", "0.001", "--max-accept", "1000000", "--threads", str(threads),],) - - # Added by Ziad - #shutil.copy(base.joinpath("res_exp_realign"), base.joinpath("res_exp_realign-minimal")) - #shutil.copy(base.joinpath("res_exp_realign.index"), base.joinpath("res_exp_realign-minimal.index")) - #exit() - run_mmseqs(mmseqs, ["cpdb", base.joinpath("qdb"), base.joinpath("qdb-minimal")]) - - for merged_db in [base.joinpath("res_exp_realign"), base.joinpath("tmp/latest/aln_0"), base.joinpath("tmp/latest/aln_1")]: - print(f"merging {merged_db}") - expand_db(merged_db, seq_map, True) - - os.rename(base.joinpath("original-query.fas"), base.joinpath("query.fas")) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("qdb")]) - query_file = base.joinpath("query.fas") - run_mmseqs( - mmseqs, - ["createdb", query_file, base.joinpath("qdb"), "--shuffle", "0", "--dbtype", "1"], - ) - shutil.copy(base.joinpath("org-qdb.lookup"), base.joinpath("qdb.lookup")) - - ### fix with res - - #exit() - - - # create profile - #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) - #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) - - prof_param = f"--sub-mat aa:blosum62.out,nucl:nucleotide.out -e 0.1 --mask-profile 1 --e-profile 0.1 --comp-bias-corr 1 --comp-bias-corr-scale 1 --wg 0 --allow-deletion 0 --filter-msa 1 --filter-min-enable 0 --max-seq-id 0.9 --qid 0.0 --qsc -20 --cov 0 --diff 1000 --pseudo-cnt-mode 0 --pca substitution:1.100,context:1.400 --pcb substitution:4.100,context:5.800 --db-load-mode 0 --gap-open aa:11,nucl:5 --gap-extend aa:1,nucl:2 --threads {threads} --compressed 0 -v 3 --profile-output-mode 0" - run_mmseqs( - mmseqs, - ["result2profile", base.joinpath("qdb"), dbbase.joinpath(db), - base.joinpath("tmp/latest/aln_0"), base.joinpath("tmp/latest/profile_0")] + prof_param.split(), - ) - run_mmseqs( - mmseqs, - ["result2profile", base.joinpath("tmp/latest/profile_0"), dbbase.joinpath(db), - base.joinpath("tmp/latest/aln_1"), base.joinpath("prof_res")] + prof_param.split(), - ) - - ### - - #exit() - run_mmseqs(mmseqs, ["pairaln", base.joinpath("qdb"), dbbase.joinpath(f"{db}"), base.joinpath("res_exp_realign"), base.joinpath("res_exp_realign_pair"), "--db-load-mode", str(db_load_mode), "--pairing-mode", str(pairing_strategy), "--pairing-dummy-mode", "0", "--threads", str(threads), ],) - - run_mmseqs(mmseqs, ["align", base.joinpath("prof_res"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res_exp_realign_pair"), base.joinpath("res_exp_realign_pair_bt"), "--db-load-mode", str(db_load_mode), "-e", "inf", "-a", "--threads", str(threads), ],) - run_mmseqs(mmseqs, ["pairaln", base.joinpath("qdb"), dbbase.joinpath(f"{db}"), base.joinpath("res_exp_realign_pair_bt"), base.joinpath("res_final"), "--db-load-mode", str(db_load_mode), "--pairing-mode", str(pairing_strategy), "--pairing-dummy-mode", "1", "--threads", str(threads),],) - run_mmseqs(mmseqs, ["result2msa", base.joinpath("qdb"), dbbase.joinpath(f"{db}{dbSuffix1}"), base.joinpath("res_final"), base.joinpath("pair.a3m"), "--db-load-mode", str(db_load_mode), "--msa-format-mode", "5", "--threads", str(threads),],) - - if unpack: - run_mmseqs(mmseqs, ["unpackdb", base.joinpath("pair.a3m"), base.joinpath("."), "--unpack-name-mode", "0", "--unpack-suffix", output,],) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("pair.a3m")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign_pair")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_exp_realign_pair_bt")]) - run_mmseqs(mmseqs, ["rmdb", base.joinpath("res_final")]) - #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res")]) - #run_mmseqs(mmseqs, ["rmdb", base.joinpath("prof_res_h")]) - #shutil.rmtree(base.joinpath("tmp")) - # @formatter:on - # fmt: on - -def main(): - parser = ArgumentParser(formatter_class=ArgumentDefaultsHelpFormatter) - parser.add_argument( - "query", - type=Path, - help="fasta files with the queries.", - ) - parser.add_argument( - "dbbase", - type=Path, - help="The path to the database and indices you downloaded and created with setup_databases.sh", - ) - parser.add_argument( - "base", type=Path, help="Directory for the results (and intermediate files)" - ) - parser.add_argument( - "--prefilter-mode", - type=int, - default=0, - choices=[0, 1, 2], - help="Prefiltering algorithm to use: 0: k-mer (high-mem), 1: ungapped (high-cpu), 2: exhaustive (no prefilter, very slow). See wiki for more details: https://github.com/sokrypton/ColabFold/wiki#colabfold_search", - ) - parser.add_argument( - "-s", - type=float, - default=None, - help="MMseqs2 sensitivity. Lowering this will result in a much faster search but possibly sparser MSAs. By default, the k-mer threshold is directly set to the same one of the server, which corresponds to a sensitivity of ~8.", - ) - # dbs are uniref, templates and environmental - # We normally don't use templates - parser.add_argument( - "--db1", type=Path, default=Path("uniref30_2302_db"), help="UniRef database" - ) - parser.add_argument("--db2", type=Path, default=Path(""), help="Templates database") - parser.add_argument( - "--db3", - type=Path, - default=Path("colabfold_envdb_202108_db"), - help="Environmental database", - ) - parser.add_argument("--db4", type=Path, default=Path("spire_ctg10_2401_db"), help="Environmental pairing database") - - # poor man's boolean arguments - parser.add_argument( - "--use-env", type=int, default=1, choices=[0, 1], help="Use --db3" - ) - parser.add_argument( - "--use-env-pairing", type=int, default=0, choices=[0, 1], help="Use --db4" - ) - parser.add_argument( - "--use-templates", type=int, default=0, choices=[0, 1], help="Use --db2" - ) - parser.add_argument( - "--filter", - type=int, - default=1, - choices=[0, 1], - help="Filter the MSA by pre-defined align_eval, qsc, max_accept", - ) - - # mmseqs params - parser.add_argument( - "--mmseqs", - type=Path, - default=Path("mmseqs"), - help="Location of the mmseqs binary.", - ) - parser.add_argument( - "--expand-eval", - type=float, - default=math.inf, - help="e-val threshold for 'expandaln'.", - ) - parser.add_argument( - "--align-eval", type=int, default=10, help="e-val threshold for 'align'." - ) - parser.add_argument( - "--diff", - type=int, - default=3000, - help="filterresult - Keep at least this many seqs in each MSA block.", - ) - parser.add_argument( - "--qsc", - type=float, - default=-20.0, - help="filterresult - reduce diversity of output MSAs using min score thresh.", - ) - parser.add_argument( - "--max-accept", - type=int, - default=1000000, - help="align - Maximum accepted alignments before alignment calculation for a query is stopped.", - ) - parser.add_argument( - "--pairing_strategy", type=int, default=0, help="pairaln - Pairing strategy." - ) - parser.add_argument( - "--db-load-mode", - type=int, - default=0, - help="Database preload mode 0: auto, 1: fread, 2: mmap, 3: mmap+touch", - ) - parser.add_argument( - "--unpack", type=int, default=1, choices=[0, 1], help="Unpack results to loose files or keep MMseqs2 databases." - ) - parser.add_argument( - "--threads", type=int, default=64, help="Number of threads to use." - ) - parser.add_argument( - "--gpu", type=int, default=0, choices=[0, 1], help="Whether to use GPU (1) or not (0). Control number of GPUs with CUDA_VISIBLE_DEVICES env var." - ) - parser.add_argument( - "--gpu-server", type=int, default=0, choices=[0, 1], help="Whether to use GPU server (1) or not (0)" - ) - - # AlphaFold3 relevant params - parser.add_argument( - "--af3-json", action="store_true", help="Generate input JSON for AlphaFold3 from the provided FASTA/A3M file." - ) - parser.add_argument( - "--af3-msa-as-path", action="store_true", help="Save MSA as a file path instead of a string in the JSON." - ) - args = parser.parse_args() - - logging.basicConfig(level = logging.INFO) - - queries, is_complex = get_queries(args.query, None) - - monomor_seqs = set() - multimer_seqs = set() - queries_unique = [] - overall_unique_seqs = [] - seq_map = [] - for job_number, (raw_jobname, query_sequences, a3m_lines, other_molecules) in enumerate(queries): - # remove duplicates before searching - query_sequences = ( - [query_sequences] if isinstance(query_sequences, str) else query_sequences - ) - if len(query_sequences) == 1: - monomor_seqs.add(query_sequences[0]) - else: - multimer_seqs.update(query_sequences) - - query_seqs_unique = [] - for x in query_sequences: - if x not in query_seqs_unique: - query_seqs_unique.append(x) - - if x not in overall_unique_seqs: - overall_unique_seqs.append(x) - - - query_seqs_cardinality = [0] * len(query_seqs_unique) - for seq in query_sequences: - seq_idx = query_seqs_unique.index(seq) - query_seqs_cardinality[seq_idx] += 1 - - queries_unique.append([raw_jobname, query_seqs_unique, query_seqs_cardinality, other_molecules]) - # Ziad added - - monomor_seqs = monomor_seqs.difference(multimer_seqs) - - for job_number, (raw_jobname, query_sequences, a3m_lines, other_molecules) in enumerate(queries): - seq_map.append([]) - query_seqs_unique = [] - query_sequences = ( - [query_sequences] if isinstance(query_sequences, str) else query_sequences - ) - for x in query_sequences: - if x not in query_seqs_unique: - query_seqs_unique.append(x) - seq_map[job_number].append(overall_unique_seqs.index(x)) - - #print(seq_map) - #exit() - args.base.mkdir(exist_ok=True, parents=True) - - # updated by Ziad - query_file = args.base.joinpath("original-query.fas") - with query_file.open("w") as f: - for job_number, ( - raw_jobname, - query_sequences, - query_seqs_cardinality, - _ - ) in enumerate(queries_unique): - for j, seq in enumerate(query_sequences): - # The header of first sequence set as 101 - query_seq_headername = 101 + j - f.write(f">{query_seq_headername}\n{seq}\n") - - query_file = args.base.joinpath("query.fas") - with query_file.open("w") as f: - for j, seq in enumerate(overall_unique_seqs): - # The header of first sequence set as 101 - query_seq_headername = 101 + j - f.write(f">{query_seq_headername}\n{seq}\n") - - run_mmseqs( - args.mmseqs, - ["createdb", query_file, args.base.joinpath("qdb"), "--shuffle", "0", "--dbtype", "1"], - ) - with args.base.joinpath("qdb.lookup").open("w") as f: - id = 0 - file_number = 0 - for job_number, ( - raw_jobname, - query_sequences, - query_seqs_cardinality, - _ - ) in enumerate(queries_unique): - for seq in query_sequences: - raw_jobname_first = raw_jobname.split()[0] - f.write(f"{id}\t{raw_jobname_first}\t{file_number}\n") - id += 1 - file_number += 1 - shutil.copy(args.base.joinpath("qdb.lookup"), args.base.joinpath("org-qdb.lookup")) - #print("DOne") - - #exit() - mmseqs_search_monomer( - mmseqs=args.mmseqs, - dbbase=args.dbbase, - base=args.base, - uniref_db=args.db1, - template_db=args.db2, - metagenomic_db=args.db3, - use_env=args.use_env, - use_templates=args.use_templates, - filter=args.filter, - expand_eval=args.expand_eval, - align_eval=args.align_eval, - diff=args.diff, - qsc=args.qsc, - max_accept=args.max_accept, - prefilter_mode=args.prefilter_mode, - s=args.s, - db_load_mode=args.db_load_mode, - threads=args.threads, - gpu=args.gpu, - gpu_server=args.gpu_server, - unpack=args.unpack, - ) - ## - print(seq_map) - - for seq_id in range(len(overall_unique_seqs)): - a3m_content = open(args.base.joinpath(f"{seq_id}.a3m"), "r").readlines() - shutil.copy(args.base.joinpath(f"{seq_id}.a3m"), args.base.joinpath(f"u-{seq_id}.a3m")) - seq_itr = 0 - header = a3m_content[0] - for seqs in seq_map: - for j, seq_index in enumerate(seqs): - if seq_index == seq_id: - new_header = f">{101 + j}\n" - with open(args.base.joinpath(f"{seq_itr}.a3m"), "w") as out_f: - for line in a3m_content: - out_f.write(line.replace(header, new_header)) - seq_itr += 1 - - - - for seq_id in range(len(overall_unique_seqs)): - os.remove(args.base.joinpath(f"u-{seq_id}.a3m")) - #exit() - ## finish monomors and keep going for hybrid batch - ## - if is_complex is True: - mmseqs_search_pair( - mmseqs=args.mmseqs, - dbbase=args.dbbase, - base=args.base, - uniref_db=args.db1, - prefilter_mode=args.prefilter_mode, - s=args.s, - db_load_mode=args.db_load_mode, - threads=args.threads, - gpu=args.gpu, - gpu_server=args.gpu_server, - pairing_strategy=args.pairing_strategy, - pair_env=False, - unpack=args.unpack, - seq_map=seq_map - ) - #exit() - if args.use_env_pairing: - mmseqs_search_pair( - mmseqs=args.mmseqs, - dbbase=args.dbbase, - base=args.base, - uniref_db=args.db1, - spire_db=args.db4, - prefilter_mode=args.prefilter_mode, - s=args.s, - db_load_mode=args.db_load_mode, - threads=args.threads, - gpu=args.gpu, - gpu_server=args.gpu_server, - pairing_strategy=args.pairing_strategy, - pair_env=True, - unpack=args.unpack, - ) - if args.unpack or args.af3_json: - id = 0 - for job_number, ( - raw_jobname, - query_sequences, - query_seqs_cardinality, - other_molecules, - ) in enumerate(queries_unique): - unpaired_msa = [] - paired_msa = None - if len(query_seqs_cardinality) > 1: - paired_msa = [] - for seq in query_sequences: - with args.base.joinpath(f"{id}.a3m").open("r") as f: - unpaired_msa.append(f.read()) - if args.af3_json: - args.base.joinpath(f"{id}.a3m").unlink() - - if args.use_env_pairing: - with open(args.base.joinpath(f"{id}.paired.a3m"), 'a') as file_pair: - with open(args.base.joinpath(f"{id}.env.paired.a3m"), 'r') as file_pair_env: - while chunk := file_pair_env.read(10 * 1024 * 1024): - file_pair.write(chunk) - if args.unpack: - args.base.joinpath(f"{id}.env.paired.a3m").unlink() - - if len(query_seqs_cardinality) > 1: - with args.base.joinpath(f"{id}.paired.a3m").open("r") as f: - paired_msa.append(f.read()) - if args.unpack: - args.base.joinpath(f"{id}.paired.a3m").unlink() - id += 1 - - if args.af3_json: - af3 = AF3Utils(raw_jobname, query_sequences, query_seqs_cardinality, unpaired_msa, paired_msa, other_molecules) - with open(args.base.joinpath(f"{job_number}.json"), 'w') as f: - f.write(json.dumps(af3.content, indent=4)) - - if args.unpack: - msa = msa_to_str( - unpaired_msa, paired_msa, query_sequences, query_seqs_cardinality - ) - args.base.joinpath(f"{job_number}.a3m").write_text(msa) - - - #os.remove(args.base.joinpath("res_exp_realign-minimal.index")) - #os.remove(args.base.joinpath("res_exp_realign-minimal")) - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("res_exp_realign-minimal")]) - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb-minimal")]) - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb-minimal_h")]) - - - - else: - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("res")]) - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("prof_res")]) - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("prof_res_h")]) - os.remove(args.base.joinpath("original-query.fas")) - - if args.af3_json: - id = 0 - for job_number, (raw_jobname, query_sequences, query_seqs_cardinality, other_molecules) in enumerate(queries_unique): - unpaired_msa = [] - for seq in query_sequences: - with args.base.joinpath(f"{id}.a3m").open("r") as f: - unpaired_msa.append(f.read()) - id += 1 - - # Create AF3Utils object and write JSON - af3 = AF3Utils(raw_jobname, query_sequences, query_seqs_cardinality, unpaired_msa, None, other_molecules) - with open(args.base.joinpath(f"{job_number}.json"), 'w') as f: - f.write(json.dumps(af3.content, indent=4)) - if args.unpack: - # rename a3m files - rename_output(queries_unique, "a3m", args.base) - - # rename m8 files - if args.use_templates: - id = 0 - for raw_jobname, query_sequences, query_seqs_cardinality, _ in queries_unique: - with args.base.joinpath(f"{safe_filename(raw_jobname)}_{args.db2}.m8").open( - "w" - ) as f: - for _ in range(len(query_seqs_cardinality)): - with args.base.joinpath(f"{id}.m8").open("r") as g: - f.write(g.read()) - os.remove(args.base.joinpath(f"{id}.m8")) - id += 1 - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb")]) - run_mmseqs(args.mmseqs, ["rmdb", args.base.joinpath("qdb_h")]) - - if args.af3_json: - # rename json files - rename_output(queries_unique, "json", args.base) - - query_file.unlink() - os.remove(args.base.joinpath("org-qdb.lookup")) - - -if __name__ == "__main__": - main() \ No newline at end of file diff --git a/conf/gadi.config b/conf/gadi.config index f90850f..8bcc1f2 100644 --- a/conf/gadi.config +++ b/conf/gadi.config @@ -24,12 +24,12 @@ params { outdir = "out-test" input = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" samplesheet2 = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" - + boltz_ccd = "/g/data/if89/proteinfold_dbs/boltz_dbs/ccd.pkl" boltz_model = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz1_conf.ckpt" colabfold_db = "/g/data/if89/proteinfold_dbs/colabfold_dbs/colabfold_envdb_202108/" colabfold_db = "/g/data/if89/proteinfold_dbs/colabfold_dbs/colabfold_envdb_202108/" - + uniref30 = "/g/data/if89/proteinfold_dbs/colabfold_dbs/uniref30_2302/" use_gpu = true project = "ll61" @@ -42,8 +42,8 @@ process { storage = "gdata/if89+scratch/${params.project}+gdata/${params.project}" withName: 'MMSEQS_COLABFOLDSEARCH' { - memory = 300.GB - time = 16.h + memory = 300.GB + time = 16.h } withName: 'RUN_BOLTZ' { cpus = 12 @@ -65,4 +65,3 @@ process { ] } - diff --git a/conf/modules.config b/conf/modules.config index c424f6d..c9549f9 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -28,7 +28,7 @@ process { } withName: 'MMSEQS_COLABFOLDSEARCH' { - memory = 300.GB + memory = 300.GB time = 16.h def args = "" if (params.mmseqs_gpu){ @@ -38,7 +38,7 @@ process { if ("${params.tools}".split(",").contains("alphafold3")){ args += "--af3-json " } - + ext.args = args } diff --git a/conf/test.config b/conf/test.config index 19aea1f..e895b00 100644 --- a/conf/test.config +++ b/conf/test.config @@ -27,5 +27,5 @@ params { // TODO nf-core: Give any required params for the test so that command line flags are not needed input = params.pipelines_testdata_base_path + 'viralrecon/samplesheet/samplesheet_test_illumina_amplicon.csv' - + } diff --git a/conf/test_gadi.config b/conf/test_gadi.config index 8892cd8..046fbe1 100644 --- a/conf/test_gadi.config +++ b/conf/test_gadi.config @@ -21,7 +21,7 @@ params { // Input data outdir = "out-test" input = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" - + boltz_ccd = "/g/data/if89/proteinfold_dbs/boltz_dbs/ccd.pkl" boltz_model = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz1_conf.ckpt" boltz2_aff = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz2_aff.ckpt" @@ -30,9 +30,9 @@ params { colabfold_db = "/g/data/if89/proteinfold_dbs/miniature_databases/colabfold_envdb_202108/" uniref30 = "/g/data/za08/tom/colabfold_uniref30" colabfold_alphafold2_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params/alphafold_params_colab_2022-12-06/" - + alphafold3_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" - + use_gpu = true project = "ll61" use_dgxa100 = false @@ -46,7 +46,7 @@ process { cache = 'lenient' stageInMode = 'symlink' queue = { task.memory < 128.GB ? 'normalbw' : (task.memory >= 128.GB && task.memory <= 190.GB ? 'normal' : (task.memory > 190.GB && task.memory <= 1020.GB ? 'hugemembw' : '')) } - + withName: 'RUN_BOLTZ' { cpus = 12 queue = "gpuvolta" @@ -64,10 +64,10 @@ process { gpus = 1 } } - + withName: 'COLABFOLD_BATCH' { queue = "gpuvolta" - time = 10.h + time = 10.h memory = 64.GB cpus = 12 gpus = 1 @@ -90,4 +90,3 @@ process { ] } - diff --git a/docs/output.md b/docs/output.md index bdce1cb..aa34f33 100644 --- a/docs/output.md +++ b/docs/output.md @@ -12,12 +12,9 @@ The directories listed below will be created in the results directory after the The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes data using the following steps: - - [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline - [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution - - ### MultiQC
diff --git a/docs/usage.md b/docs/usage.md index d4d02ac..36a8573 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -27,12 +27,12 @@ S2,Sample2.fasta,B,protein S3,S3.yaml,A,rna ``` -| Column | Description | -| --------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `id` | The `id` identifiers have to be unique in the sample sheet and **must not** have an underscore (`_`). | -| `sequence` | Full path to Fasta/YAML file for sample seqeuence. File has to have the extension ".fasta", ".fa" or "yaml". | -| `type` | The sequence type, can be either protein, rna . It is an optional column, by default it will be consdred as protein. | -| `group` | it is a way to group samnples to create custom interactions. It is an optional column, if not provided, the inteactions will be `aa-all' which means all sample against all samples. | +| Column | Description | +| ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | +| `id` | The `id` identifiers have to be unique in the sample sheet and **must not** have an underscore (`_`). | +| `sequence` | Full path to Fasta/YAML file for sample seqeuence. File has to have the extension ".fasta", ".fa" or "yaml". | +| `type` | The sequence type, can be either protein, rna . It is an optional column, by default it will be consdred as protein. | +| `group` | it is a way to group samnples to create custom interactions. It is an optional column, if not provided, the inteactions will be `aa-all' which means all sample against all samples. | An [example samplesheet](../assets/samplesheet.csv) has been provided with the pipeline. diff --git a/main.nf b/main.nf index 86ff548..f1c1fc9 100644 --- a/main.nf +++ b/main.nf @@ -39,7 +39,7 @@ workflow NFCORE_WISPS { // // WORKFLOW: Run pipeline // - + WISPS ( ch_samplesheet, params.mode, @@ -65,7 +65,7 @@ workflow NFCORE_WISPS { params.analysis_batch_size ) ch_versions = ch_versions.mix(WISPS.out.versions) - + emit: multiqc_report //= WISPS.out.multiqc_report // channel: /path/to/multiqc_report.html } diff --git a/modules/local/colabfold_batch/main.nf b/modules/local/colabfold_batch/main.nf index 82f9513..0e17128 100644 --- a/modules/local/colabfold_batch/main.nf +++ b/modules/local/colabfold_batch/main.nf @@ -40,7 +40,7 @@ process COLABFOLD_BATCH { --model-type ${colabfold_model_preset} \\ alignment \\ \$PWD - + cat <<-END_VERSIONS > versions.yml "${task.process}": colabfold_batch: \$(pip list | grep "^colabfold" | awk '{print \$2}') @@ -54,7 +54,7 @@ process COLABFOLD_BATCH { touch ./${meta.id}_relaxed_rank_model_3_00.pdb touch ./${meta.id}_coverage.png touch ./${meta.id}_scores_rank_001_00.json - + cat <<-END_VERSIONS > versions.yml "${task.process}": colabfold_batch: \$(pip list | grep "^colabfold" | awk '{print \$2}') diff --git a/modules/local/collect_confidence.nf b/modules/local/collect_confidence.nf index bf9b5ad..2d8998c 100644 --- a/modules/local/collect_confidence.nf +++ b/modules/local/collect_confidence.nf @@ -22,7 +22,7 @@ process COLLECT_CONFIDENCE { """ #!/usr/bin/env python3 - + import os, sys import json import csv @@ -63,7 +63,7 @@ process COLLECT_CONFIDENCE { writer.writeheader() for row in rows: writer.writerow({key: row.get(key, "") for key in writing_keys}) - + def extract_colabfold_results(json_files, samples, output_csv): def parse_colabfold_metrics(json_file): with open(json_file, "r") as f: @@ -83,7 +83,7 @@ process COLLECT_CONFIDENCE { result[key] = data[key] return result - + rows = [] all_keys = ["id", "plddt", "ptm", "iptm", "max_pae"] writing_keys = all_keys @@ -101,19 +101,19 @@ process COLLECT_CONFIDENCE { for row in rows: writer.writerow({key: row.get(key, "") for key in writing_keys}) - - + + if "${meta.model}".lower() == "boltz": extract_boltz_results(json_files, samples, output_csv) elif "${meta.model}".lower() == "colabfold": extract_colabfold_results(json_files, samples, output_csv) elif "${meta.model}".lower() == "alphafold3": extract_alphafold3_results(json_files, samples, output_csv) - + print(f"CSV file created at: {output_csv}") with open ("versions.yml", "w") as version_file: - version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) + version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) """ stub: diff --git a/modules/local/mmseqs_colabfoldsearch/main.nf b/modules/local/mmseqs_colabfoldsearch/main.nf index 232f42a..0e6a450 100644 --- a/modules/local/mmseqs_colabfoldsearch/main.nf +++ b/modules/local/mmseqs_colabfoldsearch/main.nf @@ -64,7 +64,7 @@ process MMSEQS_COLABFOLDSEARCH { else touch results/${meta.id}.a3m fi - + cat <<-END_VERSIONS > versions.yml "${task.process}": colabfold_search: \$(conda run -n colabfold pip list | grep "^colabfold" | awk '{print \$2}') @@ -72,4 +72,4 @@ process MMSEQS_COLABFOLDSEARCH { mmseqs: \$(mmseqs version) END_VERSIONS """ -} \ No newline at end of file +} diff --git a/modules/local/msa_manager/split_msa.nf b/modules/local/msa_manager/split_msa.nf index dad42e5..075b28d 100644 --- a/modules/local/msa_manager/split_msa.nf +++ b/modules/local/msa_manager/split_msa.nf @@ -24,9 +24,9 @@ process SPLIT_MSA { for f in "\${files[@]}"; do meta_id=\$(basename "\$f" ".a3m") - msa_manager.py \$f -o output_msa --meta_id "\${meta_id}" + msa_manager.py \$f -o output_msa --meta_id "\${meta_id}" done - + cat <<-END_VERSIONS > versions.yml "${task.process}": diff --git a/modules/local/prepare_interactions.nf b/modules/local/prepare_interactions.nf index da41840..6be245e 100644 --- a/modules/local/prepare_interactions.nf +++ b/modules/local/prepare_interactions.nf @@ -13,7 +13,7 @@ process PREPARE_INTERACTIONS { val(a3m) val(types) path(files) - + output: tuple val(meta), path ("*_boltz_interaction_input.fasta"), emit: fasta path "versions.yml" , emit: versions @@ -32,14 +32,14 @@ process PREPARE_INTERACTIONS { fasta_files_batch = ${fasta.collect { inner -> inner.collect { "\"${it}\"" }}.toString()} a3m_files_batch = ${a3m.collect { inner -> inner.collect { "\"${it}\"" }}.toString()} seq_types_batch = ${types.collect { inner -> inner.collect { "\"${it}\"" }}.toString()} - + all_combinations = list(string.ascii_uppercase) + list(string.ascii_lowercase) + [str(x) for x in range(0, 10)] batch_itr = 0 for batch_itr in range(len(fasta_files_batch)): a3m_files = a3m_files_batch[batch_itr] seq_types = seq_types_batch[batch_itr] fasta_files = fasta_files_batch[batch_itr] - + for seq_type in seq_types: if seq_type not in {"protein", "dna", "rna", "smiles", "ccd"}: print(f'seqeuence type should be ["protein", "dna", "rna", "smiles", "ccd"], found {seq_type}!') @@ -67,12 +67,12 @@ process PREPARE_INTERACTIONS { header += f"|{os.path.basename(a3m)}\\n" else: header += "\\n" - + outfile.write(header) outfile.writelines(body) with open ("versions.yml", "w") as version_file: - version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) + version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) """ stub: diff --git a/modules/local/run_alphafold3/main.nf b/modules/local/run_alphafold3/main.nf index becd1be..fdce44c 100644 --- a/modules/local/run_alphafold3/main.nf +++ b/modules/local/run_alphafold3/main.nf @@ -30,13 +30,13 @@ process RUN_ALPHAFOLD3 { --norun_data_pipeline \\ --output_dir=out/ \\ $args - + cat <<-END_VERSIONS > versions.yml "${task.process}": python: \$(python3 --version | sed 's/Python //g') END_VERSIONS """ - + stub: def prefix = task.ext.prefix ?: "${meta.id}" """ diff --git a/modules/local/run_boltz/main.nf b/modules/local/run_boltz/main.nf index 9c24533..5bb3a76 100644 --- a/modules/local/run_boltz/main.nf +++ b/modules/local/run_boltz/main.nf @@ -25,7 +25,7 @@ process RUN_BOLTZ { tuple val(meta), path ("boltz_results_*/predictions/*/*model_0.cif") , optional: true, emit: cif tuple val(meta), path ("boltz_results_*/predictions/*/plddt_*model_0.npz") , emit: plddt tuple val(meta), path ("boltz_results_*/predictions/*/pae_*model_0.npz") , optional: true, emit: pae - + path "versions.yml", emit: versions when: @@ -43,7 +43,7 @@ process RUN_BOLTZ { export HOME=/tmp boltz predict fasta ${args} --cache ./ - + cat <<-END_VERSIONS > versions.yml "${task.process}": boltz: $version diff --git a/modules/nf-core/multiqc/tests/main.nf.test.snap b/modules/nf-core/multiqc/tests/main.nf.test.snap index 2fcbb5f..261dc0f 100644 --- a/modules/nf-core/multiqc/tests/main.nf.test.snap +++ b/modules/nf-core/multiqc/tests/main.nf.test.snap @@ -38,4 +38,4 @@ }, "timestamp": "2024-10-02T17:52:09.185842" } -} \ No newline at end of file +} diff --git a/nextflow.config b/nextflow.config index f8367ed..01f21a6 100644 --- a/nextflow.config +++ b/nextflow.config @@ -16,14 +16,14 @@ params { mmseqs_batch_size = 10000 mmseqs_gpu = false analysis_batch_size = 10000 - + colabfold_model_preset = "alphafold2_multimer_v3" colabfold_num_recycles = 3 tools = "boltz,colabfold" - + ipsae_pae_cutoff = 10 ipsae_dist_cutoff = 10 - + boltz_ccd = 'https://huggingface.co/boltz-community/boltz-1/resolve/main/ccd.pkl' boltz_model = 'https://huggingface.co/boltz-community/boltz-1/resolve/main/boltz1_conf.ckpt' boltz2_aff = 'https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_aff.ckpt' diff --git a/nextflow_schema.json b/nextflow_schema.json index 7625b99..7ceec30 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -116,31 +116,26 @@ "description": "Dictionary with Alphafold2 parameters tags", "fa_icon": "fas fa-stream" }, - "boltz_db": { - "type": "string", - "description": "Path to boltz databases", - "icon": "fas folder-open" - }, "boltz_ccd": { "type": "string", "description": "Path to CCD file", "icon": "fas folder-open", - "default": "null/params/ccd.pkl" + "default": "https://huggingface.co/boltz-community/boltz-1/resolve/main/ccd.pkl" }, "boltz_model": { "type": "string", "description": "Path to boltz Model file", "icon": "fas folder-open", - "default": "null/params/boltz1_conf.ckpt" + "default": "https://huggingface.co/boltz-community/boltz-1/resolve/main/boltz1_conf.ckpt" }, "boltz2_aff": { "type": "string", - "default": "null/params/boltz2_aff.ckpt", + "default": "https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_aff.ckpt", "description": "Path to boltz affinity file" }, "boltz2_conf": { "type": "string", - "default": "null/params/boltz2_conf.ckpt", + "default": "https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_conf.ckpt", "description": "Path to boltz-2 conf file" }, "boltz2_mols": { @@ -189,15 +184,14 @@ "description": "The pae cutoff for ipsae.", "fa_icon": "fas fa-recycle", "errorMessage": "The pae cutoff for ipsae." - },"ipsae_dist_cutoff": { + }, + "ipsae_dist_cutoff": { "type": "integer", "default": 10, "description": "The dist cutoff for ipsae.", "fa_icon": "fas fa-recycle", "errorMessage": "" } - - } }, "institutional_config_options": { diff --git a/subworkflows/local/msa.nf b/subworkflows/local/msa.nf index b32acc0..5759134 100644 --- a/subworkflows/local/msa.nf +++ b/subworkflows/local/msa.nf @@ -12,14 +12,14 @@ workflow MSA { take: ch_samplesheet ch_colabfold_db // channel: path(colabfold_db) - ch_uniref30 // channel: path(uniref30) + ch_uniref30 // channel: path(uniref30) batch_size - + main: ch_versions = Channel.empty() ch_a3m = Channel.empty() ch_json = Channel.empty() - + ch_samplesheet .branch { fasta: it[1].extension == "fasta" || it[1].extension == "fa" @@ -33,10 +33,10 @@ workflow MSA { [it[0], "${it[0].id},${getYamlSequences(it[1].text).collect { it.sequence }.join(':')}"] } .set{ch_yaml_seqs} - + if (batch_size > 1){ def batch_itr = 0 - + ch_input.fasta .map{ "${it[0].id},${getFastaSequences(it[1].text).collect { it.sequence }.join(':')}" @@ -73,7 +73,7 @@ workflow MSA { ch_uniref30 ) ch_versions = ch_versions.mix(MMSEQS_COLABFOLDSEARCH.out.versions) - + ch_a3m = ch_a3m.mix( ch_input.fasta.mix(ch_input.yaml) .map{[it[1].baseName, it[0]]} @@ -99,8 +99,8 @@ workflow MSA { .map{[it[1], it[2]]} ) //MMSEQS_COLABFOLDSEARCH.out.a3m.view() - //ch_a3m.view() - + //ch_a3m.view() + emit: formated_input = ch_input.fasta.mix(ch_input.yaml) a3m = ch_a3m @@ -167,4 +167,4 @@ def getFastaSequences(fastaData) { } return fastaEntries -} \ No newline at end of file +} diff --git a/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf b/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf index 9a5b9c4..dc63ab9 100644 --- a/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf +++ b/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf @@ -68,7 +68,7 @@ workflow PIPELINE_INITIALISATION { // ch_samplesheet = Channel.fromList(samplesheetToList(params.input, "assets/schema_input.json")) - + emit: samplesheet = ch_samplesheet versions = ch_versions @@ -150,7 +150,7 @@ def toolCitationText() { // Uncomment function in methodsDescriptionText to render in MultiQC report def citation_text = [ "Tools used in the workflow included:", - + "MultiQC (Ewels et al. 2016)", "." ].join(' ').trim() @@ -163,7 +163,7 @@ def toolBibliographyText() { // Can use ternary operators to dynamically construct based conditions, e.g. params["run_xyz"] ? "
  • Author (2023) Pub name, Journal, DOI
    • " : "", // Uncomment function in methodsDescriptionText to render in MultiQC report def reference_text = [ - + "
  • Ewels, P., Magnusson, M., Lundin, S., & Käller, M. (2016). MultiQC: summarize analysis results for multiple tools and samples in a single report. Bioinformatics , 32(19), 3047–3048. doi: /10.1093/bioinformatics/btw354
    • " ].join(' ').trim() diff --git a/subworkflows/nf-core/utils_nextflow_pipeline/tests/main.function.nf.test.snap b/subworkflows/nf-core/utils_nextflow_pipeline/tests/main.function.nf.test.snap index e3f0baf..846287c 100644 --- a/subworkflows/nf-core/utils_nextflow_pipeline/tests/main.function.nf.test.snap +++ b/subworkflows/nf-core/utils_nextflow_pipeline/tests/main.function.nf.test.snap @@ -17,4 +17,4 @@ }, "timestamp": "2024-02-28T12:02:12.425833" } -} \ No newline at end of file +} diff --git a/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.function.nf.test.snap b/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.function.nf.test.snap index 1037232..facbdcf 100644 --- a/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.function.nf.test.snap +++ b/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.function.nf.test.snap @@ -163,4 +163,4 @@ }, "timestamp": "2024-02-28T12:03:21.714424" } -} \ No newline at end of file +} diff --git a/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.workflow.nf.test.snap b/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.workflow.nf.test.snap index 859d103..84ee1e1 100644 --- a/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.workflow.nf.test.snap +++ b/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.workflow.nf.test.snap @@ -16,4 +16,4 @@ }, "timestamp": "2024-02-28T12:03:25.726491" } -} \ No newline at end of file +} diff --git a/subworkflows/nf-core/utils_nfschema_plugin/main.nf b/subworkflows/nf-core/utils_nfschema_plugin/main.nf index 4994303..93de2a5 100644 --- a/subworkflows/nf-core/utils_nfschema_plugin/main.nf +++ b/subworkflows/nf-core/utils_nfschema_plugin/main.nf @@ -43,4 +43,3 @@ workflow UTILS_NFSCHEMA_PLUGIN { emit: dummy_emit = true } - diff --git a/subworkflows/nf-core/utils_nfschema_plugin/tests/nextflow.config b/subworkflows/nf-core/utils_nfschema_plugin/tests/nextflow.config index 0907ac5..478fb8a 100644 --- a/subworkflows/nf-core/utils_nfschema_plugin/tests/nextflow.config +++ b/subworkflows/nf-core/utils_nfschema_plugin/tests/nextflow.config @@ -5,4 +5,4 @@ plugins { validation { parametersSchema = "${projectDir}/subworkflows/nf-core/utils_nfschema_plugin/tests/nextflow_schema.json" monochromeLogs = true -} \ No newline at end of file +} diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 75b4d1a..eece1a9 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -54,7 +54,7 @@ include { getYamlSequences } from '../subworkflows/local/msa' */ workflow WISPS { - + take: ch_samplesheet mode @@ -82,7 +82,7 @@ workflow WISPS { main: ch_multiqc_files = Channel.empty() ch_confidence_scores = Channel.empty() - + interaction_mode = mode.split(",").collect { pair -> pair.split('-').sort().join('-') @@ -99,7 +99,7 @@ workflow WISPS { emitted -> { if (required - emitted){ log.error "The groups ${required - emitted} is not in the sample sheet!" - exit 1 + exit 1 } } } @@ -118,14 +118,14 @@ workflow WISPS { ch_samplesheet .combine(ch_samplesheet) .map{[ - [ + [ "id": [it[0]["id"], it[2]["id"]].min() + "-" + [it[0]["id"], it[2]["id"]].max(), "group": [it[0]["group"], it[2]["group"]].min() + "-" + [it[0]["group"], it[2]["group"]].max(), ], [it[0], it[2]], [it[1], it[3]], ]}.set{ch_pairs} - + ch_pairs .join(ch_unique_pairs) .set{ch_interaction_in} @@ -150,13 +150,13 @@ workflow WISPS { ch_interaction_in .map{ if (it[1][0].type != "protein" && it[1][1].type == "protein"){ - [it[1][1], it[2][1]] + [it[1][1], it[2][1]] }else if (it[1][1].type != "protein" && it[1][0].type == "protein"){ - [it[1][0], it[2][0]] + [it[1][0], it[2][0]] } }.unique() .set{ch_single_protein} - + //ch_protein_pairs.view() MSA ( ch_protein_pairs @@ -168,7 +168,7 @@ workflow WISPS { mmseqs_batch_size ) ch_versions = ch_versions.mix(MSA.out.versions) - + // Prepare interactions for boltz ch_boltz_data = Channel.empty() ch_split_msa_in = Channel.empty() @@ -176,7 +176,7 @@ workflow WISPS { if ("boltz" in tools.split(",")){ ch_split_msa_in = MSA.out.a3m.join(ch_protein_pairs.map{it[0]}) - ch_boltz_interactions_in = ch_interaction_in + ch_boltz_interactions_in = ch_interaction_in } // Adding non protein for boltz @@ -214,7 +214,7 @@ workflow WISPS { ) ch_versions = ch_versions.mix(SPLIT_MSA.out.versions) - + SPLIT_MSA.out.msa_csv .map{it[1]} .flatten() @@ -230,15 +230,15 @@ workflow WISPS { ch_split_msa_out .map{ if (it[1].size() == 1){ - it[1] = [it[1][0], it[1][0]] + it[1] = [it[1][0], it[1][0]] } it } - + ) .map{[it[1], it[2]]} ) - + batch_id = 0 PREPARE_INTERACTIONS( @@ -259,7 +259,7 @@ workflow WISPS { .map{[it[0][2][0], it[0][2][1], it[1][0], it[1][1]]} .buffer( size: analysis_batch_size, remainder: true ) .map{it.flatten()findAll{it}.unique{it.toUriString()}} - + ) PREPARE_INTERACTIONS.out.fasta @@ -274,7 +274,7 @@ workflow WISPS { .set{ch_boltz_in} boltz_batch = 0 - + RUN_BOLTZ( ch_boltz_in.map{boltz_batch += 1; [["id": "batch-${boltz_batch}-${it.size()}"], it.collect{it[1]}]}, ch_boltz_in.map{it.collect{it[2]}.flatten().findAll{it}.unique{it.toUriString()}}, @@ -284,20 +284,20 @@ workflow WISPS { ch_boltz2_conf, ch_mols ) - + RUN_BOLTZ.out.confidence .map{it[1]} .flatten() .map{[["id": it.baseName.split("_")[1], "model": "boltz"], it]} .set{ch_boltz_confidence} - + RUN_BOLTZ.out.pae .map{it[1]} .flatten() .map{[["id": it.baseName.split("_")[1], "model": "boltz"], it]} .set{ch_boltz_pae} - + RUN_BOLTZ.out.cif .map{it[1]} .flatten() @@ -309,7 +309,7 @@ workflow WISPS { ids: json_list.collect{it[0].id} json: json_list.collect{it[1]} }.set{ch_boltz_confidence_scores} - + //prepare interactions for colabfold ch_colabfold_interaction_in = Channel.empty() if ("colabfold" in tools.split(",")){ @@ -325,7 +325,7 @@ workflow WISPS { ch_colabfold_interaction_in } } - + COLABFOLD_BATCH( ch_colabfold_interaction_in, colabfold_model_preset, @@ -335,13 +335,13 @@ workflow WISPS { num_recycles ) ch_versions = ch_versions.mix(COLABFOLD_BATCH.out.versions) - + COLABFOLD_BATCH.out.top_ranked_scores .map{it[1]} .flatten() .map{[["id": it.baseName.split("_")[0], "model": "colabfold"], it]} .set{ch_colabfold_scores} - + COLABFOLD_BATCH.out.pdb .map{it[1]} .flatten() @@ -355,7 +355,7 @@ workflow WISPS { json: json_list.collect{it[1]} }.set{ch_colabfold_confidence_scores} - + af3_batch = 0 ch_alphafold3_interaction_in = Channel.empty() if ("alphafold3" in tools.split(",")){ @@ -382,13 +382,13 @@ workflow WISPS { .flatten() .map{[["id": it.baseName.split("_")[0], "model": "alphafold3"], it]} .set{ch_alphafold3_cif} - + RUN_ALPHAFOLD3.out.confidence .map{it[1]} .flatten() .map{[["id": it.baseName.split("_")[0], "model": "alphafold3"], it]} .set{ch_alphafold3_confidence} - + RUN_ALPHAFOLD3.out.summary_confidences .map{it[1]} .flatten() @@ -401,7 +401,7 @@ workflow WISPS { json: json_list.collect{it[1]} }.set{ch_alphafold3_confidence_scores} - + ch_colabfold_scores .join(ch_colabfold_pdb) .map{[["id": it[0].id], it, []]} @@ -428,7 +428,7 @@ workflow WISPS { ) ) .set{ch_ipsae_in} - + IPSAE( ch_ipsae_in.map{it[1]}, ch_ipsae_in.map{it[2]} @@ -451,8 +451,8 @@ workflow WISPS { ) ch_versions = ch_versions.mix(COLLECT_CONFIDENCE.out.versions) - - + + // // Collate and save software versions // @@ -495,5 +495,5 @@ workflow WISPS { emit: versions = ch_versions - -} + +} From 46d0b3609215af7a8c4a1d08c38ff9839fa76870 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Tue, 7 Oct 2025 11:56:53 +1100 Subject: [PATCH 20/70] cleaning --- .pre-commit-config.yaml | 4 +--- 1 file changed, 1 insertion(+), 3 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 13f7acf..25f0509 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -12,9 +12,7 @@ repos: - id: editorconfig-checker alias: ec - repo: https://github.com/pre-commit/pre-commit-hooks - rev: v4.5.0 + rev: v6.0.0 hooks: - id: trailing-whitespace - id: end-of-file-fixer - - id: check-yaml - - id: check-json From 2811c4edc51d600d868bf0cd08c66348f4d9b52d Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Tue, 7 Oct 2025 12:02:18 +1100 Subject: [PATCH 21/70] fix config formats --- nextflow_schema.json | 13 ++----------- 1 file changed, 2 insertions(+), 11 deletions(-) diff --git a/nextflow_schema.json b/nextflow_schema.json index 7ceec30..5b5b7f2 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -97,25 +97,18 @@ "uniref30": { "type": "string", "description": "Link to the UniRef30 database", - "fa_icon": "fas fa-folder-open", - "default": "null/colabfold_uniref30/*" + "fa_icon": "fas fa-folder-open" }, "colabfold_envdb": { "type": "string", "description": "Link to the ColabFold database", - "fa_icon": "fas fa-folder-open", - "default": "null/colabfold_envdb/*" + "fa_icon": "fas fa-folder-open" }, "colabfold_alphafold2_params": { "type": "string", "description": "Link to the Alphafold2 parameters for Colabfold", "fa_icon": "fas fa-folder-open" }, - "colabfold_alphafold2_params_tags": { - "type": "object", - "description": "Dictionary with Alphafold2 parameters tags", - "fa_icon": "fas fa-stream" - }, "boltz_ccd": { "type": "string", "description": "Path to CCD file", @@ -140,12 +133,10 @@ }, "boltz2_mols": { "type": "string", - "default": "null/params/mols/", "description": "Path to boltz-2 mols" }, "alphafold3_params": { "type": "string", - "default": "null/params//", "description": "Path to Alphafold3 params" } } From 43d7b7c81eff452b868e43e6a7456f20ce0be1d6 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Tue, 7 Oct 2025 13:01:59 +1100 Subject: [PATCH 22/70] cleaning + formatting --- modules.json | 6 +- nextflow.config | 2 + .../nf-core/utils_nextflow_pipeline/main.nf | 2 + .../tests/main.workflow.nf.test | 10 ++- .../utils_nextflow_pipeline/tests/tags.yml | 2 - .../nf-core/utils_nfcore_pipeline/main.nf | 89 +++++-------------- .../tests/main.function.nf.test | 46 ++++------ .../tests/main.function.nf.test.snap | 30 ------- .../utils_nfcore_pipeline/tests/tags.yml | 2 - .../nf-core/utils_nfschema_plugin/main.nf | 40 +++++++-- .../utils_nfschema_plugin/tests/main.nf.test | 60 ++++++++++++- .../tests/nextflow.config | 2 +- 12 files changed, 148 insertions(+), 143 deletions(-) delete mode 100644 subworkflows/nf-core/utils_nextflow_pipeline/tests/tags.yml delete mode 100644 subworkflows/nf-core/utils_nfcore_pipeline/tests/tags.yml diff --git a/modules.json b/modules.json index d6c6736..b75bd10 100644 --- a/modules.json +++ b/modules.json @@ -16,17 +16,17 @@ "nf-core": { "utils_nextflow_pipeline": { "branch": "master", - "git_sha": "3aa0aec1d52d492fe241919f0c6100ebf0074082", + "git_sha": "05954dab2ff481bcb999f24455da29a5828af08d", "installed_by": ["subworkflows"] }, "utils_nfcore_pipeline": { "branch": "master", - "git_sha": "1b6b9a3338d011367137808b49b923515080e3ba", + "git_sha": "05954dab2ff481bcb999f24455da29a5828af08d", "installed_by": ["subworkflows"] }, "utils_nfschema_plugin": { "branch": "master", - "git_sha": "bbd5a41f4535a8defafe6080e00ea74c45f4f96c", + "git_sha": "4b406a74dc0449c0401ed87d5bfff4252fd277fd", "installed_by": ["subworkflows"] } } diff --git a/nextflow.config b/nextflow.config index 01f21a6..eb26971 100644 --- a/nextflow.config +++ b/nextflow.config @@ -15,6 +15,7 @@ params { mode = "all-all" mmseqs_batch_size = 10000 mmseqs_gpu = false + use_gpu = true analysis_batch_size = 10000 colabfold_model_preset = "alphafold2_multimer_v3" @@ -33,6 +34,7 @@ params { colabfold_db = null uniref30 = null colabfold_alphafold2_params = null + colabfold_envdb = null alphafold3_params = null // MultiQC options diff --git a/subworkflows/nf-core/utils_nextflow_pipeline/main.nf b/subworkflows/nf-core/utils_nextflow_pipeline/main.nf index 0fcbf7b..d6e593e 100644 --- a/subworkflows/nf-core/utils_nextflow_pipeline/main.nf +++ b/subworkflows/nf-core/utils_nextflow_pipeline/main.nf @@ -92,10 +92,12 @@ def checkCondaChannels() { channels = config.channels } catch (NullPointerException e) { + log.debug(e) log.warn("Could not verify conda channel configuration.") return null } catch (IOException e) { + log.debug(e) log.warn("Could not verify conda channel configuration.") return null } diff --git a/subworkflows/nf-core/utils_nextflow_pipeline/tests/main.workflow.nf.test b/subworkflows/nf-core/utils_nextflow_pipeline/tests/main.workflow.nf.test index ca964ce..02dbf09 100644 --- a/subworkflows/nf-core/utils_nextflow_pipeline/tests/main.workflow.nf.test +++ b/subworkflows/nf-core/utils_nextflow_pipeline/tests/main.workflow.nf.test @@ -52,10 +52,12 @@ nextflow_workflow { } then { - assertAll( - { assert workflow.success }, - { assert workflow.stdout.contains("nextflow_workflow v9.9.9") } - ) + expect { + with(workflow) { + assert success + assert "nextflow_workflow v9.9.9" in stdout + } + } } } diff --git a/subworkflows/nf-core/utils_nextflow_pipeline/tests/tags.yml b/subworkflows/nf-core/utils_nextflow_pipeline/tests/tags.yml deleted file mode 100644 index f847611..0000000 --- a/subworkflows/nf-core/utils_nextflow_pipeline/tests/tags.yml +++ /dev/null @@ -1,2 +0,0 @@ -subworkflows/utils_nextflow_pipeline: - - subworkflows/nf-core/utils_nextflow_pipeline/** diff --git a/subworkflows/nf-core/utils_nfcore_pipeline/main.nf b/subworkflows/nf-core/utils_nfcore_pipeline/main.nf index 5cb7baf..bfd2587 100644 --- a/subworkflows/nf-core/utils_nfcore_pipeline/main.nf +++ b/subworkflows/nf-core/utils_nfcore_pipeline/main.nf @@ -56,21 +56,6 @@ def checkProfileProvided(nextflow_cli_args) { } } -// -// Citation string for pipeline -// -def workflowCitation() { - def temp_doi_ref = "" - def manifest_doi = workflow.manifest.doi.tokenize(",") - // Handling multiple DOIs - // Removing `https://doi.org/` to handle pipelines using DOIs vs DOI resolvers - // Removing ` ` since the manifest.doi is a string and not a proper list - manifest_doi.each { doi_ref -> - temp_doi_ref += " https://doi.org/${doi_ref.replace('https://doi.org/', '').replace(' ', '')}\n" - } - return "If you use ${workflow.manifest.name} for your analysis please cite:\n\n" + "* The pipeline\n" + temp_doi_ref + "\n" + "* The nf-core framework\n" + " https://doi.org/10.1038/s41587-020-0439-x\n\n" + "* Software dependencies\n" + " https://github.com/${workflow.manifest.name}/blob/master/CITATIONS.md" -} - // // Generate workflow version string // @@ -150,33 +135,6 @@ def paramsSummaryMultiqc(summary_params) { return yaml_file_text } -// -// nf-core logo -// -def nfCoreLogo(monochrome_logs=true) { - def colors = logColours(monochrome_logs) as Map - String.format( - """\n - ${dashedLine(monochrome_logs)} - ${colors.green},--.${colors.black}/${colors.green},-.${colors.reset} - ${colors.blue} ___ __ __ __ ___ ${colors.green}/,-._.--~\'${colors.reset} - ${colors.blue} |\\ | |__ __ / ` / \\ |__) |__ ${colors.yellow}} {${colors.reset} - ${colors.blue} | \\| | \\__, \\__/ | \\ |___ ${colors.green}\\`-._,-`-,${colors.reset} - ${colors.green}`._,._,\'${colors.reset} - ${colors.purple} ${workflow.manifest.name} ${getWorkflowVersion()}${colors.reset} - ${dashedLine(monochrome_logs)} - """.stripIndent() - ) -} - -// -// Return dashed line -// -def dashedLine(monochrome_logs=true) { - def colors = logColours(monochrome_logs) as Map - return "-${colors.dim}----------------------------------------------------${colors.reset}-" -} - // // ANSII colours used for terminal logging // @@ -245,28 +203,24 @@ def logColours(monochrome_logs=true) { return colorcodes } -// -// Attach the multiqc report to email -// -def attachMultiqcReport(multiqc_report) { - def mqc_report = null - try { - if (workflow.success) { - mqc_report = multiqc_report.getVal() - if (mqc_report.getClass() == ArrayList && mqc_report.size() >= 1) { - if (mqc_report.size() > 1) { - log.warn("[${workflow.manifest.name}] Found multiple reports from process 'MULTIQC', will use only one") - } - mqc_report = mqc_report[0] - } +// Return a single report from an object that may be a Path or List +// +def getSingleReport(multiqc_reports) { + if (multiqc_reports instanceof Path) { + return multiqc_reports + } else if (multiqc_reports instanceof List) { + if (multiqc_reports.size() == 0) { + log.warn("[${workflow.manifest.name}] No reports found from process 'MULTIQC'") + return null + } else if (multiqc_reports.size() == 1) { + return multiqc_reports.first() + } else { + log.warn("[${workflow.manifest.name}] Found multiple reports from process 'MULTIQC', will use only one") + return multiqc_reports.first() } + } else { + return null } - catch (Exception all) { - if (multiqc_report) { - log.warn("[${workflow.manifest.name}] Could not attach MultiQC report to summary email") - } - } - return mqc_report } // @@ -320,7 +274,7 @@ def completionEmail(summary_params, email, email_on_fail, plaintext_email, outdi email_fields['summary'] = summary << misc_fields // On success try attach the multiqc report - def mqc_report = attachMultiqcReport(multiqc_report) + def mqc_report = getSingleReport(multiqc_report) // Check if we are only sending emails on failure def email_address = email @@ -340,7 +294,7 @@ def completionEmail(summary_params, email, email_on_fail, plaintext_email, outdi def email_html = html_template.toString() // Render the sendmail template - def max_multiqc_email_size = (params.containsKey('max_multiqc_email_size') ? params.max_multiqc_email_size : 0) as nextflow.util.MemoryUnit + def max_multiqc_email_size = (params.containsKey('max_multiqc_email_size') ? params.max_multiqc_email_size : 0) as MemoryUnit def smail_fields = [email: email_address, subject: subject, email_txt: email_txt, email_html: email_html, projectDir: "${workflow.projectDir}", mqcFile: mqc_report, mqcMaxSize: max_multiqc_email_size.toBytes()] def sf = new File("${workflow.projectDir}/assets/sendmail_template.txt") def sendmail_template = engine.createTemplate(sf).make(smail_fields) @@ -351,14 +305,17 @@ def completionEmail(summary_params, email, email_on_fail, plaintext_email, outdi if (email_address) { try { if (plaintext_email) { -new org.codehaus.groovy.GroovyException('Send plaintext e-mail, not HTML') } + new org.codehaus.groovy.GroovyException('Send plaintext e-mail, not HTML') + } // Try to send HTML e-mail using sendmail def sendmail_tf = new File(workflow.launchDir.toString(), ".sendmail_tmp.html") sendmail_tf.withWriter { w -> w << sendmail_html } ['sendmail', '-t'].execute() << sendmail_html log.info("-${colors.purple}[${workflow.manifest.name}]${colors.green} Sent summary e-mail to ${email_address} (sendmail)-") } - catch (Exception all) { + catch (Exception msg) { + log.debug(msg.toString()) + log.debug("Trying with mail instead of sendmail") // Catch failures and try with plaintext def mail_cmd = ['mail', '-s', subject, '--content-type=text/html', email_address] mail_cmd.execute() << email_html diff --git a/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.function.nf.test b/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.function.nf.test index 1dc317f..f117040 100644 --- a/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.function.nf.test +++ b/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.function.nf.test @@ -41,26 +41,14 @@ nextflow_function { } } - test("Test Function workflowCitation") { - - function "workflowCitation" - - then { - assertAll( - { assert function.success }, - { assert snapshot(function.result).match() } - ) - } - } - - test("Test Function nfCoreLogo") { + test("Test Function without logColours") { - function "nfCoreLogo" + function "logColours" when { function { """ - input[0] = false + input[0] = true """ } } @@ -73,9 +61,8 @@ nextflow_function { } } - test("Test Function dashedLine") { - - function "dashedLine" + test("Test Function with logColours") { + function "logColours" when { function { @@ -93,14 +80,13 @@ nextflow_function { } } - test("Test Function without logColours") { - - function "logColours" + test("Test Function getSingleReport with a single file") { + function "getSingleReport" when { function { """ - input[0] = true + input[0] = file(params.modules_testdata_base_path + '/generic/tsv/test.tsv', checkIfExists: true) """ } } @@ -108,18 +94,22 @@ nextflow_function { then { assertAll( { assert function.success }, - { assert snapshot(function.result).match() } + { assert function.result.contains("test.tsv") } ) } } - test("Test Function with logColours") { - function "logColours" + test("Test Function getSingleReport with multiple files") { + function "getSingleReport" when { function { """ - input[0] = false + input[0] = [ + file(params.modules_testdata_base_path + '/generic/tsv/test.tsv', checkIfExists: true), + file(params.modules_testdata_base_path + '/generic/tsv/network.tsv', checkIfExists: true), + file(params.modules_testdata_base_path + '/generic/tsv/expression.tsv', checkIfExists: true) + ] """ } } @@ -127,7 +117,9 @@ nextflow_function { then { assertAll( { assert function.success }, - { assert snapshot(function.result).match() } + { assert function.result.contains("test.tsv") }, + { assert !function.result.contains("network.tsv") }, + { assert !function.result.contains("expression.tsv") } ) } } diff --git a/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.function.nf.test.snap b/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.function.nf.test.snap index facbdcf..b13b311 100644 --- a/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.function.nf.test.snap +++ b/subworkflows/nf-core/utils_nfcore_pipeline/tests/main.function.nf.test.snap @@ -17,26 +17,6 @@ }, "timestamp": "2024-02-28T12:02:59.729647" }, - "Test Function nfCoreLogo": { - "content": [ - "\n\n-\u001b[2m----------------------------------------------------\u001b[0m-\n \u001b[0;32m,--.\u001b[0;30m/\u001b[0;32m,-.\u001b[0m\n\u001b[0;34m ___ __ __ __ ___ \u001b[0;32m/,-._.--~'\u001b[0m\n\u001b[0;34m |\\ | |__ __ / ` / \\ |__) |__ \u001b[0;33m} {\u001b[0m\n\u001b[0;34m | \\| | \\__, \\__/ | \\ |___ \u001b[0;32m\\`-._,-`-,\u001b[0m\n \u001b[0;32m`._,._,'\u001b[0m\n\u001b[0;35m nextflow_workflow v9.9.9\u001b[0m\n-\u001b[2m----------------------------------------------------\u001b[0m-\n" - ], - "meta": { - "nf-test": "0.8.4", - "nextflow": "23.10.1" - }, - "timestamp": "2024-02-28T12:03:10.562934" - }, - "Test Function workflowCitation": { - "content": [ - "If you use nextflow_workflow for your analysis please cite:\n\n* The pipeline\n https://doi.org/10.5281/zenodo.5070524\n\n* The nf-core framework\n https://doi.org/10.1038/s41587-020-0439-x\n\n* Software dependencies\n https://github.com/nextflow_workflow/blob/master/CITATIONS.md" - ], - "meta": { - "nf-test": "0.8.4", - "nextflow": "23.10.1" - }, - "timestamp": "2024-02-28T12:03:07.019761" - }, "Test Function without logColours": { "content": [ { @@ -95,16 +75,6 @@ }, "timestamp": "2024-02-28T12:03:17.969323" }, - "Test Function dashedLine": { - "content": [ - "-\u001b[2m----------------------------------------------------\u001b[0m-" - ], - "meta": { - "nf-test": "0.8.4", - "nextflow": "23.10.1" - }, - "timestamp": "2024-02-28T12:03:14.366181" - }, "Test Function with logColours": { "content": [ { diff --git a/subworkflows/nf-core/utils_nfcore_pipeline/tests/tags.yml b/subworkflows/nf-core/utils_nfcore_pipeline/tests/tags.yml deleted file mode 100644 index ac8523c..0000000 --- a/subworkflows/nf-core/utils_nfcore_pipeline/tests/tags.yml +++ /dev/null @@ -1,2 +0,0 @@ -subworkflows/utils_nfcore_pipeline: - - subworkflows/nf-core/utils_nfcore_pipeline/** diff --git a/subworkflows/nf-core/utils_nfschema_plugin/main.nf b/subworkflows/nf-core/utils_nfschema_plugin/main.nf index 93de2a5..acb3972 100644 --- a/subworkflows/nf-core/utils_nfschema_plugin/main.nf +++ b/subworkflows/nf-core/utils_nfschema_plugin/main.nf @@ -4,6 +4,7 @@ include { paramsSummaryLog } from 'plugin/nf-schema' include { validateParameters } from 'plugin/nf-schema' +include { paramsHelp } from 'plugin/nf-schema' workflow UTILS_NFSCHEMA_PLUGIN { @@ -15,29 +16,56 @@ workflow UTILS_NFSCHEMA_PLUGIN { // when this input is empty it will automatically use the configured schema or // "${projectDir}/nextflow_schema.json" as default. This input should not be empty // for meta pipelines + help // boolean: show help message + help_full // boolean: show full help message + show_hidden // boolean: show hidden parameters in help message + before_text // string: text to show before the help message and parameters summary + after_text // string: text to show after the help message and parameters summary + command // string: an example command of the pipeline main: + if(help || help_full) { + help_options = [ + beforeText: before_text, + afterText: after_text, + command: command, + showHidden: show_hidden, + fullHelp: help_full, + ] + if(parameters_schema) { + help_options << [parametersSchema: parameters_schema] + } + log.info paramsHelp( + help_options, + params.help instanceof String ? params.help : "", + ) + exit 0 + } + // // Print parameter summary to stdout. This will display the parameters // that differ from the default given in the JSON schema // + + summary_options = [:] if(parameters_schema) { - log.info paramsSummaryLog(input_workflow, parameters_schema:parameters_schema) - } else { - log.info paramsSummaryLog(input_workflow) + summary_options << [parametersSchema: parameters_schema] } + log.info before_text + log.info paramsSummaryLog(summary_options, input_workflow) + log.info after_text // // Validate the parameters using nextflow_schema.json or the schema // given via the validation.parametersSchema configuration option // if(validate_params) { + validateOptions = [:] if(parameters_schema) { - validateParameters(parameters_schema:parameters_schema) - } else { - validateParameters() + validateOptions << [parametersSchema: parameters_schema] } + validateParameters(validateOptions) } emit: diff --git a/subworkflows/nf-core/utils_nfschema_plugin/tests/main.nf.test b/subworkflows/nf-core/utils_nfschema_plugin/tests/main.nf.test index 842dc43..c977917 100644 --- a/subworkflows/nf-core/utils_nfschema_plugin/tests/main.nf.test +++ b/subworkflows/nf-core/utils_nfschema_plugin/tests/main.nf.test @@ -25,6 +25,12 @@ nextflow_workflow { input[0] = workflow input[1] = validate_params input[2] = "" + input[3] = false + input[4] = false + input[5] = false + input[6] = "" + input[7] = "" + input[8] = "" """ } } @@ -42,7 +48,7 @@ nextflow_workflow { params { test_data = '' - outdir = 1 + outdir = null } workflow { @@ -51,6 +57,12 @@ nextflow_workflow { input[0] = workflow input[1] = validate_params input[2] = "" + input[3] = false + input[4] = false + input[5] = false + input[6] = "" + input[7] = "" + input[8] = "" """ } } @@ -77,6 +89,12 @@ nextflow_workflow { input[0] = workflow input[1] = validate_params input[2] = "${projectDir}/subworkflows/nf-core/utils_nfschema_plugin/tests/nextflow_schema.json" + input[3] = false + input[4] = false + input[5] = false + input[6] = "" + input[7] = "" + input[8] = "" """ } } @@ -94,7 +112,7 @@ nextflow_workflow { params { test_data = '' - outdir = 1 + outdir = null } workflow { @@ -103,6 +121,12 @@ nextflow_workflow { input[0] = workflow input[1] = validate_params input[2] = "${projectDir}/subworkflows/nf-core/utils_nfschema_plugin/tests/nextflow_schema.json" + input[3] = false + input[4] = false + input[5] = false + input[6] = "" + input[7] = "" + input[8] = "" """ } } @@ -114,4 +138,36 @@ nextflow_workflow { ) } } + + test("Should create a help message") { + + when { + + params { + test_data = '' + outdir = null + } + + workflow { + """ + validate_params = true + input[0] = workflow + input[1] = validate_params + input[2] = "${projectDir}/subworkflows/nf-core/utils_nfschema_plugin/tests/nextflow_schema.json" + input[3] = true + input[4] = false + input[5] = false + input[6] = "Before" + input[7] = "After" + input[8] = "nextflow run test/test" + """ + } + } + + then { + assertAll( + { assert workflow.success } + ) + } + } } diff --git a/subworkflows/nf-core/utils_nfschema_plugin/tests/nextflow.config b/subworkflows/nf-core/utils_nfschema_plugin/tests/nextflow.config index 478fb8a..8d8c737 100644 --- a/subworkflows/nf-core/utils_nfschema_plugin/tests/nextflow.config +++ b/subworkflows/nf-core/utils_nfschema_plugin/tests/nextflow.config @@ -1,5 +1,5 @@ plugins { - id "nf-schema@2.1.0" + id "nf-schema@2.5.1" } validation { From 11c554e639a202e3fd157cd518b8099d3169a903 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Tue, 7 Oct 2025 16:44:05 +1100 Subject: [PATCH 23/70] minor updates --- assets/samplesheet.csv | 2 +- assets/schema_input.json | 4 ++-- conf/test_gadi.config | 2 +- subworkflows/local/utils_nfcore_wisps_pipeline/main.nf | 8 +++++++- workflows/wisps.nf | 2 +- 5 files changed, 12 insertions(+), 6 deletions(-) diff --git a/assets/samplesheet.csv b/assets/samplesheet.csv index 8e79bde..6d87802 100644 --- a/assets/samplesheet.csv +++ b/assets/samplesheet.csv @@ -1,3 +1,3 @@ -id,fasta,type,group +id,sequence,type,group T1024,https://raw.githubusercontent.com/nf-core/test-datasets/proteinfold/testdata/sequences/T1024.fasta,protein,G1 T1026,https://raw.githubusercontent.com/nf-core/test-datasets/proteinfold/testdata/sequences/T1026.fasta,protein,G1 diff --git a/assets/schema_input.json b/assets/schema_input.json index c57b0e9..236decb 100644 --- a/assets/schema_input.json +++ b/assets/schema_input.json @@ -17,8 +17,8 @@ "type": "string", "format": "file-path", "exists": true, - "pattern": "^\\S+\\.fa(sta)?$", - "errorMessage": "Fasta/YAML file must be provided, cannot contain spaces and must have extension '.fa' or '.fasta'" + "pattern": "^\\S+\\.(fa(sta)?|yaml|yml|json)$", + "errorMessage": "Fasta, yaml or json file must be provided, cannot contain spaces and must have extension '.fa', '.fasta', '.yaml', '.yml', or '.json'" }, "type": { "type": "string", diff --git a/conf/test_gadi.config b/conf/test_gadi.config index 046fbe1..dfcd195 100644 --- a/conf/test_gadi.config +++ b/conf/test_gadi.config @@ -83,7 +83,7 @@ process { memory: '2000.GB', time: '24.h' ] - resourceLimits1 = [ + resourceLimits = [ cpus: 16, memory: '24.GB', time: '3.h' diff --git a/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf b/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf index dc63ab9..68813d6 100644 --- a/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf +++ b/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf @@ -53,7 +53,13 @@ workflow PIPELINE_INITIALISATION { UTILS_NFSCHEMA_PLUGIN ( workflow, validate_params, - null + null, + false, + false, // boolean: show full help message + false, // boolean: show hidden parameters in help message + "", // string: text to show before the help message and parameters summary + "", // string: text to show after the help message and parameters summary + "" // string: an example command of the pipeline ) // diff --git a/workflows/wisps.nf b/workflows/wisps.nf index eece1a9..104217c 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -114,7 +114,7 @@ workflow WISPS { .filter{ it["group"] in interaction_mode || interaction_mode[0] == "all-all"} .unique() .set{ch_unique_pairs} - + ch_unique_pairs.view() ch_samplesheet .combine(ch_samplesheet) .map{[ From 1452b6a109e3c1f805e1f2d4eb56fd5cd7d173a9 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Tue, 7 Oct 2025 17:09:39 +1100 Subject: [PATCH 24/70] update docs --- docs/usage.md | 20 ++++++++++++++------ 1 file changed, 14 insertions(+), 6 deletions(-) diff --git a/docs/usage.md b/docs/usage.md index 36a8573..45faa49 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -27,15 +27,23 @@ S2,Sample2.fasta,B,protein S3,S3.yaml,A,rna ``` -| Column | Description | -| ---------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | -| `id` | The `id` identifiers have to be unique in the sample sheet and **must not** have an underscore (`_`). | -| `sequence` | Full path to Fasta/YAML file for sample seqeuence. File has to have the extension ".fasta", ".fa" or "yaml". | -| `type` | The sequence type, can be either protein, rna . It is an optional column, by default it will be consdred as protein. | -| `group` | it is a way to group samnples to create custom interactions. It is an optional column, if not provided, the inteactions will be `aa-all' which means all sample against all samples. | +| Column | Description | +| ---------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `id` | The `id` identifiers have to be unique in the sample sheet and **must not** have an underscore or hyphen (`_`, `-`). | +| `sequence` | Full path to Fasta/YAML file for sample sequence. File has to have the extension ".fasta", ".fa", or "yaml". | +| `type` | The sequence type, can be either `protein`, `rna`, `smiles`. It is an optional column; by default, it will be considered as `protein`. | +| `group` | It is a way to group samples together to create custom interactions. It is an optional column and **must not** have a hyphen (`-`). If not provided, the interactions will be `all-all`, which means all samples against all samples, or you can use `group.a-group.b` to only consider the samples from `group.a` against samples from `group.b`. | An [example samplesheet](../assets/samplesheet.csv) has been provided with the pipeline. +## Creating Interactions from sample sheet + +The created interactions generated from the sample sheet are customised through the parameter `--mode`. Two different ways to customise what interactions are generated from the sample sheet: + +1. The default behavior is for `--mode all-all`. In this case, the workflow will generate interaction pairs for all samples in the sample sheet against each other (all possible combinations) and keep the unique pairs after ignoring the order of the samples. This does not require the group column to be provided in the sample sheet, and this is the default behavior of the workflow unless the `--mode` parameter is customised. + +2. A custom combination can be achieved through the column group in the sample sheet. You can use a combination of the group values. You can use multiple combinations by separating them with a comma (`,`). For example, there are group `A` and group `B1` in the example sample sheet above, running the pipeline with `--mode A-A,A-B` will generate the followiong pairs `S1-S1`, `S3-S3`, and `S1-S3` from the combination `A-A` and add to it the pait `S1-S2` and `S2-S3` from teh combination `A-B`. + ## Running the pipeline The typical command for running the pipeline is as follows: From 8d0218b1b2bb9f9b1743f2f94cbff52bc6563ca4 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Thu, 9 Oct 2025 17:10:59 +1100 Subject: [PATCH 25/70] adding ipsea to multiqc --- assets/multiqc_config.yml | 55 ++++++++++ bin/ipsae.py | 5 + conf/modules.config | 29 ++++-- conf/test_gadi.config | 8 +- modules/local/colabfold_batch/main.nf | 15 ++- modules/local/ipsae/main.nf | 37 +++++-- modules/local/mmseqs_colabfoldsearch/main.nf | 3 +- modules/local/prepare_interactions.nf | 14 +-- modules/local/run_alphafold3/main.nf | 14 ++- modules/local/run_boltz/main.nf | 26 +++-- nextflow.config | 6 ++ nextflow_schema.json | 28 +++++ workflows/wisps.nf | 101 ++++++++++++++----- 13 files changed, 271 insertions(+), 70 deletions(-) diff --git a/assets/multiqc_config.yml b/assets/multiqc_config.yml index 95d111e..6bfa4b5 100644 --- a/assets/multiqc_config.yml +++ b/assets/multiqc_config.yml @@ -13,3 +13,58 @@ report_section_order: export_plots: true disable_version_detection: true + +strict: true + +custom_data: + colabfold_confidence: + section_name: "ColabFold Confidence" + description: "Confidence scores for models generated by ColabFold" + file_format: "csv" + plot_type: "table" + pconfig: + id: "colabfold_confidence_table" + title: "ColabFold Confidence Scores" + + boltz_confidence: + section_name: "Boltz Confidence" + description: "Confidence scores for models generated by Boltz" + file_format: "csv" + plot_type: "table" + pconfig: + id: "boltz_confidence_table" + title: "Boltz Confidence Scores" + + alphafold3_confidence: + section_name: "AlphaFold3 Confidence" + description: "Confidence scores for models generated by AlphaFold3" + file_format: "csv" + plot_type: "table" + pconfig: + id: "alphafold3_confidence_table" + title: "AlphaFold3 Confidence Scores" + + ipsae_scores: + section_name: "IPSAE scores" + description: "Confidence scores for all used models generated by IPSAE" + file_format: "csv" + plot_type: "table" + pconfig: + id: "ipsae_scores_table" + title: "IPSAE Confidence Scores" + +sp: + colabfold_confidence: + fn: "*colabfold_confidence_scores_full.csv" + boltz_confidence: + fn: "*boltz_confidence_scores_full.csv" + alphafold3_confidence: + fn: "*alphafold3_confidence_scores_full.csv" + ipsae_scores: + fn: "*ipsae_scores.csv" + +custom_table_header_config: + ipsae_scores_table: + colabfold_ipsae: { format: "{:,.5f}" } + boltz_ipsae: { format: "{:,.5f}" } + alphafold3_ipsae: { format: "{:,.5f}" } diff --git a/bin/ipsae.py b/bin/ipsae.py index dd8ad42..1f41a3f 100755 --- a/bin/ipsae.py +++ b/bin/ipsae.py @@ -86,6 +86,7 @@ print("Wrong PDB or PAE file type ", pdb_path) sys.exit() +print(f"Output file name: {path_stem}") file_path = path_stem + ".txt" file2_path = path_stem + "_byres.txt" pml_path = path_stem + ".pml" @@ -969,3 +970,7 @@ def classify_chains(chains, residue_types): chain2_residues = f'chain {chain2} and resi {contiguous_ranges(unique_residues_chain2[chain1][chain2])}' PML.write(f'alias {chain_pair}, color gray80, all; color {color1}, {chain1_residues}; color {color2}, {chain2_residues}\n\n') OUT.write("\n") + +OUT.close() +PML.close() +OUT2.close() diff --git a/conf/modules.config b/conf/modules.config index c9549f9..3451468 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -31,15 +31,30 @@ process { memory = 300.GB time = 16.h def args = "" - if (params.mmseqs_gpu){ - args += "--gpu 1 " - } + if (params.colabfold_search_args){ + ext.args = "${params.colabfold_search_args}" + }else{ + if (params.mmseqs_gpu){ + args += "--gpu 1 " + } - if ("${params.tools}".split(",").contains("alphafold3")){ - args += "--af3-json " - } + if ("${params.tools}".split(",").contains("alphafold3")){ + args += "--af3-json " + } + + if (params.colabfold_uniref30_prefix){ + args += "--db1 ${params.colabfold_uniref30_prefix} " + } + if (params.colabfold_envdb_prefix){ + args += "--db3 ${params.colabfold_envdb_prefix} " + } - ext.args = args + if (params.use_spire_db){ + args += "--use-env-pairing --db4 ${params.spire_db_prefix} " + } + + ext.args = args + } } withName: 'RUN_BOLTZ' { diff --git a/conf/test_gadi.config b/conf/test_gadi.config index dfcd195..aa73729 100644 --- a/conf/test_gadi.config +++ b/conf/test_gadi.config @@ -36,11 +36,13 @@ params { use_gpu = true project = "ll61" use_dgxa100 = false + + colabfold_search_args = " --use-env 0 --af3-json --db1 colabfold_uniref30/uniref30_2302_db --db3 colabfold_envdb_202108/colabfold_envdb_202108_db" } process { executor = "pbspro" - //executor = "local" + executor = "local" storage = "gdata/za08+gdata/if89+scratch/${params.project}+gdata/${params.project}" module = 'singularity' cache = 'lenient' @@ -78,12 +80,12 @@ process { memory: '4.GB', time: '1.h' ] - resourceLimits = [ + resourceLimits1 = [ cpus: 1000, memory: '2000.GB', time: '24.h' ] - resourceLimits = [ + resourceLimits1 = [ cpus: 16, memory: '24.GB', time: '3.h' diff --git a/modules/local/colabfold_batch/main.nf b/modules/local/colabfold_batch/main.nf index 0e17128..1d6d21c 100644 --- a/modules/local/colabfold_batch/main.nf +++ b/modules/local/colabfold_batch/main.nf @@ -49,11 +49,16 @@ process COLABFOLD_BATCH { stub: """ - touch ./${meta.id}_relaxed_rank_model_1_00.pdb - touch ./${meta.id}_relaxed_rank_model_2_00.pdb - touch ./${meta.id}_relaxed_rank_model_3_00.pdb - touch ./${meta.id}_coverage.png - touch ./${meta.id}_scores_rank_001_00.json + for f in alignment/*; do + [[ -f "\$f" ]] || continue + fname=\${f##*/} + id=\${fname%%.*} + touch \${id}_relaxed_rank_model_1_00.pdb + touch \${id}_relaxed_rank_model_2_00.pdb + touch \${id}_relaxed_rank_model_3_00.pdb + touch \${id}_coverage.png + touch \${id}_scores_rank_001_00.json + done cat <<-END_VERSIONS > versions.yml "${task.process}": diff --git a/modules/local/ipsae/main.nf b/modules/local/ipsae/main.nf index ed4551c..8973233 100644 --- a/modules/local/ipsae/main.nf +++ b/modules/local/ipsae/main.nf @@ -8,13 +8,13 @@ process IPSAE { 'quay.io/biocontainers/numpy:2.2.2' }" input: - tuple val(meta), path(pae), path(pdb) - path (extra_files) + tuple val(meta), val(files_names) + path ("data/") output: - tuple val(meta), path ("*.pml"), emit: pml - tuple val(meta), path ("*_byres.txt"), emit: byres - tuple val(meta), path ("*.txt"), emit: txt + tuple val(meta), path ("data/*.pml"), emit: pml + tuple val(meta), path ("data/*_byres.txt"), emit: byres + tuple val(meta), path ("data/*[0-9].txt"), emit: txt path "versions.yml" , emit: versions when: @@ -24,9 +24,16 @@ process IPSAE { def args = task.ext.args ?: '' """ - ipsae.py ${pae} \\ - ${pdb} \\ - ${args} + pae_files=(${files_names.collect { "\"${it[0]}\"" }.join(" ")}) + pdb_files=(${files_names.collect { "\"${it[1]}\"" }.join(" ")}) + + [[ \${#pae_files[@]} -eq \${#pdb_files[@]} ]] || { echo "lengths differ"; exit 1; } + + for i in "\${!pae_files[@]}"; do + ipsae.py data/\${pae_files[i]} \\ + data/\${pdb_files[i]} \\ + ${args} + done cat <<-END_VERSIONS > versions.yml "${task.process}": @@ -36,9 +43,17 @@ process IPSAE { stub: """ - touch "${meta.id}.pml" - touch "${meta.id}.txt" - touch "${meta.id}.byres.txt" + pae_files=(${files_names.collect { "\"${it[0]}\"" }.join(" ")}) + pdb_files=(${files_names.collect { "\"${it[1]}\"" }.join(" ")}) + + [[ \${#pae_files[@]} -eq \${#pdb_files[@]} ]] || { echo "lengths differ"; exit 1; } + + for i in "\${!pae_files[@]}"; do + s="\${pdb_files[i]}" + touch "data/\${s%%_*}_10.pml" + touch "data/\${s%%_*}_10.txt" + touch "data/\${s%%_*}_10_byres.txt" + done cat <<-END_VERSIONS > versions.yml "${task.process}": diff --git a/modules/local/mmseqs_colabfoldsearch/main.nf b/modules/local/mmseqs_colabfoldsearch/main.nf index 0e6a450..959d8fe 100644 --- a/modules/local/mmseqs_colabfoldsearch/main.nf +++ b/modules/local/mmseqs_colabfoldsearch/main.nf @@ -28,7 +28,6 @@ process MMSEQS_COLABFOLDSEARCH { mamba run --name colab colabfold_search \\ $args \\ --threads $task.cpus \\ - --use-env 0 --db1 colabfold_uniref30/uniref30_2302_db --db3 colabfold_envdb_202108/colabfold_envdb_202108_db \\ ${fasta} \\ ./db \\ "result/" @@ -60,9 +59,11 @@ process MMSEQS_COLABFOLDSEARCH { safe_name=\$(echo "\$firstcol" | tr -cd '[:alnum:]_-') touch "results/\${safe_name}.a3m" + touch "results/\${safe_name}.json" done < "$fasta" else touch results/${meta.id}.a3m + touch results/${meta.id}.json fi cat <<-END_VERSIONS > versions.yml diff --git a/modules/local/prepare_interactions.nf b/modules/local/prepare_interactions.nf index 6be245e..3c17291 100644 --- a/modules/local/prepare_interactions.nf +++ b/modules/local/prepare_interactions.nf @@ -77,12 +77,14 @@ process PREPARE_INTERACTIONS { stub: """ - touch "${meta.id}_boltz_interaction_input.fasta" + #!/usr/bin/env python3 + from pathlib import Path + import sys, os + ids_batch = ${ids.collect { "\"${it}\"" }.toString()} + for batch_itr in range(len(ids_batch)): + Path(ids_batch[batch_itr] + "_boltz_interaction_input.fasta").touch() - cat <<-END_VERSIONS > versions.yml - "${task.process}": - python: \$(python3 --version | sed 's/Python //g') - generate_comparison_report.py: \$(python3 --version) - END_VERSIONS + with open ("versions.yml", "w") as version_file: + version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) """ } diff --git a/modules/local/run_alphafold3/main.nf b/modules/local/run_alphafold3/main.nf index fdce44c..444fe04 100644 --- a/modules/local/run_alphafold3/main.nf +++ b/modules/local/run_alphafold3/main.nf @@ -41,9 +41,17 @@ process RUN_ALPHAFOLD3 { def prefix = task.ext.prefix ?: "${meta.id}" """ mkdir out - touch out/${prefix}_model.cif - touch out/${prefix}_confidences.json - touch out/${prefix}_summary_confidences.json + + for f in data/*; do + [[ -f "\$f" ]] || continue + fname=\${f##*/} + id=\${fname%%.*} + mkdir -p out/\$id + touch out/\$id/\${id}_model.cif + touch out/\$id/\${id}_confidences.json + touch out/\$id/\${id}_summary_confidences.json + done + cat <<-END_VERSIONS > versions.yml "${task.process}": python: \$(python3 --version | sed 's/Python //g') diff --git a/modules/local/run_boltz/main.nf b/modules/local/run_boltz/main.nf index 5bb3a76..4b78501 100644 --- a/modules/local/run_boltz/main.nf +++ b/modules/local/run_boltz/main.nf @@ -53,17 +53,23 @@ process RUN_BOLTZ { stub: def version = "2.0.3" """ - mkdir -p boltz_results_${meta.id}/processed/msa/ - mkdir -p boltz_results_${meta.id}/processed/structures/ - mkdir -p boltz_results_${meta.id}/predictions/${meta.id}/ + mkdir -p boltz_results_fasta/processed/msa/ + mkdir -p boltz_results_fasta/processed/structures/ + mkdir -p boltz_results_fasta/predictions/ - touch boltz_results_${meta.id}/processed/msa/${meta.id}.npz - touch boltz_results_${meta.id}/processed/structures/${meta.id}.npz - touch boltz_results_${meta.id}/predictions/${meta.id}/confidence_${meta.id}.json - touch boltz_results_${meta.id}/predictions/${meta.id}/${meta.id}.pdb - touch boltz_results_${meta.id}/predictions/${meta.id}/${meta.id}.cif - touch boltz_results_${meta.id}/predictions/${meta.id}/plddt_${meta.id}_model_0.npz - touch boltz_results_${meta.id}/predictions/${meta.id}/pae_${meta.id}_model_0.npz + for f in fasta/*; do + [[ -f "\$f" ]] || continue + fname=\${f##*/} + id=\${fname%%_*} + mkdir -p boltz_results_fasta/predictions/\${id}_boltz_interaction_input + touch boltz_results_fasta/predictions/\${id}_boltz_interaction_input/\${id}_boltz_interaction_input_model_0.pdb + touch boltz_results_fasta/predictions/\${id}_boltz_interaction_input/\${id}_boltz_interaction_input_model_0.cif + touch boltz_results_fasta/predictions/\${id}_boltz_interaction_input/confidence_\${id}_boltz_interaction_input_model_0.json + touch boltz_results_fasta/predictions/\${id}_boltz_interaction_input/pae_\${id}_boltz_interaction_input_model_0.npz + touch boltz_results_fasta/predictions/\${id}_boltz_interaction_input/plddt_\${id}_boltz_interaction_input_model_0.npz + touch boltz_results_fasta/processed/msa/\${id}_boltz_interaction_input_0.npz + touch boltz_results_fasta/processed/structures/\${id}_boltz_interaction_input.npz + done cat <<-END_VERSIONS > versions.yml "${task.process}": diff --git a/nextflow.config b/nextflow.config index eb26971..84de3cf 100644 --- a/nextflow.config +++ b/nextflow.config @@ -36,6 +36,12 @@ params { colabfold_alphafold2_params = null colabfold_envdb = null alphafold3_params = null + spire_db = null + + colabfold_uniref30_prefix = "colabfold_uniref30/uniref30_2302_db" + colabfold_envdb_prefix = "colabfold_envdb_202108/colabfold_envdb_202108_db" + use_spire_db = false + colabfold_search_args = null // MultiQC options multiqc_config = null diff --git a/nextflow_schema.json b/nextflow_schema.json index 5b5b7f2..fed197d 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -65,6 +65,11 @@ "description": "Run mmseqs on CPUs (default) or GPUs", "fa_icon": "fas fa-microchip" }, + "use_spire_db": { + "type": "boolean", + "description": "Use spire DB for search", + "fa_icon": "fas fa-folder-open" + }, "email": { "type": "string", "description": "Email address for completion summary.", @@ -104,6 +109,23 @@ "description": "Link to the ColabFold database", "fa_icon": "fas fa-folder-open" }, + "colabfold_uniref30_prefix": { + "type": "string", + "description": "Link to the ColabFold database", + "fa_icon": "fas fa-folder-open", + "default": "colabfold_uniref30/uniref30_2302_db" + }, + "colabfold_envdb_prefix": { + "type": "string", + "description": "Link to the ColabFold database", + "fa_icon": "fas fa-folder-open", + "default": "colabfold_uniref30/uniref30_2302_db" + }, + "spire_db": { + "type": "string", + "description": "Link to the ColabFold database", + "fa_icon": "fas fa-folder-open" + }, "colabfold_alphafold2_params": { "type": "string", "description": "Link to the Alphafold2 parameters for Colabfold", @@ -169,6 +191,12 @@ ], "fa_icon": "fas fa-stream" }, + "colabfold_search_args": { + "type": "string", + "default": null, + "description": "Arguments to be passed to colabfold_search", + "fa_icon": "fas fa-stream" + }, "ipsae_pae_cutoff": { "type": "integer", "default": 10, diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 104217c..1c093c9 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -114,7 +114,7 @@ workflow WISPS { .filter{ it["group"] in interaction_mode || interaction_mode[0] == "all-all"} .unique() .set{ch_unique_pairs} - ch_unique_pairs.view() + ch_samplesheet .combine(ch_samplesheet) .map{[ @@ -304,12 +304,6 @@ workflow WISPS { .map{[["id": it.baseName.split("_")[0], "model": "boltz"], it]} .set{ch_boltz_cif} - ch_boltz_confidence - .collect(flat: false, sort: true).multiMap{json_list -> - ids: json_list.collect{it[0].id} - json: json_list.collect{it[1]} - }.set{ch_boltz_confidence_scores} - //prepare interactions for colabfold ch_colabfold_interaction_in = Channel.empty() if ("colabfold" in tools.split(",")){ @@ -319,7 +313,7 @@ workflow WISPS { .buffer( size: analysis_batch_size, remainder: true ) .map{ colabfold_batch += 1; - [["id": "batch-${colabfold_batch}"], it] + [["id": "batch-${colabfold_batch}-${it.size()}"], it] } .set{ ch_colabfold_interaction_in @@ -349,13 +343,6 @@ workflow WISPS { .set{ch_colabfold_pdb} - ch_colabfold_scores - .collect(flat: false, sort: true).multiMap{json_list -> - ids: json_list.collect{it[0].id} - json: json_list.collect{it[1]} - }.set{ch_colabfold_confidence_scores} - - af3_batch = 0 ch_alphafold3_interaction_in = Channel.empty() if ("alphafold3" in tools.split(",")){ @@ -396,19 +383,21 @@ workflow WISPS { .set{ch_alphafold3_summary_confidences} - ch_alphafold3_summary_confidences.collect(flat: false, sort: true).multiMap{json_list -> - ids: json_list.collect{it[0].id} - json: json_list.collect{it[1]} - }.set{ch_alphafold3_confidence_scores} - + ipsae_batch = 0 ch_colabfold_scores .join(ch_colabfold_pdb) - .map{[["id": it[0].id], it, []]} + .map{[["id": it[0].id], it]} .join(ch_interaction_in .filter{it[1][0].type == "protein" || it[1][1].type == "protein"} .map{["id": it[0].id]} ) + .map{[it[1][1], it[1][2], []]} + .buffer( size: analysis_batch_size, remainder: true ) + .map{ + ipsae_batch += 1; + [["id": "batch-${ipsae_batch}-${it.size()}", "model": "colabfold"], it] + } .mix( ch_boltz_pae .join(ch_boltz_cif) @@ -418,24 +407,87 @@ workflow WISPS { .filter{it[1][0].type == "protein" || it[1][1].type == "protein"} .map{["id": it[0].id]} ) + .map{[it[1][1], it[1][2], it[2]]} + .buffer( size: analysis_batch_size, remainder: true ) + .map{ + ipsae_batch += 1; + [["id": "batch-${ipsae_batch}-${it.size()}", "model": "boltz"], it] + } ) .mix( ch_alphafold3_confidence.join(ch_alphafold3_cif) - .map{[["id": it[0].id], it, []]} + .map{[["id": it[0].id], it]} .join(ch_interaction_in .filter{it[1][0].type == "protein" || it[1][1].type == "protein"} .map{["id": it[0].id]} ) + .map{[it[1][1], it[1][2], []]} + .buffer( size: analysis_batch_size, remainder: true ) + .map{ + ipsae_batch += 1; + [["id": "batch-${ipsae_batch}-${it.size()}", "model": "alphafold3"], it] + } ) .set{ch_ipsae_in} IPSAE( - ch_ipsae_in.map{it[1]}, - ch_ipsae_in.map{it[2]} + ch_ipsae_in + .map{[it[0], it[1].collect{[it[0].name, it[1].name]}]}, + ch_ipsae_in + .map{it[1].flatten()} ) ch_versions = ch_versions.mix(IPSAE.out.versions) + IPSAE.out.txt + .transpose() + .branch { + boltz: it[0].model == "boltz" + lines = it[1].text.split("\n").findAll{line -> line.split().size() > 4 && line.split()[4].trim() == "max" } + max_vals = lines.collect{new BigDecimal(it.split()[5].trim())} + return [it[1].baseName.split("_")[0], max_vals ? (max_vals.sum() / max_vals.size()) : null] + + alphafold3: it[0].model == "alphafold3" + lines = it[1].text.split("\n").findAll{line -> line.split().size() > 4 && line.split()[4].trim() == "max" } + max_vals = lines.collect{new BigDecimal(it.split()[5].trim())} + return [it[1].baseName.split("_")[0], max_vals ? (max_vals.sum() / max_vals.size()) : null] + + colabfold: it[0].model == "colabfold" + lines = it[1].text.split("\n").findAll{line -> line.split().size() > 4 && line.split()[4].trim() == "max" } + max_vals = lines.collect{new BigDecimal(it.split()[5].trim())} + return [it[1].baseName.split("_")[0], max_vals ? (max_vals.sum() / max_vals.size()) : null] + } + .set{ch_ipsae_out} + + ch_interaction_in.map{it[0].id} + .join(ch_ipsae_out.boltz, remainder: true) + .join(ch_ipsae_out.colabfold, remainder: true) + .join(ch_ipsae_out.alphafold3, remainder: true) + .map{"${it[0]},${it[1] != null ? it[1] : ""},${ it[2] != null ? it[2] : ""},${ it[3] != null ? it[3] : ""}\n"} + .toSortedList() + .flatten() + .collectFile(name: 'ipsae_scores.csv', seed: "Sample,boltz_ipsae,colabfold_ipsae,alphafold3_ipsae\n") + .set{ch_ipsae_scores} + + ch_boltz_confidence + .collect(flat: false, sort: true).multiMap{json_list -> + ids: json_list.collect{it[0].id} + json: json_list.collect{it[1]} + }.set{ch_boltz_confidence_scores} + + ch_alphafold3_summary_confidences + .collect(flat: false, sort: true).multiMap{json_list -> + ids: json_list.collect{it[0].id} + json: json_list.collect{it[1]} + }.set{ch_alphafold3_confidence_scores} + + ch_colabfold_scores + .collect(flat: false, sort: true).multiMap{json_list -> + ids: json_list.collect{it[0].id} + json: json_list.collect{it[1]} + }.set{ch_colabfold_confidence_scores} + + COLLECT_CONFIDENCE( ch_boltz_confidence_scores.ids .map{[["id": "all-boltz", "model": "boltz"], it]} @@ -477,6 +529,7 @@ workflow WISPS { ch_multiqc_files = ch_multiqc_files.mix(ch_collated_versions) ch_multiqc_files = ch_multiqc_files .mix(COLLECT_CONFIDENCE.out.confidence.map{it[1]}) + .mix(ch_ipsae_scores) MULTIQC ( ch_multiqc_files.collect(sort: true), ch_multiqc_config.collect() From 51aeeb509ca4f1c8160cb096a4516d4f887e8a8f Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Thu, 9 Oct 2025 18:20:52 +1100 Subject: [PATCH 26/70] fix collect confidence output --- modules/local/collect_confidence.nf | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/modules/local/collect_confidence.nf b/modules/local/collect_confidence.nf index 2d8998c..00420d1 100644 --- a/modules/local/collect_confidence.nf +++ b/modules/local/collect_confidence.nf @@ -39,6 +39,7 @@ process COLLECT_CONFIDENCE { rows = [] all_keys = ["confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde", "chains_ptm"] writing_keys = ["id", "confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde"] + writing_keys_extra = set() # First pass: read and collect keys cntr = 0 for file in json_files: @@ -52,14 +53,15 @@ process COLLECT_CONFIDENCE { if isinstance(value, dict): for sub_key, sub_value in value.items(): flat_data[f"{key}_{sub_key}"] = sub_value - writing_keys.append(f"{key}_{sub_key}") + writing_keys_extra.add(f"{key}_{sub_key}") else: flat_data[key] = value rows.append(flat_data) # Write to CSV + with open(output_csv, "w", newline="") as f: - writer = csv.DictWriter(f, fieldnames=writing_keys) + writer = csv.DictWriter(f, fieldnames=writing_keys + sorted(writing_keys_extra)) writer.writeheader() for row in rows: writer.writerow({key: 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END_VERSIONS """ @@ -42,7 +37,7 @@ process SPLIT_MSA { cat <<-END_VERSIONS > versions.yml "${task.process}": - python: \$(python3 --version | sed 's/Python //g') + msakit: 0.0.1 END_VERSIONS """ } From 735a55cae56fc74ddeba9ec0af8a438b7adc2e73 Mon Sep 17 00:00:00 2001 From: Ziad Al-Bkhetan Date: Mon, 13 Oct 2025 13:47:36 +1100 Subject: [PATCH 28/70] Add files via upload --- bin/msakit | Bin 935504 -> 1108048 bytes 1 file changed, 0 insertions(+), 0 deletions(-) diff --git a/bin/msakit b/bin/msakit index c1ee5da8cec479238b0e0c3fdfac8d0972b7de19..0f4aae0e05a6404e943582aa1decace6063e341d 100755 GIT binary patch literal 1108048 zcmd444V+WO_5Xhtb|Hw6phVXPH0WZN`jl1FMMbl~!i{DnD(JR~1YvPe9wH>NR*_(K zWn-EewY6&>Z2GNj*Xp-MZS9Iyvw*NrYlBu@?Ss+!5L~qpE36MC|IfKIH+yqrtbV`W z*Z=j~z9jd)@7yzI&YYP!Gk5Oox<=ouVHFjc`8QlUN29ZBm0%uuA^WPsOrm+TdTlKJ zJw}_TjR390e;#?2|2l??3+As)rXx)E`Q>%~d!$Tf{+b%nFWsm5OFk&Bn7^7-o9?Tk zOKEYP|4th_+PGl;TJJOR%ZTe5``vQbFylV+*Lok>#+4sqT<5=S>kX{+-zl=DCX!)wFT{Oh&oBFD 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    #sM&#eDTD`A-E=@6 zX!Ty2FDaBS>e(e9iJfU(w0_0(!t>Pni1sboRpB&|qOD)K*61u|V0dsvJ)3AymYu(X2a;(wFW)X4z~j`V6aJba8#j{i>cy-HZ?d7rLnGQ;riN zlbEW&4XaNDUsd-&o_}|xT!HDXe@@lz_owCV$w}2?SsR@mGb1k6U$^@#(}oA$`K5cf zTVn59_acimNg9jxLXqjQzHI-{)u7Wuu`cWSNy~tU$ZA!cWr$9@SFE;W`MT4lMPD>r zt+&g!8QsEQf7V{@nMmb9nJfZz)tRo+AUBNgpxvZ zw$-m>8Q7=E(`n4d(b$k{rNfEv7<2w?YM=x?l$I|uW>XZs#|X|zT1?mTngA%SF7DWD6e*z28~eK6xgvuOwC45FcrGj z@*8Oi^=q^9i)FzJ*%roHP}nr_p^V=9-`}E!U*qr3*qUDcx_RNQf7^cUF7n&vzrV|y z-{jAgzp~}s^^@k0dHv@)?_=IK%YSFfyX&W&-~UGE{nJkQ|7^><>nEMxcgz1a-~X>) z{9^6e|8ra3UETfvtgWZp{+!SMB7d&@$lbtRe{Ks(A7$)Z`5*9F{w?{FTe|W;{|oZz zXymT{$F|3OYU*&W<@yzWzi71okN%4J)?I(kydAmryZgB7Kjr)X*C>DfS4{zT)kgD? zdq%GPw%XC}@O22y<{NkYY-QfN`@8b4|Nq>Ue`tO-`h(vwFWlArPRh$%?Uw(y zd?w@S>K}c}8~OLG{$IVMt){}JCv``!J2{~J@@UH|0Y zRYmoM8#njqf8#~7{C9unFX>nA`ul&~{nA{!_x~TZ{IA(_tev*!JO_OEUE z-!<1CyNRKt>+-Iizu#&9=-=4;erK-VwUX?Q~JU|L?Z^pPcF2(I--dIqLfD Date: Thu, 16 Oct 2025 11:56:02 +1100 Subject: [PATCH 29/70] update collect confidence --- bin/collect_confidence.py | 183 ++++++++++++++++++++++++++++ modules/local/collect_confidence.nf | 107 ++-------------- workflows/wisps.nf | 5 +- 3 files changed, 197 insertions(+), 98 deletions(-) create mode 100755 bin/collect_confidence.py diff --git a/bin/collect_confidence.py b/bin/collect_confidence.py new file mode 100755 index 0000000..a8b27f8 --- /dev/null +++ b/bin/collect_confidence.py @@ -0,0 +1,183 @@ +#!/usr/bin/env python3 + +import os, sys +import json +import csv +import statistics +from pathlib import Path +from typing import Any, Dict, Iterable +import argparse + +def flatten_deep( + data: Dict[Any, Any], + *, + sep: str = "_", + index_lists: bool = False, # set True to flatten lists/tuples by index + keep_empty_dicts: bool = False +) -> Dict[str, Any]: + """ + Recursively flattens nested dictionaries by joining keys with `sep`. + - Dict keys at any depth are converted to strings in the output keys. + - If `index_lists` is True, lists/tuples are traversed and indexed. + - If `keep_empty_dicts` is True, empty dicts become key -> {} (else skipped). + """ + flat: Dict[str, Any] = {} + + def _walk(prefix: str, obj: Any) -> None: + # dict -> dive deeper + if isinstance(obj, dict): + if not obj: + if keep_empty_dicts and prefix: + flat[prefix] = {} + return + for k, v in obj.items(): + k_str = str(k) + new_key = f"{prefix}{sep}{k_str}" if prefix else k_str + _walk(new_key, v) + return + + # list/tuple handling (optional) + if index_lists and isinstance(obj, (list, tuple)): + if not obj: + # represent empty list if desired; default: skip + return + for i, item in enumerate(obj): + new_key = f"{prefix}{sep}{i}" if prefix else str(i) + _walk(new_key, item) + return + + # leaf value -> record it + if prefix == "": + # top-level non-dict without a key path; use a default name if needed + flat["_"] = obj + else: + flat[prefix] = obj + + _walk("", data) + return flat + +def extract_boltz_results(json_files, samples, output_csv): + rows = [] + all_keys = ["confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde", "chains_ptm"] + writing_keys = ["id", "confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde"] + writing_keys_extra = set() + # First pass: read and collect keys + cntr = 0 + for file in json_files: + with open(file) as f: + data = json.load(f) + flat_data = {"id": samples[cntr]} + cntr += 1 + for key, value in data.items(): + if key not in all_keys: + continue + if isinstance(value, dict): + for sub_key, sub_value in value.items(): + flat_data[f"{key}_{sub_key}"] = sub_value + writing_keys_extra.add(f"{key}_{sub_key}") + else: + flat_data[key] = value + rows.append(flat_data) + + # Write to CSV + + with open(output_csv, "w", newline="") as f: + writer = csv.DictWriter(f, fieldnames=writing_keys + sorted(writing_keys_extra)) + writer.writeheader() + for row in rows: + writer.writerow({key: row.get(key, "") for key in writing_keys}) + +def extract_colabfold_results(json_files, samples, output_csv): + def parse_colabfold_metrics(json_file): + with open(json_file, "r") as f: + data = json.load(f) + + result = {} + for key in ["iptm", "max_pae", "pae", "ptm", "plddt"]: + if key not in data: + result[key] = None + continue + + if key == "plddt" and isinstance(data[key], list): + # Compute mean for list + result[key] = statistics.mean(data[key]) if data[key] else None + else: + # Take value directly + result[key] = data[key] + + return result + + rows = [] + all_keys = ["id", "plddt", "ptm", "iptm", "max_pae"] + writing_keys = all_keys + cntr = 0 + for file in json_files: + flat_data = parse_colabfold_metrics(file) + flat_data["id"] = samples[cntr] + cntr += 1 + rows.append(flat_data) + + # Write to CSV + with open(output_csv, "w", newline="") as f: + writer = csv.DictWriter(f, fieldnames=writing_keys) + writer.writeheader() + for row in rows: + writer.writerow({key: row.get(key, "") for key in writing_keys}) + +def extract_alphafold3_results(json_files, samples, output_csv): + rows = [] + all_keys = ["chain_iptm","chain_pair_iptm", "chain_pair_pae_min", "ptm", "iptm", "chain_ptm", "fraction_disordered", "has_clash", "ranking_score"] + writing_keys = ["id", "ptm", "iptm", "fraction_disordered", "has_clash", "ranking_score"] + writing_keys_extra = set() + # First pass: read and collect keys + cntr = 0 + for file in json_files: + with open(file) as f: + data = json.load(f) + flat_data = {"id": samples[cntr]} + cntr += 1 + for key, value in data.items(): + if key not in all_keys: + continue + if isinstance(value, dict) or isinstance(value, list): + sub_data = flatten_deep(value, index_lists=True) + for sub_key, sub_value in sub_data.items(): + flat_data[f"{key}_{sub_key}"] = sub_value + writing_keys_extra.add(f"{key}_{sub_key}") + else: + flat_data[key] = value + rows.append(flat_data) + + # Write to CSV + final_writing_vals = writing_keys + sorted(writing_keys_extra) + with open(output_csv, "w", newline="") as f: + writer = csv.DictWriter(f, fieldnames=final_writing_vals) + writer.writeheader() + for row in rows: + writer.writerow({key: row.get(key, "") for key in final_writing_vals}) + + + +def main(): + parser = argparse.ArgumentParser(description="Collect confidence scorer generating by different models..") + parser.add_argument("-i", "--input", help="Path to input directory containing all json files") + parser.add_argument("-o", "--output", default="output_msa", help="output CSV file") + parser.add_argument("--model", default="boltz", help="model generating the input files can be one of [boltz, alphafold3, and colabfold]") + + args = parser.parse_args() + json_files = [str(f) for f in Path(args.input).glob("*.json") if f.is_file()] + + if args.model.lower() == "boltz": + samples = [Path(p).name.split("_")[1] for p in json_files] + extract_boltz_results(json_files, samples, args.output) + elif args.model.lower() == "colabfold": + samples = [Path(p).name.split("_")[0] for p in json_files] + extract_colabfold_results(json_files, samples, args.output) + elif args.model.lower() == "alphafold3": + samples = [Path(p).name.split("_")[0] for p in json_files] + extract_alphafold3_results(json_files, samples, args.output) + + print(f"CSV file created at: {args.output}") + +if __name__ == "__main__": + main() diff --git a/modules/local/collect_confidence.nf b/modules/local/collect_confidence.nf index 3199154..00b78c9 100644 --- a/modules/local/collect_confidence.nf +++ b/modules/local/collect_confidence.nf @@ -9,7 +9,7 @@ process COLLECT_CONFIDENCE { input: tuple val(meta), val(samples) - path(json_files) + path("input_json_files/*") output: tuple val(meta), path ("*confidence_scores_full.csv"), emit: confidence path "versions.yml" , emit: versions @@ -21,103 +21,16 @@ process COLLECT_CONFIDENCE { def args = task.ext.args ?: '' """ - #!/usr/bin/env python3 + collect_confidence.py \\ + --input input_json_files \\ + --model "${meta.model}"\\ + --output "${meta.model}_confidence_scores_full.csv" - import os, sys - import json - import csv - import statistics - - # Folder containing the JSON files - output_csv = "${meta.model}_confidence_scores_full.csv" - - # Collect all JSON files - json_files = ["${json_files.join('", "')}"] - samples = ["${samples.join('", "')}"] - - def extract_boltz_results(json_files, samples, output_csv): - rows = [] - all_keys = ["confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde", "chains_ptm"] - writing_keys = ["id", "confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde"] - writing_keys_extra = set() - # First pass: read and collect keys - cntr = 0 - for file in json_files: - with open(file) as f: - data = json.load(f) - flat_data = {"id": samples[cntr]} - cntr += 1 - for key, value in data.items(): - if key not in all_keys: - continue - if isinstance(value, dict): - for sub_key, sub_value in value.items(): - flat_data[f"{key}_{sub_key}"] = sub_value - writing_keys_extra.add(f"{key}_{sub_key}") - else: - flat_data[key] = value - rows.append(flat_data) - - # Write to CSV - - with open(output_csv, "w", newline="") as f: - writer = csv.DictWriter(f, fieldnames=writing_keys + sorted(writing_keys_extra)) - writer.writeheader() - for row in rows: - writer.writerow({key: row.get(key, "") for key in writing_keys}) - - - - def extract_colabfold_results(json_files, samples, output_csv): - def parse_colabfold_metrics(json_file): - with open(json_file, "r") as f: - data = json.load(f) - - result = {} - for key in ["iptm", "max_pae", "pae", "ptm", "plddt"]: - if key not in data: - result[key] = None - continue - - if key == "plddt" and isinstance(data[key], list): - # Compute mean for list - result[key] = statistics.mean(data[key]) if data[key] else None - else: - # Take value directly - result[key] = data[key] - - return result - - rows = [] - all_keys = ["id", "plddt", "ptm", "iptm", "max_pae"] - writing_keys = all_keys - cntr = 0 - for file in json_files: - flat_data = parse_colabfold_metrics(file) - flat_data["id"] = samples[cntr] - cntr += 1 - rows.append(flat_data) - - # Write to CSV - with open(output_csv, "w", newline="") as f: - writer = csv.DictWriter(f, fieldnames=writing_keys) - writer.writeheader() - for row in rows: - writer.writerow({key: row.get(key, "") for key in writing_keys}) - - - - if "${meta.model}".lower() == "boltz": - extract_boltz_results(json_files, samples, output_csv) - elif "${meta.model}".lower() == "colabfold": - extract_colabfold_results(json_files, samples, output_csv) - elif "${meta.model}".lower() == "alphafold3": - extract_alphafold3_results(json_files, samples, output_csv) - - print(f"CSV file created at: {output_csv}") - - with open ("versions.yml", "w") as version_file: - version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + generate_comparison_report.py: \$(python3 --version) + END_VERSIONS """ stub: diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 1c093c9..12aaf59 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -466,7 +466,10 @@ workflow WISPS { .map{"${it[0]},${it[1] != null ? it[1] : ""},${ it[2] != null ? it[2] : ""},${ it[3] != null ? it[3] : ""}\n"} .toSortedList() .flatten() - .collectFile(name: 'ipsae_scores.csv', seed: "Sample,boltz_ipsae,colabfold_ipsae,alphafold3_ipsae\n") + .collectFile( + storeDir: "${outdir}/ipsae", + name: 'ipsae_scores.csv', + seed: "Sample,boltz_ipsae,colabfold_ipsae,alphafold3_ipsae\n") .set{ch_ipsae_scores} ch_boltz_confidence From b9bd7f2dd48e4877e620e79e79ae60f06e1796cb Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Tue, 27 Jan 2026 14:00:41 +1100 Subject: [PATCH 30/70] updating interaction creation --- conf/gadi.config | 19 ++- conf/modules.config | 2 +- .../local/data_convertor/boltz_fasta/main.nf | 1 - .../data_convertor/create_interactions.nf | 59 ++++++++ nextflow.config | 2 +- subworkflows/local/msa.nf | 2 + workflows/wisps.nf | 143 +++++++++++------- 7 files changed, 162 insertions(+), 66 deletions(-) create mode 100644 modules/local/data_convertor/create_interactions.nf diff --git a/conf/gadi.config b/conf/gadi.config index 8bcc1f2..c26600d 100644 --- a/conf/gadi.config +++ b/conf/gadi.config @@ -23,12 +23,18 @@ params { // Input data outdir = "out-test" input = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" - samplesheet2 = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" boltz_ccd = "/g/data/if89/proteinfold_dbs/boltz_dbs/ccd.pkl" boltz_model = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz1_conf.ckpt" + boltz2_aff = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz2_aff.ckpt" + boltz2_conf = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz2_conf.ckpt" + boltz2_mols = "/g/data/if89/proteinfold_dbs/boltz_dbs/mols" + + //colabfold_db = "/g/data/if89/proteinfold_dbs/colabfold_dbs/colabfold_envdb_202108/" colabfold_db = "/g/data/if89/proteinfold_dbs/colabfold_dbs/colabfold_envdb_202108/" - colabfold_db = "/g/data/if89/proteinfold_dbs/colabfold_dbs/colabfold_envdb_202108/" +colabfold_alphafold2_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params/alphafold_params_colab_2022-12-06/" + + alphafold3_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" uniref30 = "/g/data/if89/proteinfold_dbs/colabfold_dbs/uniref30_2302/" use_gpu = true @@ -43,12 +49,12 @@ process { withName: 'MMSEQS_COLABFOLDSEARCH' { memory = 300.GB - time = 16.h + time = 24.h } withName: 'RUN_BOLTZ' { cpus = 12 queue = "gpuvolta" - time = 10.h + time = 24.h memory = 24.GB cpus = 12 gpus = 1 @@ -61,7 +67,10 @@ process { resourceLimits = [ cpus: 1000, memory: '2000.GB', - time: '24.h' + time: '48.h' ] } +executor.pollInterval = '5 sec' +executor.queueStatInterval = '1 min' +executor.submitRateLimit = '20min' diff --git a/conf/modules.config b/conf/modules.config index 3451468..986e8c2 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -29,7 +29,7 @@ process { withName: 'MMSEQS_COLABFOLDSEARCH' { memory = 300.GB - time = 16.h + time = 48.h def args = "" if (params.colabfold_search_args){ ext.args = "${params.colabfold_search_args}" diff --git a/modules/local/data_convertor/boltz_fasta/main.nf b/modules/local/data_convertor/boltz_fasta/main.nf index 200125a..2e8cfc7 100644 --- a/modules/local/data_convertor/boltz_fasta/main.nf +++ b/modules/local/data_convertor/boltz_fasta/main.nf @@ -113,7 +113,6 @@ process BOLTZ_FASTA { with open ("versions.yml", "w") as version_file: version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) - ${args} """ stub: diff --git a/modules/local/data_convertor/create_interactions.nf b/modules/local/data_convertor/create_interactions.nf new file mode 100644 index 0000000..e15862f --- /dev/null +++ b/modules/local/data_convertor/create_interactions.nf @@ -0,0 +1,59 @@ +process CREATE_INTERACTIONS { + tag "all_run" + label 'process_single' + + conda "${moduleDir}/environment.yml" + container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? + 'https://depot.galaxyproject.org/singularity/python:3.8.3' : + 'quay.io/biocontainers/python:3.8.3' }" + + input: + val(ids) + val(types) + val(seqs) + + output: + path ("interactions.fasta"), emit: interactions + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + def args = task.ext.args ?: '' + """ + #!/usr/bin/env python3 + import os, sys + seqs = [${"\"" + seqs.join('", "') + "\""}] + ids = [${"\"" + ids.join('", "') + "\""}] + types = [${"\"" + types.join('", "') + "\""}] + done_singles = set() + n = len(seqs) + with open("interactions.fasta", "w") as target_interactions: + for i in range(n): + for j in range(i + 1, n): + if types[i] == "protein" and types[j] == "protein": + target_interactions.write(f">{ids[i]}-{ids[j]}\\n{seqs[i]}:{seqs[j]}\\n") + elif types[i] == "protein": + if ids[i] not in done_singles: + target_interactions.write(f">{ids[i]}\\n{seqs[i]}\\n") + done_singles.add(ids[i]) + elif types[j] == "protein": + if ids[j] not in done_singles: + target_interactions.write(f">{ids[j]}\\n{seqs[j]}\\n") + done_singles.add(ids[j]) + + with open ("versions.yml", "w") as version_file: + version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) + """ + + stub: + """ + touch interactions.fasta + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + END_VERSIONS + """ +} diff --git a/nextflow.config b/nextflow.config index 84de3cf..ae096a2 100644 --- a/nextflow.config +++ b/nextflow.config @@ -38,7 +38,7 @@ params { alphafold3_params = null spire_db = null - colabfold_uniref30_prefix = "colabfold_uniref30/uniref30_2302_db" + colabfold_uniref30_prefix = "uniref30_2302/uniref30_2302_db" colabfold_envdb_prefix = "colabfold_envdb_202108/colabfold_envdb_202108_db" use_spire_db = false colabfold_search_args = null diff --git a/subworkflows/local/msa.nf b/subworkflows/local/msa.nf index 5759134..dbf7099 100644 --- a/subworkflows/local/msa.nf +++ b/subworkflows/local/msa.nf @@ -74,6 +74,8 @@ workflow MSA { ) ch_versions = ch_versions.mix(MMSEQS_COLABFOLDSEARCH.out.versions) + MMSEQS_COLABFOLDSEARCH.out.a3m.view() + ch_input.fasta.view() ch_a3m = ch_a3m.mix( ch_input.fasta.mix(ch_input.yaml) .map{[it[1].baseName, it[0]]} diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 12aaf59..a0735bf 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -27,7 +27,6 @@ include { paramsSummaryMap } from 'plugin/nf-schema' include { paramsSummaryMultiqc } from '../subworkflows/nf-core/utils_nfcore_pipeline' include { softwareVersionsToYAML } from '../subworkflows/nf-core/utils_nfcore_pipeline' include { methodsDescriptionText } from '../subworkflows/local/utils_nfcore_wisps_pipeline' -include { MSA } from '../subworkflows/local/msa' // // LOCAL MODULE: Boltz @@ -38,7 +37,8 @@ include { COLABFOLD_BATCH } from '../modules/local/colabfold_batch' include { BOLTZ_FASTA } from '../modules/local/data_convertor/boltz_fasta' include { SPLIT_MSA } from '../modules/local/msa_manager/split_msa' include { IPSAE } from '../modules/local/ipsae' - +include {CREATE_INTERACTIONS} from '../modules/local/data_convertor/create_interactions' +include { MMSEQS_COLABFOLDSEARCH } from '../modules/local/mmseqs_colabfoldsearch' // // FUNCTIONS @@ -105,46 +105,58 @@ workflow WISPS { } } log.info "Used Interactions (Sorted): ${interaction_mode.join(',')}" - ch_samplesheet.map{it[0]} - .combine(ch_samplesheet.map{it[0]}) - .map{[ - "id": [it[0]["id"], it[1]["id"]].min() + "-" + [it[0]["id"], it[1]["id"]].max(), - "group": [it[0]["group"], it[1]["group"]].min() + "-" + [it[0]["group"], it[1]["group"]].max(), - ]} - .filter{ it["group"] in interaction_mode || interaction_mode[0] == "all-all"} - .unique() - .set{ch_unique_pairs} ch_samplesheet - .combine(ch_samplesheet) - .map{[ - [ - "id": [it[0]["id"], it[2]["id"]].min() + "-" + [it[0]["id"], it[2]["id"]].max(), - "group": [it[0]["group"], it[2]["group"]].min() + "-" + [it[0]["group"], it[2]["group"]].max(), - ], - [it[0], it[2]], - [it[1], it[3]], - ]}.set{ch_pairs} - - ch_pairs - .join(ch_unique_pairs) + .multiMap{ + if (it[1].extension == "fasta" || it[1].extension == "fa") + {seq = getFastaSequences(it[1].text).sequence.join(":")} + else if (it[1].extension == "yaml" || it[1].extension == ".yml") + {seq = getYamlSequences(it[1].text).sequence.join(":")} + else if (it[1].extension == "json") + {seq = ""} + + ids:it[0].id + types: it[0].type + seqs: seq + }.set{ch_raw_sample_sheet} + + + CREATE_INTERACTIONS( + ch_raw_sample_sheet.ids.collect(), + ch_raw_sample_sheet.types.collect(), + ch_raw_sample_sheet.seqs.collect() + ) + + ch_samplesheet + .collect(flat: false) + .flatMap { data_ls -> + def list = data_ls.toList() + def out = [] + for (int i = 0; i < list.size(); i++) { + for (int j = i + 1; j < list.size(); j++) { + //print("${list[i]} - ${list[j]}") + if ("${[list[i][0]["id"], list[j][0]["id"]].min()}-${[list[i][0]["id"], list[j][0]["id"]].max()}" in interaction_mode || interaction_mode[0] == "all-all") + { + out << [ + [ + "id": list[i][0]["id"] + "-" + list[j][0]["id"], + "group": list[i][0]["group"] + "-" + list[j][0]["group"] + ], + [list[i][0], list[j][0]], + [list[i][1], list[j][1]], + ] + } + } + } + out + } .set{ch_interaction_in} + + ch_interaction_in.count().subscribe{print("total final: ${it}")} + ch_interaction_in .filter{it[1][0].type == "protein" && it[1][1].type == "protein"} - .collectFile{ - seqs = [] - for (j in [0, 1]){ - if (it[2][j].extension == "fasta" || it[2][j].extension == "fa") - {seqs.add(getFastaSequences(it[2][j].text))} - else if (it[2][j].extension == "yaml" || it[2][j].extension == ".yml") - {seqs.add(getYamlSequences(it[2][j].text))} - else if (it[2][j].extension == "json") - {seqs.add("")} - } - [ "${it[0].id}.fasta", ">${it[0].id}\n${seqs.collect{it.sequence.join(":")}.join(":")}\n" ] - } - .map{[["id": it.baseName], it]} .set {ch_protein_pairs} ch_interaction_in @@ -158,16 +170,25 @@ workflow WISPS { .set{ch_single_protein} //ch_protein_pairs.view() - MSA ( - ch_protein_pairs - .mix( - ch_single_protein - ), + + MMSEQS_COLABFOLDSEARCH ( + CREATE_INTERACTIONS.out.interactions.map{[["id": "all_run"], it]}, ch_colabfold_db, - ch_uniref30, - mmseqs_batch_size + ch_uniref30 + ) + ch_versions = ch_versions.mix(MMSEQS_COLABFOLDSEARCH.out.versions) + + MMSEQS_COLABFOLDSEARCH.out.a3m + .map{it[1]} + .flatten() + .map{[it.baseName, it]} + .cross( + ch_protein_pairs + .mix(ch_single_protein) + .map{[it[0].id, it[0]]} ) - ch_versions = ch_versions.mix(MSA.out.versions) + .map{[it[1][1], it[0][1]]} + .set{ch_a3m} // Prepare interactions for boltz ch_boltz_data = Channel.empty() @@ -175,12 +196,26 @@ workflow WISPS { ch_boltz_interactions_in = Channel.empty() if ("boltz" in tools.split(",")){ - ch_split_msa_in = MSA.out.a3m.join(ch_protein_pairs.map{it[0]}) + ch_a3m + .join(ch_protein_pairs.map{it[0]}) + .set{ch_split_msa_in} ch_boltz_interactions_in = ch_interaction_in } + split_batch_id = 0 + SPLIT_MSA( + ch_split_msa_in + .map{it[1]} + .buffer( size: mmseqs_batch_size, remainder: true ) + .map{ split_batch_id += 1; [["id" : "batch-${split_batch_id}-${it.size()}"], it]} + ) + + ch_versions = ch_versions.mix(SPLIT_MSA.out.versions) + // Adding non protein for boltz - ch_boltz_data = ch_boltz_data.mix(ch_boltz_interactions_in + ch_boltz_data = + ch_boltz_data + .mix(ch_boltz_interactions_in .filter{it[1][0].type != "protein" && it[1][1].type != "protein"} .map{[it, ["", ""]]} ) @@ -196,7 +231,7 @@ workflow WISPS { [it[1][1], it] } } - .combine(MSA.out.a3m.filter{it[0].type == "protein"}) + .combine(ch_a3m.filter{it[0].type == "protein"}) .filter{it[0] == it[2]} .map{ if (it[1][1][0].type == "protein") @@ -205,15 +240,6 @@ workflow WISPS { [it[1], ["", it[3]]] } ) - split_batch_id = 0 - SPLIT_MSA( - ch_split_msa_in - .map{it[1]} - .buffer( size: mmseqs_batch_size, remainder: true ) - .map{ split_batch_id += 1; [["id" : "batch-${split_batch_id}-${it.size()}"], it]} - ) - - ch_versions = ch_versions.mix(SPLIT_MSA.out.versions) SPLIT_MSA.out.msa_csv .map{it[1]} @@ -308,7 +334,7 @@ workflow WISPS { ch_colabfold_interaction_in = Channel.empty() if ("colabfold" in tools.split(",")){ colabfold_batch = 0 - MSA.out.a3m.join(ch_protein_pairs.map{it[0]}) + ch_a3m.join(ch_protein_pairs.map{it[0]}) .map{it[1]} .buffer( size: analysis_batch_size, remainder: true ) .map{ @@ -319,6 +345,7 @@ workflow WISPS { ch_colabfold_interaction_in } } + //ch_colabfold_interaction_in.view() COLABFOLD_BATCH( ch_colabfold_interaction_in, @@ -346,7 +373,7 @@ workflow WISPS { af3_batch = 0 ch_alphafold3_interaction_in = Channel.empty() if ("alphafold3" in tools.split(",")){ - MSA.out.json.join(ch_protein_pairs.map{it[0]}) + ch_a3m.join(ch_protein_pairs.map{it[0]}) .map{it[1]} .buffer( size: analysis_batch_size, remainder: true ) .map{ From 3208b4c7e216133074028ceab1c4be3b29ee0b81 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Wed, 25 Feb 2026 15:26:42 +1100 Subject: [PATCH 31/70] interaction creation and limiting to neighbours --- README.md | 15 ------- conf/gadi.config | 43 +++++++++++-------- conf/modules.config | 4 +- docs/usage.md | 2 +- main.nf | 3 +- .../data_convertor/create_interactions.nf | 37 +++++++++++----- nextflow.config | 8 ++-- workflows/wisps.nf | 18 +++++--- 8 files changed, 73 insertions(+), 57 deletions(-) diff --git a/README.md b/README.md index 28b6924..6514708 100644 --- a/README.md +++ b/README.md @@ -91,18 +91,3 @@ If you would like to contribute to this pipeline, please see the [contributing g For further information or help, don't hesitate to get in touch on the [Slack `#wisps` channel](https://nfcore.slack.com/channels/wisps) (you can join with [this invite](https://nf-co.re/join/slack)). ## Citations - - - - - - -An extensive list of references for the tools used by the pipeline can be found in the [`CITATIONS.md`](CITATIONS.md) file. - -You can cite the `nf-core` publication as follows: - -> **The nf-core framework for community-curated bioinformatics pipelines.** -> -> Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen. -> -> _Nat Biotechnol._ 2020 Feb 13. doi: [10.1038/s41587-020-0439-x](https://dx.doi.org/10.1038/s41587-020-0439-x). diff --git a/conf/gadi.config b/conf/gadi.config index c26600d..5a81ee6 100644 --- a/conf/gadi.config +++ b/conf/gadi.config @@ -24,19 +24,19 @@ params { outdir = "out-test" input = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" - boltz_ccd = "/g/data/if89/proteinfold_dbs/boltz_dbs/ccd.pkl" - boltz_model = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz1_conf.ckpt" - boltz2_aff = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz2_aff.ckpt" - boltz2_conf = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz2_conf.ckpt" - boltz2_mols = "/g/data/if89/proteinfold_dbs/boltz_dbs/mols" + boltz_ccd = "/g/data/li87/struct_bio/params/boltz/ccd.pkl" + boltz_model = "/g/data/li87/struct_bio/params/boltz/boltz1_conf.ckpt" + boltz2_aff = "/g/data/li87/struct_bio/params/boltz/boltz2_aff.ckpt" + boltz2_conf = "/g/data/li87/struct_bio/params/boltz/boltz2_conf.ckpt" + boltz2_mols = "/g/data/li87/struct_bio/params/boltz/mols" - //colabfold_db = "/g/data/if89/proteinfold_dbs/colabfold_dbs/colabfold_envdb_202108/" - colabfold_db = "/g/data/if89/proteinfold_dbs/colabfold_dbs/colabfold_envdb_202108/" -colabfold_alphafold2_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params/alphafold_params_colab_2022-12-06/" + uniref30 = "/g/data/li87/proteinfold_dbs/colabfold_uniref30/" + colabfold_db = "/g/data/li87/proteinfold_dbs/colabfold_envdb/" - alphafold3_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" + colabfold_alphafold2_params = "/g/data/li87/struct_bio/params/alphafold2/" + + alphafold3_params = "/g/data/li87/struct_bio/params/alphafold2" - uniref30 = "/g/data/if89/proteinfold_dbs/colabfold_dbs/uniref30_2302/" use_gpu = true project = "ll61" use_dgxa100 = false @@ -45,25 +45,27 @@ colabfold_alphafold2_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params process { //executor = "local" - storage = "gdata/if89+scratch/${params.project}+gdata/${params.project}" + storage = "gdata/li87+gdata/if89+scratch/${params.project}+gdata/${params.project}" withName: 'MMSEQS_COLABFOLDSEARCH' { memory = 300.GB time = 24.h + cpus = 24 } withName: 'RUN_BOLTZ' { + queue = "gpuvolta" + time = 48.h + memory = 128.GB cpus = 12 + gpus = 1 + } + withName: 'COLABFOLD_BATCH' { queue = "gpuvolta" - time = 24.h - memory = 24.GB + time = 16.h + memory = 128.GB cpus = 12 gpus = 1 } - resourceLimits = [ - cpus: 1, - memory: '4.GB', - time: '1.h' - ] resourceLimits = [ cpus: 1000, memory: '2000.GB', @@ -74,3 +76,8 @@ process { executor.pollInterval = '5 sec' executor.queueStatInterval = '1 min' executor.submitRateLimit = '20min' + +gadi { + format = 'csv' + output = 'gadi_report.csv' +} diff --git a/conf/modules.config b/conf/modules.config index 986e8c2..f9953fa 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -59,8 +59,8 @@ process { withName: 'RUN_BOLTZ' { cpus = 12 - time = 10.h - memory = 24.GB + time = 24.h + memory = 128.GB ext.args = "--write_full_pae --output_format mmcif" } diff --git a/docs/usage.md b/docs/usage.md index 45faa49..7ce1ac0 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -40,7 +40,7 @@ An [example samplesheet](../assets/samplesheet.csv) has been provided with the p The created interactions generated from the sample sheet are customised through the parameter `--mode`. Two different ways to customise what interactions are generated from the sample sheet: -1. The default behavior is for `--mode all-all`. In this case, the workflow will generate interaction pairs for all samples in the sample sheet against each other (all possible combinations) and keep the unique pairs after ignoring the order of the samples. This does not require the group column to be provided in the sample sheet, and this is the default behavior of the workflow unless the `--mode` parameter is customised. +1. The default behavior is for `--mode all-all`. In this case, the workflow will generate interaction pairs for all samples in the sample sheet against each other (all possible combinations) and keep the unique pairs after ignoring the order of the samples. This does not require the group column to be provided in the sample sheet, and this is the default behavior of the workflow unless the `--mode` parameter is customised. When using this mode, the user can liit the number of formed interactions through the parameter `interaction_threshold` which takes a numeric value. by default the value is 0 and all interactions are formed. For any positive value `n`, onlye the neighboring paires that are within `n` neighbors will be considered. In this case, teh order of the samples in teh sample sheet matters. For example, if `--interaction_threshold 2`, the 2 nighbouring samples (2 before and 2 after) will be consdered. 2. A custom combination can be achieved through the column group in the sample sheet. You can use a combination of the group values. You can use multiple combinations by separating them with a comma (`,`). For example, there are group `A` and group `B1` in the example sample sheet above, running the pipeline with `--mode A-A,A-B` will generate the followiong pairs `S1-S1`, `S3-S3`, and `S1-S3` from the combination `A-A` and add to it the pait `S1-S2` and `S2-S3` from teh combination `A-B`. diff --git a/main.nf b/main.nf index f1c1fc9..9a0c9a6 100644 --- a/main.nf +++ b/main.nf @@ -62,7 +62,8 @@ workflow NFCORE_WISPS { ch_multiqc_logo, ch_multiqc_methods_description, params.outdir, - params.analysis_batch_size + params.analysis_batch_size, + params.interaction_threshold ) ch_versions = ch_versions.mix(WISPS.out.versions) diff --git a/modules/local/data_convertor/create_interactions.nf b/modules/local/data_convertor/create_interactions.nf index e15862f..3f947c6 100644 --- a/modules/local/data_convertor/create_interactions.nf +++ b/modules/local/data_convertor/create_interactions.nf @@ -10,7 +10,10 @@ process CREATE_INTERACTIONS { input: val(ids) val(types) + val(groups) val(seqs) + val(interaction_mode) + val(interaction_threshold) output: path ("interactions.fasta"), emit: interactions @@ -24,25 +27,37 @@ process CREATE_INTERACTIONS { """ #!/usr/bin/env python3 import os, sys + interaction_mode = [${"\"" + interaction_mode.join('", "') + "\""}] seqs = [${"\"" + seqs.join('", "') + "\""}] ids = [${"\"" + ids.join('", "') + "\""}] types = [${"\"" + types.join('", "') + "\""}] + groups = [${"\"" + groups.join('", "') + "\""}] done_singles = set() n = len(seqs) + interactions_cntr = 0 + group_ls = {part for s in groups for part in s.split("-")} with open("interactions.fasta", "w") as target_interactions: for i in range(n): - for j in range(i + 1, n): - if types[i] == "protein" and types[j] == "protein": - target_interactions.write(f">{ids[i]}-{ids[j]}\\n{seqs[i]}:{seqs[j]}\\n") - elif types[i] == "protein": - if ids[i] not in done_singles: - target_interactions.write(f">{ids[i]}\\n{seqs[i]}\\n") - done_singles.add(ids[i]) - elif types[j] == "protein": - if ids[j] not in done_singles: - target_interactions.write(f">{ids[j]}\\n{seqs[j]}\\n") - done_singles.add(ids[j]) + for j in range(i, n): + if interaction_mode[0] != "all-all" and groups[i] not in group_ls: + continue + if (interaction_mode[0] != "all-all" and "-".join(sorted([groups[i], groups[j]])) in interaction_mode) or (interaction_mode[0] == "all-all" and (${interaction_threshold} == 0 or abs(i-j) <= ${interaction_threshold})): + interactions_cntr += 1 + if types[i] == "protein" and types[j] == "protein": + target_interactions.write(f">{ids[i]}-{ids[j]}\\n{seqs[i]}:{seqs[j]}\\n") + elif types[i] == "protein": + if ids[i] not in done_singles: + target_interactions.write(f">{ids[i]}\\n{seqs[i]}\\n") + done_singles.add(ids[i]) + elif types[j] == "protein": + if ids[j] not in done_singles: + target_interactions.write(f">{ids[j]}\\n{seqs[j]}\\n") + done_singles.add(ids[j]) + if interactions_cntr == 0: + print("No Interactions found!!") + exit(1) + print(f"{interactions_cntr} Interactions found!!") with open ("versions.yml", "w") as version_file: version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) """ diff --git a/nextflow.config b/nextflow.config index ae096a2..d5bdae1 100644 --- a/nextflow.config +++ b/nextflow.config @@ -13,10 +13,11 @@ params { // Input options input = null mode = "all-all" + interaction_threshold = 0 mmseqs_batch_size = 10000 mmseqs_gpu = false use_gpu = true - analysis_batch_size = 10000 + analysis_batch_size = 3000 colabfold_model_preset = "alphafold2_multimer_v3" colabfold_num_recycles = 3 @@ -38,8 +39,8 @@ params { alphafold3_params = null spire_db = null - colabfold_uniref30_prefix = "uniref30_2302/uniref30_2302_db" - colabfold_envdb_prefix = "colabfold_envdb_202108/colabfold_envdb_202108_db" + colabfold_uniref30_prefix = "colabfold_uniref30/uniref30_2302_db" + colabfold_envdb_prefix = "colabfold_envdb/colabfold_envdb_202108_db" use_spire_db = false colabfold_search_args = null @@ -259,6 +260,7 @@ manifest { // Nextflow plugins plugins { id 'nf-schema@2.1.1' // Validation of pipeline parameters and creation of an input channel from a sample sheet + id 'nf-gadi@1.2.0' } validation { diff --git a/workflows/wisps.nf b/workflows/wisps.nf index a0735bf..a8fad74 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -78,6 +78,7 @@ workflow WISPS { ch_multiqc_methods_description outdir analysis_batch_size + interaction_threshold main: ch_multiqc_files = Channel.empty() @@ -117,6 +118,7 @@ workflow WISPS { ids:it[0].id types: it[0].type + groups: it[0].group seqs: seq }.set{ch_raw_sample_sheet} @@ -124,7 +126,10 @@ workflow WISPS { CREATE_INTERACTIONS( ch_raw_sample_sheet.ids.collect(), ch_raw_sample_sheet.types.collect(), - ch_raw_sample_sheet.seqs.collect() + ch_raw_sample_sheet.groups.collect(), + ch_raw_sample_sheet.seqs.collect(), + interaction_mode, + interaction_threshold ) ch_samplesheet @@ -133,14 +138,14 @@ workflow WISPS { def list = data_ls.toList() def out = [] for (int i = 0; i < list.size(); i++) { - for (int j = i + 1; j < list.size(); j++) { - //print("${list[i]} - ${list[j]}") - if ("${[list[i][0]["id"], list[j][0]["id"]].min()}-${[list[i][0]["id"], list[j][0]["id"]].max()}" in interaction_mode || interaction_mode[0] == "all-all") + for (int j = i; j < list.size(); j++) { + def key = [list[i][0]['group'].toString(), list[j][0]['group'].toString()].sort().join('-') + if ((interaction_mode[0] != "all-all" && interaction_mode.contains(key)) || (interaction_mode[0] == "all-all" && (interaction_threshold == 0 || Math.abs(i-j) <= interaction_threshold))) { out << [ [ "id": list[i][0]["id"] + "-" + list[j][0]["id"], - "group": list[i][0]["group"] + "-" + list[j][0]["group"] + "group": key ], [list[i][0], list[j][0]], [list[i][1], list[j][1]], @@ -189,7 +194,8 @@ workflow WISPS { ) .map{[it[1][1], it[0][1]]} .set{ch_a3m} - + ch_a3m.first().view() + ch_protein_pairs.first().view() // Prepare interactions for boltz ch_boltz_data = Channel.empty() ch_split_msa_in = Channel.empty() From 268b85cf22a181af3ec2a1065b65de58affe3180 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Sat, 21 Mar 2026 12:35:58 +1100 Subject: [PATCH 32/70] general hpc fixes --- conf/gadi.config | 4 ++++ modules/local/mmseqs_colabfoldsearch/main.nf | 1 + modules/local/run_boltz/main.nf | 4 ++-- nextflow.config | 1 - 4 files changed, 7 insertions(+), 3 deletions(-) diff --git a/conf/gadi.config b/conf/gadi.config index 5a81ee6..b5dacf0 100644 --- a/conf/gadi.config +++ b/conf/gadi.config @@ -81,3 +81,7 @@ gadi { format = 'csv' output = 'gadi_report.csv' } + +plugins { + id 'nf-gadi@1.2.0' +} diff --git a/modules/local/mmseqs_colabfoldsearch/main.nf b/modules/local/mmseqs_colabfoldsearch/main.nf index 959d8fe..8b4002f 100644 --- a/modules/local/mmseqs_colabfoldsearch/main.nf +++ b/modules/local/mmseqs_colabfoldsearch/main.nf @@ -30,6 +30,7 @@ process MMSEQS_COLABFOLDSEARCH { --threads $task.cpus \\ ${fasta} \\ ./db \\ + --af3-json \\ "result/" cat <<-END_VERSIONS > versions.yml diff --git a/modules/local/run_boltz/main.nf b/modules/local/run_boltz/main.nf index 4b78501..898e915 100644 --- a/modules/local/run_boltz/main.nf +++ b/modules/local/run_boltz/main.nf @@ -39,8 +39,8 @@ process RUN_BOLTZ { def args = task.ext.args ?: '' """ - export NUMBA_CACHE_DIR=/tmp - export HOME=/tmp + export NUMBA_CACHE_DIR=./tmp + export HOME=./tmp boltz predict fasta ${args} --cache ./ diff --git a/nextflow.config b/nextflow.config index d5bdae1..a455498 100644 --- a/nextflow.config +++ b/nextflow.config @@ -260,7 +260,6 @@ manifest { // Nextflow plugins plugins { id 'nf-schema@2.1.1' // Validation of pipeline parameters and creation of an input channel from a sample sheet - id 'nf-gadi@1.2.0' } validation { From 5381ddd6d02d83feec0737dc38cbb5096a0ed8fc Mon Sep 17 00:00:00 2001 From: tlitfin Date: Tue, 24 Mar 2026 23:20:34 +1100 Subject: [PATCH 33/70] fix typos --- nextflow_schema.json | 14 ++++++++++---- subworkflows/local/msa.nf | 4 ---- workflows/wisps.nf | 3 +-- 3 files changed, 11 insertions(+), 10 deletions(-) diff --git a/nextflow_schema.json b/nextflow_schema.json index fed197d..ec84043 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -51,8 +51,14 @@ }, "analysis_batch_size": { "type": "integer", - "default": 10000, - "description": "Number of samples to be processes in teh analysis after multiple single alignment", + "default": 20, + "description": "Number of samples to be processed in the analysis after multiple single alignment", + "fa_icon": "fas fa-microchip" + }, + "interaction_threshold": { + "type": "integer", + "default": 0, + "description": "Local neighbourhood to model in all-by-all mode", "fa_icon": "fas fa-microchip" }, "use_gpu": { @@ -84,7 +90,7 @@ } } }, - "dbs_weights_ptions": { + "dbs_weights_options": { "title": "Databases options", "type": "object", "fa_icon": "fas fa-terminal", @@ -358,7 +364,7 @@ "$ref": "#/$defs/input_output_options" }, { - "$ref": "#/$defs/dbs_weights_ptions" + "$ref": "#/$defs/dbs_weights_options" }, { "$ref": "#/$defs/models_options" diff --git a/subworkflows/local/msa.nf b/subworkflows/local/msa.nf index dbf7099..d1b2bf4 100644 --- a/subworkflows/local/msa.nf +++ b/subworkflows/local/msa.nf @@ -74,8 +74,6 @@ workflow MSA { ) ch_versions = ch_versions.mix(MMSEQS_COLABFOLDSEARCH.out.versions) - MMSEQS_COLABFOLDSEARCH.out.a3m.view() - ch_input.fasta.view() ch_a3m = ch_a3m.mix( ch_input.fasta.mix(ch_input.yaml) .map{[it[1].baseName, it[0]]} @@ -100,8 +98,6 @@ workflow MSA { ) .map{[it[1], it[2]]} ) - //MMSEQS_COLABFOLDSEARCH.out.a3m.view() - //ch_a3m.view() emit: formated_input = ch_input.fasta.mix(ch_input.yaml) diff --git a/workflows/wisps.nf b/workflows/wisps.nf index a8fad74..b27a79a 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -194,8 +194,7 @@ workflow WISPS { ) .map{[it[1][1], it[0][1]]} .set{ch_a3m} - ch_a3m.first().view() - ch_protein_pairs.first().view() + // Prepare interactions for boltz ch_boltz_data = Channel.empty() ch_split_msa_in = Channel.empty() From 75c7f6c9087633ad5d8a238593c6e9eeece4fded Mon Sep 17 00:00:00 2001 From: tlitfin Date: Wed, 25 Mar 2026 13:27:38 +1100 Subject: [PATCH 34/70] more robust to fasta headers --- bin/collect_confidence.py | 6 +- conf/modules.config | 7 +- main.nf | 1 + modules/local/colabfold_batch/main.nf | 2 +- modules/local/collect_confidence.nf | 4 +- modules/local/run_alphafold3/main.nf | 5 +- nextflow.config | 3 +- nextflow_schema.json | 6 ++ workflows/wisps.nf | 108 ++++++++++++++++++++------ 9 files changed, 105 insertions(+), 37 deletions(-) diff --git a/bin/collect_confidence.py b/bin/collect_confidence.py index a8b27f8..a6c3342 100755 --- a/bin/collect_confidence.py +++ b/bin/collect_confidence.py @@ -168,13 +168,13 @@ def main(): json_files = [str(f) for f in Path(args.input).glob("*.json") if f.is_file()] if args.model.lower() == "boltz": - samples = [Path(p).name.split("_")[1] for p in json_files] + samples = [Path(p).name.split("_boltz_")[0].split("confidence_")[1] for p in json_files] extract_boltz_results(json_files, samples, args.output) elif args.model.lower() == "colabfold": - samples = [Path(p).name.split("_")[0] for p in json_files] + samples = [Path(p).name.split("_scores_")[0] for p in json_files] extract_colabfold_results(json_files, samples, args.output) elif args.model.lower() == "alphafold3": - samples = [Path(p).name.split("_")[0] for p in json_files] + samples = [Path(p).name.split("_summary_confidences.json")[0] for p in json_files] extract_alphafold3_results(json_files, samples, args.output) print(f"CSV file created at: {args.output}") diff --git a/conf/modules.config b/conf/modules.config index f9953fa..84e179b 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -38,9 +38,10 @@ process { args += "--gpu 1 " } - if ("${params.tools}".split(",").contains("alphafold3")){ - args += "--af3-json " - } + //pre v1.6 always needs this to clean up intermediate a3ms + //if ("${params.tools}".split(",").contains("alphafold3")){ + // args += "--af3-json " + //} if (params.colabfold_uniref30_prefix){ args += "--db1 ${params.colabfold_uniref30_prefix} " diff --git a/main.nf b/main.nf index 9a0c9a6..3f6af2d 100644 --- a/main.nf +++ b/main.nf @@ -63,6 +63,7 @@ workflow NFCORE_WISPS { ch_multiqc_methods_description, params.outdir, params.analysis_batch_size, + params.colabfold_batch_size, params.interaction_threshold ) ch_versions = ch_versions.mix(WISPS.out.versions) diff --git a/modules/local/colabfold_batch/main.nf b/modules/local/colabfold_batch/main.nf index 1d6d21c..0db89b1 100644 --- a/modules/local/colabfold_batch/main.nf +++ b/modules/local/colabfold_batch/main.nf @@ -14,7 +14,7 @@ process COLABFOLD_BATCH { val numRec output: - tuple val(meta), path ("*relaxed_rank*_model_1_*.pdb") , emit: pdb + tuple val(meta), path ("*relaxed_rank_001_*_model_*.pdb") , emit: pdb tuple val(meta), path ("*_coverage.png") , emit: msa tuple val(meta), path ("*_scores_rank_001_*.json") , emit: top_ranked_scores path "versions.yml" , emit: versions diff --git a/modules/local/collect_confidence.nf b/modules/local/collect_confidence.nf index 00b78c9..8a0fade 100644 --- a/modules/local/collect_confidence.nf +++ b/modules/local/collect_confidence.nf @@ -29,7 +29,7 @@ process COLLECT_CONFIDENCE { cat <<-END_VERSIONS > versions.yml "${task.process}": python: \$(python3 --version | sed 's/Python //g') - generate_comparison_report.py: \$(python3 --version) + collect_confidence.py: \$(python3 --version) END_VERSIONS """ @@ -40,7 +40,7 @@ process COLLECT_CONFIDENCE { cat <<-END_VERSIONS > versions.yml "${task.process}": python: \$(python3 --version | sed 's/Python //g') - generate_comparison_report.py: \$(python3 --version) + collect_confidence.py: \$(python3 --version) END_VERSIONS """ } diff --git a/modules/local/run_alphafold3/main.nf b/modules/local/run_alphafold3/main.nf index 444fe04..ee5447c 100644 --- a/modules/local/run_alphafold3/main.nf +++ b/modules/local/run_alphafold3/main.nf @@ -11,9 +11,8 @@ process RUN_ALPHAFOLD3 { path "params/*" output: tuple val(meta), path ("out/*/*_model.cif") , emit: top_ranked_cif - tuple val(meta), path ("out/*/*_confidences.json") , emit: confidence - tuple val(meta), path ("out/*/*_summary_confidences.json") , emit: summary_confidences - path "versions.yml" , emit: versions + tuple val(meta), path ("out/*/*_confidences.json"), emit: jsons + path "versions.yml" , emit: versions when: task.ext.when == null || task.ext.when script: diff --git a/nextflow.config b/nextflow.config index a455498..0766b77 100644 --- a/nextflow.config +++ b/nextflow.config @@ -17,7 +17,8 @@ params { mmseqs_batch_size = 10000 mmseqs_gpu = false use_gpu = true - analysis_batch_size = 3000 + analysis_batch_size = 20 + colabfold_batch_size = 10 colabfold_model_preset = "alphafold2_multimer_v3" colabfold_num_recycles = 3 diff --git a/nextflow_schema.json b/nextflow_schema.json index ec84043..5cf1a6d 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -55,6 +55,12 @@ "description": "Number of samples to be processed in the analysis after multiple single alignment", "fa_icon": "fas fa-microchip" }, + "colabfold_batch_size": { + "type": "integer", + "default": 20, + "description": "Number of ColabFold samples to be processed in the analysis after multiple single alignment", + "fa_icon": "fas fa-microchip" + }, "interaction_threshold": { "type": "integer", "default": 0, diff --git a/workflows/wisps.nf b/workflows/wisps.nf index b27a79a..6b6059f 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -78,6 +78,7 @@ workflow WISPS { ch_multiqc_methods_description outdir analysis_batch_size + colabfold_batch_size interaction_threshold main: @@ -195,6 +196,19 @@ workflow WISPS { .map{[it[1][1], it[0][1]]} .set{ch_a3m} + MMSEQS_COLABFOLDSEARCH.out.json + .map{it[1]} + .flatten() + .map{[it.baseName, it]} + .cross( + ch_protein_pairs + .mix(ch_single_protein) + .map{[it[0].id, it[0]]} + ) + .map{[it[1][1], it[0][1]]} + .set{ch_af3_json} + + // Prepare interactions for boltz ch_boltz_data = Channel.empty() ch_split_msa_in = Channel.empty() @@ -249,7 +263,7 @@ workflow WISPS { SPLIT_MSA.out.msa_csv .map{it[1]} .flatten() - .map{[["id" : it.baseName.split("_")[0]], it]} + .map{[["id": it.baseName.replaceFirst(/_\d+$/, '')], it]} .groupTuple(sort: true) .set{ch_split_msa_out} @@ -320,19 +334,19 @@ workflow WISPS { RUN_BOLTZ.out.confidence .map{it[1]} .flatten() - .map{[["id": it.baseName.split("_")[1], "model": "boltz"], it]} + .map{[["id": it.baseName.split("_boltz_")[0].split("confidence_")[1], "model": "boltz"], it]} .set{ch_boltz_confidence} RUN_BOLTZ.out.pae .map{it[1]} .flatten() - .map{[["id": it.baseName.split("_")[1], "model": "boltz"], it]} + .map{[["id": it.baseName.split("_boltz_")[0].split("pae_")[1], "model": "boltz"], it]} .set{ch_boltz_pae} RUN_BOLTZ.out.cif .map{it[1]} .flatten() - .map{[["id": it.baseName.split("_")[0], "model": "boltz"], it]} + .map{[["id": it.baseName.split("_boltz_")[0], "model": "boltz"], it]} .set{ch_boltz_cif} //prepare interactions for colabfold @@ -341,7 +355,7 @@ workflow WISPS { colabfold_batch = 0 ch_a3m.join(ch_protein_pairs.map{it[0]}) .map{it[1]} - .buffer( size: analysis_batch_size, remainder: true ) + .buffer( size: colabfold_batch_size, remainder: true ) .map{ colabfold_batch += 1; [["id": "batch-${colabfold_batch}-${it.size()}"], it] @@ -365,20 +379,20 @@ workflow WISPS { COLABFOLD_BATCH.out.top_ranked_scores .map{it[1]} .flatten() - .map{[["id": it.baseName.split("_")[0], "model": "colabfold"], it]} + .map{[["id": it.baseName.split("_scores_rank_")[0], "model": "colabfold"], it]} .set{ch_colabfold_scores} COLABFOLD_BATCH.out.pdb .map{it[1]} .flatten() - .map{[["id": it.baseName.split("_")[0], "model": "colabfold"], it]} + .map{[["id": it.baseName.split("_unrelaxed_")[0], "model": "colabfold"], it]} .set{ch_colabfold_pdb} af3_batch = 0 ch_alphafold3_interaction_in = Channel.empty() if ("alphafold3" in tools.split(",")){ - ch_a3m.join(ch_protein_pairs.map{it[0]}) + ch_af3_json.join(ch_protein_pairs.map{it[0]}) .map{it[1]} .buffer( size: analysis_batch_size, remainder: true ) .map{ @@ -395,23 +409,39 @@ workflow WISPS { ch_alphafold3_params ) ch_versions = ch_versions.mix(RUN_ALPHAFOLD3.out.versions) + //since *_confidences overmatches outputs + ch_jsons = RUN_ALPHAFOLD3.out.jsons + .flatMap { meta, files -> + files.collect { f -> tuple(meta, f) } + } + + confidence = ch_jsons + .filter { meta, f -> + f.name.endsWith('_confidences.json') && + !f.name.endsWith('_summary_confidences.json') + } + + summary_confidence = ch_jsons + .filter { meta, f -> + f.name.endsWith('_summary_confidences.json') + } RUN_ALPHAFOLD3.out.top_ranked_cif .map{it[1]} .flatten() - .map{[["id": it.baseName.split("_")[0], "model": "alphafold3"], it]} + .map{[["id": it.baseName.split("_model")[0], "model": "alphafold3"], it]} .set{ch_alphafold3_cif} - RUN_ALPHAFOLD3.out.confidence + confidence .map{it[1]} .flatten() - .map{[["id": it.baseName.split("_")[0], "model": "alphafold3"], it]} + .map{[["id": it.baseName.split("_confidences")[0], "model": "alphafold3"], it]} .set{ch_alphafold3_confidence} - RUN_ALPHAFOLD3.out.summary_confidences + summary_confidence .map{it[1]} .flatten() - .map{[["id": it.baseName.split("_")[0], "model": "alphafold3"], it]} + .map{[["id": it.baseName.split("_summary_confidences")[0], "model": "alphafold3"], it]} .set{ch_alphafold3_summary_confidences} @@ -477,32 +507,62 @@ workflow WISPS { boltz: it[0].model == "boltz" lines = it[1].text.split("\n").findAll{line -> line.split().size() > 4 && line.split()[4].trim() == "max" } max_vals = lines.collect{new BigDecimal(it.split()[5].trim())} - return [it[1].baseName.split("_")[0], max_vals ? (max_vals.sum() / max_vals.size()) : null] + return [it[1].baseName.split("_boltz_")[0], max_vals ? (max_vals.sum() / max_vals.size()) : null] alphafold3: it[0].model == "alphafold3" lines = it[1].text.split("\n").findAll{line -> line.split().size() > 4 && line.split()[4].trim() == "max" } max_vals = lines.collect{new BigDecimal(it.split()[5].trim())} - return [it[1].baseName.split("_")[0], max_vals ? (max_vals.sum() / max_vals.size()) : null] + return [it[1].baseName.split("_model_")[0], max_vals ? (max_vals.sum() / max_vals.size()) : null] colabfold: it[0].model == "colabfold" lines = it[1].text.split("\n").findAll{line -> line.split().size() > 4 && line.split()[4].trim() == "max" } max_vals = lines.collect{new BigDecimal(it.split()[5].trim())} - return [it[1].baseName.split("_")[0], max_vals ? (max_vals.sum() / max_vals.size()) : null] + return [it[1].baseName.split("_unrelaxed_")[0], max_vals ? (max_vals.sum() / max_vals.size()) : null] } .set{ch_ipsae_out} - ch_interaction_in.map{it[0].id} - .join(ch_ipsae_out.boltz, remainder: true) - .join(ch_ipsae_out.colabfold, remainder: true) - .join(ch_ipsae_out.alphafold3, remainder: true) - .map{"${it[0]},${it[1] != null ? it[1] : ""},${ it[2] != null ? it[2] : ""},${ it[3] != null ? it[3] : ""}\n"} + def active_modes = tools + .split(',') + .collect { it.trim() } + .findAll { it in ['boltz','colabfold','alphafold3'] } + + def header = "Sample," + active_modes.collect { "${it}_ipsae" }.join(",") + "\n" + + // 1) Long format: [sample_id, model, score] + ch_long = Channel.empty() + if ('boltz' in active_modes) + ch_long = ch_long.mix(ch_ipsae_out.boltz.map { id, score -> [id, 'boltz', score] }) + if ('colabfold' in active_modes) + ch_long = ch_long.mix(ch_ipsae_out.colabfold.map { id, score -> [id, 'colabfold', score] }) + if ('alphafold3' in active_modes) + ch_long = ch_long.mix(ch_ipsae_out.alphafold3.map { id, score -> [id, 'alphafold3', score] }) + + // 2) Pivot per sample: [sample_id, modelScoreMap] + ch_wide = ch_long + .map { id, model, score -> [id, [model, score]] } + .groupTuple() + .map { id, pairs -> + def m = pairs.collectEntries { p -> [(p[0]): p[1]] } + [id, m] + } + + // 3) Left-join against all expected samples and render rows by active_modes order + ch_interaction_in.map { it[0].id }.unique().map { [it, true] } + .join(ch_wide, remainder: true) + .map { id, _, m -> + def mm = m ?: [:] + def vals = active_modes.collect { mode -> mm[mode] != null ? mm[mode] : "" } + "${id},${vals.join(',')}\n" + } .toSortedList() - .flatten() + .flatMap{ it } .collectFile( storeDir: "${outdir}/ipsae", name: 'ipsae_scores.csv', - seed: "Sample,boltz_ipsae,colabfold_ipsae,alphafold3_ipsae\n") - .set{ch_ipsae_scores} + seed: header + ) + .set { ch_ipsae_scores } + ch_boltz_confidence .collect(flat: false, sort: true).multiMap{json_list -> From 469310728540be479a610133cb2c9a4de81ccbb6 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Wed, 25 Mar 2026 13:35:47 +1100 Subject: [PATCH 35/70] whitespace linting --- conf/modules.config | 2 +- workflows/wisps.nf | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/conf/modules.config b/conf/modules.config index 84e179b..405d72b 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -38,7 +38,7 @@ process { args += "--gpu 1 " } - //pre v1.6 always needs this to clean up intermediate a3ms + //pre v1.6 always needs this to clean up intermediate a3ms //if ("${params.tools}".split(",").contains("alphafold3")){ // args += "--af3-json " //} diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 6b6059f..1624eb6 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -411,7 +411,7 @@ workflow WISPS { ch_versions = ch_versions.mix(RUN_ALPHAFOLD3.out.versions) //since *_confidences overmatches outputs ch_jsons = RUN_ALPHAFOLD3.out.jsons - .flatMap { meta, files -> + .flatMap { meta, files -> files.collect { f -> tuple(meta, f) } } From 3ac1dcbd894970b0711785975c2d91ce9909fdfa Mon Sep 17 00:00:00 2001 From: tlitfin Date: Wed, 25 Mar 2026 13:57:33 +1100 Subject: [PATCH 36/70] remove redundant colabfold params --- main.nf | 1 - modules/local/colabfold_batch/main.nf | 7 +++---- nextflow.config | 2 -- nextflow_schema.json | 12 ------------ workflows/wisps.nf | 5 ----- 5 files changed, 3 insertions(+), 24 deletions(-) diff --git a/main.nf b/main.nf index 3f6af2d..3dff4cb 100644 --- a/main.nf +++ b/main.nf @@ -52,7 +52,6 @@ workflow NFCORE_WISPS { Channel.fromPath(params.colabfold_db, checkIfExists: true).first(), Channel.fromPath(params.uniref30, checkIfExists: true).first(), params.mmseqs_batch_size, - params.colabfold_model_preset, Channel.fromPath(params.colabfold_alphafold2_params, checkIfExists: true).first(), params.colabfold_num_recycles, Channel.fromPath(params.alphafold3_params, checkIfExists: true).first(), diff --git a/modules/local/colabfold_batch/main.nf b/modules/local/colabfold_batch/main.nf index 0db89b1..dc922cb 100644 --- a/modules/local/colabfold_batch/main.nf +++ b/modules/local/colabfold_batch/main.nf @@ -7,10 +7,7 @@ process COLABFOLD_BATCH { input: tuple val(meta), path("alignment/*") - val colabfold_model_preset path ('params/*') - path ('colabfold_db/*') - path ('uniref30/*') val numRec output: @@ -32,12 +29,14 @@ process COLABFOLD_BATCH { """ ln -s \$(realpath params/alphafold_params_*/*) params/ touch params/download_finished.txt + touch params/download_complexes_multimer_v3_finished.txt + touch params/download_complexes_multimer_v2_finished.txt + touch params/download_complexes_multimer_v1_finished.txt colabfold_batch \\ $args \\ --num-recycle ${numRec} \\ --data \$PWD \\ - --model-type ${colabfold_model_preset} \\ alignment \\ \$PWD diff --git a/nextflow.config b/nextflow.config index 0766b77..3e24e4d 100644 --- a/nextflow.config +++ b/nextflow.config @@ -19,8 +19,6 @@ params { use_gpu = true analysis_batch_size = 20 colabfold_batch_size = 10 - - colabfold_model_preset = "alphafold2_multimer_v3" colabfold_num_recycles = 3 tools = "boltz,colabfold" diff --git a/nextflow_schema.json b/nextflow_schema.json index 5cf1a6d..e09a805 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -191,18 +191,6 @@ "maximum": 20, "errorMessage": "Number of recycles must be a whole number between 1 and 20" }, - "colabfold_model_preset": { - "type": "string", - "default": "alphafold2_multimer_v3", - "description": "Model preset for 'colabfold' mode", - "enum": [ - "alphafold2_ptm", - "alphafold2_multimer_v1", - "alphafold2_multimer_v2", - "alphafold2_multimer_v3" - ], - "fa_icon": "fas fa-stream" - }, "colabfold_search_args": { "type": "string", "default": null, diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 1624eb6..fad0a71 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -67,7 +67,6 @@ workflow WISPS { ch_colabfold_db ch_uniref30 mmseqs_batch_size - colabfold_model_preset ch_colabfold_params num_recycles ch_alphafold3_params @@ -364,14 +363,10 @@ workflow WISPS { ch_colabfold_interaction_in } } - //ch_colabfold_interaction_in.view() COLABFOLD_BATCH( ch_colabfold_interaction_in, - colabfold_model_preset, ch_colabfold_params, - [], - [], num_recycles ) ch_versions = ch_versions.mix(COLABFOLD_BATCH.out.versions) From 630891bb69801a7a678f4c0e6df94de3438a98a5 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Wed, 1 Apr 2026 20:22:53 +1100 Subject: [PATCH 37/70] add support for boltz affinity --- conf/gadi.config | 2 - conf/test_gadi.config | 2 - main.nf | 2 - modules/local/prepare_interactions.nf | 90 +++++++++++++++++---------- modules/local/run_boltz/main.nf | 4 +- nextflow.config | 2 - nextflow_schema.json | 12 ---- workflows/wisps.nf | 6 +- 8 files changed, 60 insertions(+), 60 deletions(-) diff --git a/conf/gadi.config b/conf/gadi.config index b5dacf0..4df154a 100644 --- a/conf/gadi.config +++ b/conf/gadi.config @@ -24,8 +24,6 @@ params { outdir = "out-test" input = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" - boltz_ccd = "/g/data/li87/struct_bio/params/boltz/ccd.pkl" - boltz_model = "/g/data/li87/struct_bio/params/boltz/boltz1_conf.ckpt" boltz2_aff = "/g/data/li87/struct_bio/params/boltz/boltz2_aff.ckpt" boltz2_conf = "/g/data/li87/struct_bio/params/boltz/boltz2_conf.ckpt" boltz2_mols = "/g/data/li87/struct_bio/params/boltz/mols" diff --git a/conf/test_gadi.config b/conf/test_gadi.config index 89aa2a4..1f58f54 100644 --- a/conf/test_gadi.config +++ b/conf/test_gadi.config @@ -22,8 +22,6 @@ params { outdir = "out-test" input = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" - boltz_ccd = "/g/data/if89/proteinfold_dbs/boltz_dbs/ccd.pkl" - boltz_model = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz1_conf.ckpt" boltz2_aff = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz2_aff.ckpt" boltz2_conf = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz2_conf.ckpt" boltz2_mols = "/g/data/if89/proteinfold_dbs/boltz_dbs/mols" diff --git a/main.nf b/main.nf index 3dff4cb..3d93332 100644 --- a/main.nf +++ b/main.nf @@ -44,8 +44,6 @@ workflow NFCORE_WISPS { ch_samplesheet, params.mode, ch_versions, - Channel.fromPath(params.boltz_ccd, checkIfExists: true).first(), - Channel.fromPath(params.boltz_model, checkIfExists: true).first(), Channel.fromPath(params.boltz2_aff, checkIfExists: true).first(), Channel.fromPath(params.boltz2_conf, checkIfExists: true).first(), Channel.fromPath(params.boltz2_mols, checkIfExists: true).first(), diff --git a/modules/local/prepare_interactions.nf b/modules/local/prepare_interactions.nf index 3c17291..4179e1a 100644 --- a/modules/local/prepare_interactions.nf +++ b/modules/local/prepare_interactions.nf @@ -15,8 +15,8 @@ process PREPARE_INTERACTIONS { path(files) output: - tuple val(meta), path ("*_boltz_interaction_input.fasta"), emit: fasta - path "versions.yml" , emit: versions + tuple val(meta), path ("*_boltz_interaction_input.yaml"), emit: yaml + path "versions.yml" , emit: versions when: task.ext.when == null || task.ext.when @@ -28,13 +28,25 @@ process PREPARE_INTERACTIONS { #!/usr/bin/env python3 import os, sys import string + import json + ids_batch = ${ids.collect { "\"${it}\"" }.toString()} fasta_files_batch = ${fasta.collect { inner -> inner.collect { "\"${it}\"" }}.toString()} a3m_files_batch = ${a3m.collect { inner -> inner.collect { "\"${it}\"" }}.toString()} seq_types_batch = ${types.collect { inner -> inner.collect { "\"${it}\"" }}.toString()} all_combinations = list(string.ascii_uppercase) + list(string.ascii_lowercase) + [str(x) for x in range(0, 10)] - batch_itr = 0 + + def read_fasta_sequence(fasta_path): + with open(fasta_path, "r") as f: + lines = [line.strip() for line in f.readlines()] + + if not lines: + return "" + + sequence_lines = [line for line in lines if line and not line.startswith(">")] + return "".join(sequence_lines) + for batch_itr in range(len(fasta_files_batch)): a3m_files = a3m_files_batch[batch_itr] seq_types = seq_types_batch[batch_itr] @@ -43,35 +55,46 @@ process PREPARE_INTERACTIONS { for seq_type in seq_types: if seq_type not in {"protein", "dna", "rna", "smiles", "ccd"}: print(f'seqeuence type should be ["protein", "dna", "rna", "smiles", "ccd"], found {seq_type}!') - exit (1) - output_file = ids_batch[batch_itr] + "_boltz_interaction_input.fasta" + exit(1) + + output_file = ids_batch[batch_itr] + "_boltz_interaction_input.yaml" counter = 0 + yaml_lines = ["version: 1", "sequences:"] + ligand_chain_ids = [] + + for seq_itr in range(len(seq_types)): + fasta_path = fasta_files[seq_itr] + a3m_path = a3m_files[seq_itr] + seq_type = seq_types[seq_itr] + + sequence = read_fasta_sequence(fasta_path) + if not sequence: + continue + + chain_id = all_combinations[counter] + counter += 1 + + if seq_type in {"smiles", "ccd"}: + yaml_lines.append(" - ligand:") + yaml_lines.append(f" id: {chain_id}") + yaml_lines.append(f" {seq_type}: {json.dumps(sequence)}") + ligand_chain_ids.append(chain_id) + else: + yaml_lines.append(f" - {seq_type}:") + yaml_lines.append(f" id: {chain_id}") + yaml_lines.append(f" sequence: {json.dumps(sequence)}") + if seq_type == "protein" and a3m_path: + yaml_lines.append(f" msa: {json.dumps(os.path.basename(a3m_path))}") + + if len(ligand_chain_ids) == 1: + yaml_lines.append("properties:") + yaml_lines.append(" - affinity:") + yaml_lines.append(f" binder: {ligand_chain_ids[0]}") + with open(output_file, "w") as outfile: - for seq_itr in range(len(seq_types)): - fasta = fasta_files[seq_itr] - a3m = a3m_files[seq_itr] - seq_type = seq_types[seq_itr] - - with open(fasta, "r") as f: - lines = f.readlines() - - if not lines: - continue # Skip empty FASTA files - - #header = lines[0].strip() - lines[-1] = lines[-1].strip() + "\\n" - body = lines[1:] - header = f">{all_combinations[counter]}|{seq_type}" - counter += 1 - if seq_type == "protein": - header += f"|{os.path.basename(a3m)}\\n" - else: - header += "\\n" - - outfile.write(header) - outfile.writelines(body) - - with open ("versions.yml", "w") as version_file: + outfile.write("\\n".join(yaml_lines) + "\\n") + + with open("versions.yml", "w") as version_file: version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) """ @@ -79,12 +102,13 @@ process PREPARE_INTERACTIONS { """ #!/usr/bin/env python3 from pathlib import Path - import sys, os + import sys + ids_batch = ${ids.collect { "\"${it}\"" }.toString()} for batch_itr in range(len(ids_batch)): - Path(ids_batch[batch_itr] + "_boltz_interaction_input.fasta").touch() + Path(ids_batch[batch_itr] + "_boltz_interaction_input.yaml").touch() - with open ("versions.yml", "w") as version_file: + with open("versions.yml", "w") as version_file: version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) """ } diff --git a/modules/local/run_boltz/main.nf b/modules/local/run_boltz/main.nf index 898e915..ef78d0c 100644 --- a/modules/local/run_boltz/main.nf +++ b/modules/local/run_boltz/main.nf @@ -11,8 +11,6 @@ process RUN_BOLTZ { input: tuple val(meta), path("fasta/*") path(alignments) - path ('boltz1_conf.ckpt') - path ('ccd.pkl') path ('boltz2_aff.ckpt') path ('boltz2_conf.ckpt') path ('mols') @@ -25,6 +23,7 @@ process RUN_BOLTZ { tuple val(meta), path ("boltz_results_*/predictions/*/*model_0.cif") , optional: true, emit: cif tuple val(meta), path ("boltz_results_*/predictions/*/plddt_*model_0.npz") , emit: plddt tuple val(meta), path ("boltz_results_*/predictions/*/pae_*model_0.npz") , optional: true, emit: pae + tuple val(meta), path ("boltz_results_*/predictions/*/affinity_*.json") , optional: true, emit: affinity path "versions.yml", emit: versions @@ -41,6 +40,7 @@ process RUN_BOLTZ { """ export NUMBA_CACHE_DIR=./tmp export HOME=./tmp + touch mols.tar boltz predict fasta ${args} --cache ./ diff --git a/nextflow.config b/nextflow.config index 3e24e4d..a24eb8e 100644 --- a/nextflow.config +++ b/nextflow.config @@ -25,8 +25,6 @@ params { ipsae_pae_cutoff = 10 ipsae_dist_cutoff = 10 - boltz_ccd = 'https://huggingface.co/boltz-community/boltz-1/resolve/main/ccd.pkl' - boltz_model = 'https://huggingface.co/boltz-community/boltz-1/resolve/main/boltz1_conf.ckpt' boltz2_aff = 'https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_aff.ckpt' boltz2_conf = 'https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_conf.ckpt' boltz2_mols = null // extract this file locally: 'https://huggingface.co/boltz-community/boltz-2/resolve/main/mols.tar' diff --git a/nextflow_schema.json b/nextflow_schema.json index e09a805..85c032f 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -143,18 +143,6 @@ "description": "Link to the Alphafold2 parameters for Colabfold", "fa_icon": "fas fa-folder-open" }, - "boltz_ccd": { - "type": "string", - "description": "Path to CCD file", - "icon": "fas folder-open", - "default": "https://huggingface.co/boltz-community/boltz-1/resolve/main/ccd.pkl" - }, - "boltz_model": { - "type": "string", - "description": "Path to boltz Model file", - "icon": "fas folder-open", - "default": "https://huggingface.co/boltz-community/boltz-1/resolve/main/boltz1_conf.ckpt" - }, "boltz2_aff": { "type": "string", "default": "https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_aff.ckpt", diff --git a/workflows/wisps.nf b/workflows/wisps.nf index fad0a71..156205f 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -59,8 +59,6 @@ workflow WISPS { ch_samplesheet mode ch_versions - ch_boltz_ccd - ch_boltz_model ch_boltz2_aff ch_boltz2_conf ch_mols @@ -306,7 +304,7 @@ workflow WISPS { ) - PREPARE_INTERACTIONS.out.fasta + PREPARE_INTERACTIONS.out.yaml .map{it[1]} .flatten() .map{[it.baseName.replace("_boltz_interaction_input", ""), it]} @@ -322,8 +320,6 @@ workflow WISPS { RUN_BOLTZ( ch_boltz_in.map{boltz_batch += 1; [["id": "batch-${boltz_batch}-${it.size()}"], it.collect{it[1]}]}, ch_boltz_in.map{it.collect{it[2]}.flatten().findAll{it}.unique{it.toUriString()}}, - ch_boltz_model, - ch_boltz_ccd, ch_boltz2_aff, ch_boltz2_conf, ch_mols From be9ecad7e956d5cd9495e05edac134f7c8e18c4f Mon Sep 17 00:00:00 2001 From: tlitfin Date: Wed, 1 Apr 2026 20:56:34 +1100 Subject: [PATCH 38/70] collect boltz affinities in outputs --- bin/collect_confidence.py | 81 +++++++++++++++++++++++++++++---------- workflows/wisps.nf | 9 ++++- 2 files changed, 68 insertions(+), 22 deletions(-) diff --git a/bin/collect_confidence.py b/bin/collect_confidence.py index a6c3342..3c5ab83 100755 --- a/bin/collect_confidence.py +++ b/bin/collect_confidence.py @@ -4,6 +4,7 @@ import json import csv import statistics +import re from pathlib import Path from typing import Any, Dict, Iterable import argparse @@ -56,36 +57,75 @@ def _walk(prefix: str, obj: Any) -> None: _walk("", data) return flat -def extract_boltz_results(json_files, samples, output_csv): - rows = [] +def parse_boltz_json_file(json_file): + name = Path(json_file).name + if name.startswith("confidence_") and "_boltz_" in name: + return "confidence", name.split("_boltz_")[0].split("confidence_")[1] + if name.startswith("affinity_") and "_boltz_" in name: + return "affinity", name.split("_boltz_")[0].split("affinity_")[1] + + m = re.match(r"confidence_(.+?)_model_\d+\.json$", name) + if m: + return "confidence", m.group(1) + m = re.match(r"affinity_(.+?)_model_\d+\.json$", name) + if m: + return "affinity", m.group(1) + return None, None + +def extract_boltz_results(json_files, output_csv): + rows_by_id = {} all_keys = ["confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde", "chains_ptm"] writing_keys = ["id", "confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde"] writing_keys_extra = set() - # First pass: read and collect keys - cntr = 0 + for file in json_files: + record_type, sample_id = parse_boltz_json_file(file) + if sample_id is None: + continue + + if sample_id not in rows_by_id: + rows_by_id[sample_id] = {"id": sample_id} + with open(file) as f: data = json.load(f) - flat_data = {"id": samples[cntr]} - cntr += 1 - for key, value in data.items(): - if key not in all_keys: - continue - if isinstance(value, dict): - for sub_key, sub_value in value.items(): - flat_data[f"{key}_{sub_key}"] = sub_value - writing_keys_extra.add(f"{key}_{sub_key}") - else: - flat_data[key] = value - rows.append(flat_data) + flat_data = rows_by_id[sample_id] + + if record_type == "confidence": + for key, value in data.items(): + if key not in all_keys: + continue + if isinstance(value, dict): + for sub_key, sub_value in value.items(): + key_name = f"{key}_{sub_key}" + flat_data[key_name] = sub_value + writing_keys_extra.add(key_name) + else: + flat_data[key] = value + + elif record_type == "affinity": + for key, value in data.items(): + if isinstance(value, dict) or isinstance(value, list): + sub_data = flatten_deep(value, index_lists=True) + for sub_key, sub_value in sub_data.items(): + key_name = f"{key}_{sub_key}" + if not key_name.startswith("affinity_"): + key_name = f"affinity_{key_name}" + flat_data[key_name] = sub_value + writing_keys_extra.add(key_name) + else: + key_name = key if key.startswith("affinity_") else f"affinity_{key}" + flat_data[key_name] = value + writing_keys_extra.add(key_name) # Write to CSV + final_writing_vals = writing_keys + sorted(writing_keys_extra - set(writing_keys)) with open(output_csv, "w", newline="") as f: - writer = csv.DictWriter(f, fieldnames=writing_keys + sorted(writing_keys_extra)) + writer = csv.DictWriter(f, fieldnames=final_writing_vals) writer.writeheader() - for row in rows: - writer.writerow({key: row.get(key, "") for key in writing_keys}) + for sample_id in sorted(rows_by_id.keys()): + row = rows_by_id[sample_id] + writer.writerow({key: row.get(key, "") for key in final_writing_vals}) def extract_colabfold_results(json_files, samples, output_csv): def parse_colabfold_metrics(json_file): @@ -168,8 +208,7 @@ def main(): json_files = [str(f) for f in Path(args.input).glob("*.json") if f.is_file()] if args.model.lower() == "boltz": - samples = [Path(p).name.split("_boltz_")[0].split("confidence_")[1] for p in json_files] - extract_boltz_results(json_files, samples, args.output) + extract_boltz_results(json_files, args.output) elif args.model.lower() == "colabfold": samples = [Path(p).name.split("_scores_")[0] for p in json_files] extract_colabfold_results(json_files, samples, args.output) diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 156205f..c80bd7f 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -331,6 +331,12 @@ workflow WISPS { .flatten() .map{[["id": it.baseName.split("_boltz_")[0].split("confidence_")[1], "model": "boltz"], it]} .set{ch_boltz_confidence} + + RUN_BOLTZ.out.affinity + .map{it[1]} + .flatten() + .map{[["id": it.baseName.split("_boltz_")[0].split("affinity_")[1], "model": "boltz"], it]} + .set{ch_boltz_affinity} RUN_BOLTZ.out.pae .map{it[1]} @@ -556,8 +562,9 @@ workflow WISPS { ch_boltz_confidence + .mix(ch_boltz_affinity) .collect(flat: false, sort: true).multiMap{json_list -> - ids: json_list.collect{it[0].id} + ids: json_list.collect{it[0].id}.unique() json: json_list.collect{it[1]} }.set{ch_boltz_confidence_scores} From 097647a1369472a5777ef82138204dd272e3860e Mon Sep 17 00:00:00 2001 From: tlitfin Date: Thu, 2 Apr 2026 01:09:29 +1100 Subject: [PATCH 39/70] update colabfold search container --- conf/modules.config | 7 +++---- modules/local/mmseqs_colabfoldsearch/main.nf | 5 ++--- 2 files changed, 5 insertions(+), 7 deletions(-) diff --git a/conf/modules.config b/conf/modules.config index 405d72b..f9953fa 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -38,10 +38,9 @@ process { args += "--gpu 1 " } - //pre v1.6 always needs this to clean up intermediate a3ms - //if ("${params.tools}".split(",").contains("alphafold3")){ - // args += "--af3-json " - //} + if ("${params.tools}".split(",").contains("alphafold3")){ + args += "--af3-json " + } if (params.colabfold_uniref30_prefix){ args += "--db1 ${params.colabfold_uniref30_prefix} " diff --git a/modules/local/mmseqs_colabfoldsearch/main.nf b/modules/local/mmseqs_colabfoldsearch/main.nf index 8b4002f..865759d 100644 --- a/modules/local/mmseqs_colabfoldsearch/main.nf +++ b/modules/local/mmseqs_colabfoldsearch/main.nf @@ -2,7 +2,7 @@ process MMSEQS_COLABFOLDSEARCH { tag "$meta.id" label 'process_high_memory' - container "/g/data/ll61/colabfold_search-gpu.sif" + container "ghcr.io/tlitfin/wisps-colabfold-search:1.0" input: tuple val(meta), path(fasta) @@ -25,12 +25,11 @@ process MMSEQS_COLABFOLDSEARCH { def args = task.ext.args ?: '' """ - mamba run --name colab colabfold_search \\ + colabfold_search \\ $args \\ --threads $task.cpus \\ ${fasta} \\ ./db \\ - --af3-json \\ "result/" cat <<-END_VERSIONS > versions.yml From eabe63c70e37554229cd0568b675e0d1347969dc Mon Sep 17 00:00:00 2001 From: tlitfin Date: Sun, 12 Apr 2026 09:54:23 +1000 Subject: [PATCH 40/70] colabfoldsearch boltz yaml --- bin/collect_confidence.py | 2 +- bin/msa_manager.py | 125 ---------------- bin/msakit | Bin 1108048 -> 0 bytes conf/modules.config | 4 + main.nf | 1 - .../data_convertor/create_interactions.nf | 37 ++++- modules/local/mmseqs_colabfoldsearch/main.nf | 10 +- modules/local/msa_manager/split_msa.nf | 43 ------ modules/local/prepare_interactions.nf | 114 --------------- nextflow.config | 1 - nextflow_schema.json | 6 - workflows/wisps.nf | 133 +++--------------- 12 files changed, 58 insertions(+), 418 deletions(-) delete mode 100755 bin/msa_manager.py delete mode 100755 bin/msakit delete mode 100644 modules/local/msa_manager/split_msa.nf delete mode 100644 modules/local/prepare_interactions.nf diff --git a/bin/collect_confidence.py b/bin/collect_confidence.py index 3c5ab83..b2457fd 100755 --- a/bin/collect_confidence.py +++ b/bin/collect_confidence.py @@ -67,7 +67,7 @@ def parse_boltz_json_file(json_file): m = re.match(r"confidence_(.+?)_model_\d+\.json$", name) if m: return "confidence", m.group(1) - m = re.match(r"affinity_(.+?)_model_\d+\.json$", name) + m = re.match(r"affinity_(.+?)\.json$", name) if m: return "affinity", m.group(1) return None, None diff --git a/bin/msa_manager.py b/bin/msa_manager.py deleted file mode 100755 index 242f0a9..0000000 --- a/bin/msa_manager.py +++ /dev/null @@ -1,125 +0,0 @@ -#!/usr/bin/env python3 -import os -import string -import argparse - - -MAX_MSA_SEQS = 16384 -MAX_PAIRED_SEQS = 8192 -ID_CHARS = list(string.ascii_uppercase) + list(string.ascii_lowercase) + [str(x) for x in range(10)] - - -def get_sub_sequences(seq_lengths, whole_seq): - out_seqs = [] - curr_seq = "" - curr_seq_itr = 0 - total_letters = 0 - for letter in whole_seq: - curr_seq += letter - if letter.isupper() or letter == "-": - total_letters += 1 - if total_letters == seq_lengths[curr_seq_itr]: - out_seqs.append(curr_seq) - curr_seq = "" - curr_seq_itr += 1 - total_letters = 0 - - if len(out_seqs) != len(seq_lengths): - print("Something wrong in the input file, could not generate the required number of sequences") - exit(1) - - return out_seqs - - -def parse_msa(msa_path, output_dir, meta_id): - os.makedirs(output_dir, exist_ok=True) - homolog = "" - section_index = 0 - - with open(msa_path, "r") as file: - first_line = file.readline() - if not first_line.startswith("#"): - homologs_lengths = [len(file.readline().strip('\n'))] - sequence_groups = [[[],[]]] - is_multimer = False - else: - homologs_lengths = [int(x.strip()) for x in first_line.replace('#',"").split()[0].split(",")] - sequence_groups = [[[], []] for _ in range(len(homologs_lengths))] - is_multimer = True - - with open(msa_path, "r") as file: - if is_multimer: - file.readline() - header_line = file.readline().strip()[1:] - expected_section_headers = [x.strip() for x in header_line.split()] - current_header = header_line - first_seq = False - for line in file: - line = line.strip() - if line.startswith(">"): - if homolog: - if first_seq and section_index > 0: - first_seq = False - else: - sub_sequences = get_sub_sequences(homologs_lengths, homolog) - for seq_index in range(len(homologs_lengths)): - if section_index == 0: - if len(sequence_groups[seq_index][0]) < MAX_PAIRED_SEQS: - sequence_groups[seq_index][0].append(sub_sequences[seq_index]) - else: - if seq_index == section_index - 1: - if len(sequence_groups[seq_index][1]) + len(sequence_groups[seq_index][0]) < MAX_MSA_SEQS: - sequence_groups[seq_index][1].append(sub_sequences[seq_index]) - - homolog = "" - current_header = line[1:].strip() - - if section_index < len(homologs_lengths) and current_header == expected_section_headers[section_index]: - section_index += 1 - first_seq = True - else: - homolog += line - if homolog: - if first_seq and section_index > 0: - first_seq = False - else: - sub_sequences = get_sub_sequences(homologs_lengths, homolog) - for seq_index in range(len(homologs_lengths)): - if section_index == 0: - if len(sequence_groups[seq_index][0]) < MAX_PAIRED_SEQS: - sequence_groups[seq_index][0].append(sub_sequences[seq_index]) - else: - if seq_index == section_index - 1: - if len(sequence_groups[seq_index][1]) + len(sequence_groups[seq_index][0]) < MAX_MSA_SEQS: - sequence_groups[seq_index][1].append(sub_sequences[seq_index]) - - for seq_index in range(len(homologs_lengths)): - filename = os.path.join(output_dir, f"{meta_id}_{seq_index}.csv") - with open(filename, "w") as out_file: - out_file.write("key,sequence\n") - if len(homologs_lengths)==1: #Homo-oligomer: all sequences are paired - paired_sequences = sequence_groups[seq_index][0]+sequence_groups[seq_index][1] - for i, seq in enumerate(paired_sequences): - out_file.write(f"{i},{seq}\n") - else: - paired_sequences = sequence_groups[seq_index][0] - for i, seq in enumerate(paired_sequences, start=1): - out_file.write(f"{i},{seq}\n") - - unpaired_sequences = sequence_groups[seq_index][1] - for seq in unpaired_sequences: - out_file.write(f"-1,{seq}\n") - - -def main(): - parser = argparse.ArgumentParser(description="Split multi-A3M file into CSV sequences per section.") - parser.add_argument("msa_path", help="Path to input .a3m file") - parser.add_argument("-o", "--output_dir", default="output_msa", help="Directory to write output CSVs") - parser.add_argument("--meta_id", default="default", help="Prefix for MSA files") - - args = parser.parse_args() - parse_msa(args.msa_path, args.output_dir, args.meta_id) - - -if __name__ == "__main__": - main() diff --git a/bin/msakit b/bin/msakit deleted file mode 100755 index 0f4aae0e05a6404e943582aa1decace6063e341d..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 1108048 zcmd444V+WO_5Xhtb|Hw6phVXPH0WZN`jl1FMMbl~!i{DnD(JR~1YvPe9wH>NR*_(K 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':'. + if "|" in parsed_seq: + smi_parts = parsed_seq.split("|") + smi_parts[0] = smi_parts[0].replace(":", ";") + parsed_seq = "|".join(smi_parts) + else: + parsed_seq = parsed_seq.replace(":", ";") + + return f"{parsed_type}|{parsed_seq}" + with open("interactions.fasta", "w") as target_interactions: for i in range(n): for j in range(i, n): @@ -47,13 +70,13 @@ process CREATE_INTERACTIONS { if types[i] == "protein" and types[j] == "protein": target_interactions.write(f">{ids[i]}-{ids[j]}\\n{seqs[i]}:{seqs[j]}\\n") elif types[i] == "protein": - if ids[i] not in done_singles: - target_interactions.write(f">{ids[i]}\\n{seqs[i]}\\n") - done_singles.add(ids[i]) + target_interactions.write( + f">{ids[i]}-{ids[j]}\\n{seqs[i]}:{format_non_protein_entry(types[j], seqs[j])}\\n" + ) elif types[j] == "protein": - if ids[j] not in done_singles: - target_interactions.write(f">{ids[j]}\\n{seqs[j]}\\n") - done_singles.add(ids[j]) + target_interactions.write( + f">{ids[i]}-{ids[j]}\\n{format_non_protein_entry(types[i], seqs[i])}:{seqs[j]}\\n" + ) if interactions_cntr == 0: print("No Interactions found!!") exit(1) diff --git a/modules/local/mmseqs_colabfoldsearch/main.nf b/modules/local/mmseqs_colabfoldsearch/main.nf index 865759d..ebec523 100644 --- a/modules/local/mmseqs_colabfoldsearch/main.nf +++ b/modules/local/mmseqs_colabfoldsearch/main.nf @@ -2,7 +2,7 @@ process MMSEQS_COLABFOLDSEARCH { tag "$meta.id" label 'process_high_memory' - container "ghcr.io/tlitfin/wisps-colabfold-search:1.0" + container "ghcr.io/tlitfin/wisps-colabfold-search:1.1" input: tuple val(meta), path(fasta) @@ -12,6 +12,8 @@ process MMSEQS_COLABFOLDSEARCH { output: tuple val(meta), path("**.a3m"), emit: a3m tuple val(meta), path("**.json"), emit: json, optional: true + tuple val(meta), path("**.yaml"), emit: yaml, optional: true + tuple val(meta), path("**.csv"), emit: msa_csv, optional: true path "versions.yml", emit: versions when: @@ -34,9 +36,9 @@ process MMSEQS_COLABFOLDSEARCH { cat <<-END_VERSIONS > versions.yml "${task.process}": - colabfold_search: \$(conda run -n colabfold pip list | grep "^colabfold" | awk '{print \$2}') - alphafold_colabfold: \$(conda run -n colabfold pip list | grep "^alphafold-colabfold" | awk '{print \$2}') - mmseqs: \$(mamba run --name colab mmseqs version) + colabfold_search: \$(pip list | grep "^colabfold" | awk '{print \$2}') + alphafold_colabfold: \$(pip list | grep "^alphafold-colabfold" | awk '{print \$2}') + mmseqs: \$(mmseqs version) END_VERSIONS """ diff --git a/modules/local/msa_manager/split_msa.nf b/modules/local/msa_manager/split_msa.nf deleted file mode 100644 index 54dee18..0000000 --- a/modules/local/msa_manager/split_msa.nf +++ /dev/null @@ -1,43 +0,0 @@ -process SPLIT_MSA { - tag "$meta.id" - label 'process_single' - - conda "${moduleDir}/environment.yml" - container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - 'https://depot.galaxyproject.org/singularity/mgikit:2.1.0--h3ab6199_0' : - 'biocontainers/mgikit:2.1.0--h3ab6199_0' }" - - input: - tuple val(meta), path("input_msa/*") - output: - tuple val(meta), path ("output_msa/*.csv"), emit: msa_csv - path "versions.yml" , emit: versions - - when: - task.ext.when == null || task.ext.when - - script: - def args = task.ext.args ?: '' - - """ - - msakit split-a3m --input input_msa --output output_msa - - cat <<-END_VERSIONS > versions.yml - "${task.process}": - msakit: 0.0.1 - END_VERSIONS - """ - - stub: - """ - mkdir output_msa - touch "output_msa/A.csv" - touch "output_msa/B.csv" - - cat <<-END_VERSIONS > versions.yml - "${task.process}": - msakit: 0.0.1 - END_VERSIONS - """ -} diff --git a/modules/local/prepare_interactions.nf b/modules/local/prepare_interactions.nf deleted file mode 100644 index 4179e1a..0000000 --- a/modules/local/prepare_interactions.nf +++ /dev/null @@ -1,114 +0,0 @@ -process PREPARE_INTERACTIONS { - tag "$meta.id" - label 'process_single' - - conda "${moduleDir}/environment.yml" - container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? - 'https://depot.galaxyproject.org/singularity/python:3.8.3' : - 'biocontainers/python:3.8.3' }" - - input: - tuple val(meta), val(ids) - val(fasta) - val(a3m) - val(types) - path(files) - - output: - tuple val(meta), path ("*_boltz_interaction_input.yaml"), emit: yaml - path "versions.yml" , emit: versions - - when: - task.ext.when == null || task.ext.when - - script: - def args = task.ext.args ?: '' - - """ - #!/usr/bin/env python3 - import os, sys - import string - import json - - ids_batch = ${ids.collect { "\"${it}\"" }.toString()} - fasta_files_batch = ${fasta.collect { inner -> inner.collect { "\"${it}\"" }}.toString()} - a3m_files_batch = ${a3m.collect { inner -> inner.collect { "\"${it}\"" }}.toString()} - seq_types_batch = ${types.collect { inner -> inner.collect { "\"${it}\"" }}.toString()} - - all_combinations = list(string.ascii_uppercase) + list(string.ascii_lowercase) + [str(x) for x in range(0, 10)] - - def read_fasta_sequence(fasta_path): - with open(fasta_path, "r") as f: - lines = [line.strip() for line in f.readlines()] - - if not lines: - return "" - - sequence_lines = [line for line in lines if line and not line.startswith(">")] - return "".join(sequence_lines) - - for batch_itr in range(len(fasta_files_batch)): - a3m_files = a3m_files_batch[batch_itr] - seq_types = seq_types_batch[batch_itr] - fasta_files = fasta_files_batch[batch_itr] - - for seq_type in seq_types: - if seq_type not in {"protein", "dna", "rna", "smiles", "ccd"}: - print(f'seqeuence type should be ["protein", "dna", "rna", "smiles", "ccd"], found {seq_type}!') - exit(1) - - output_file = ids_batch[batch_itr] + "_boltz_interaction_input.yaml" - counter = 0 - yaml_lines = ["version: 1", "sequences:"] - ligand_chain_ids = [] - - for seq_itr in range(len(seq_types)): - fasta_path = fasta_files[seq_itr] - a3m_path = a3m_files[seq_itr] - seq_type = seq_types[seq_itr] - - sequence = read_fasta_sequence(fasta_path) - if not sequence: - continue - - chain_id = all_combinations[counter] - counter += 1 - - if seq_type in {"smiles", "ccd"}: - yaml_lines.append(" - ligand:") - yaml_lines.append(f" id: {chain_id}") - yaml_lines.append(f" {seq_type}: {json.dumps(sequence)}") - ligand_chain_ids.append(chain_id) - else: - yaml_lines.append(f" - {seq_type}:") - yaml_lines.append(f" id: {chain_id}") - yaml_lines.append(f" sequence: {json.dumps(sequence)}") - if seq_type == "protein" and a3m_path: - yaml_lines.append(f" msa: {json.dumps(os.path.basename(a3m_path))}") - - if len(ligand_chain_ids) == 1: - yaml_lines.append("properties:") - yaml_lines.append(" - affinity:") - yaml_lines.append(f" binder: {ligand_chain_ids[0]}") - - with open(output_file, "w") as outfile: - outfile.write("\\n".join(yaml_lines) + "\\n") - - with open("versions.yml", "w") as version_file: - version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) - """ - - stub: - """ - #!/usr/bin/env python3 - from pathlib import Path - import sys - - ids_batch = ${ids.collect { "\"${it}\"" }.toString()} - for batch_itr in range(len(ids_batch)): - Path(ids_batch[batch_itr] + "_boltz_interaction_input.yaml").touch() - - with open("versions.yml", "w") as version_file: - version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) - """ -} diff --git a/nextflow.config b/nextflow.config index a24eb8e..e49f8fe 100644 --- a/nextflow.config +++ b/nextflow.config @@ -14,7 +14,6 @@ params { input = null mode = "all-all" interaction_threshold = 0 - mmseqs_batch_size = 10000 mmseqs_gpu = false use_gpu = true analysis_batch_size = 20 diff --git a/nextflow_schema.json b/nextflow_schema.json index 85c032f..c47699e 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -43,12 +43,6 @@ "fa_icon": "fas fa-cogs", "errorMessage": "Tools must be a comma-separated list containing any combination of 'alphafold3', 'colabfold', or 'boltz' with no spaces." }, - "mmseqs_batch_size": { - "type": "integer", - "default": 10000, - "description": "Number of samples in each mmseq run (batching leads to higher performance time in total.)", - "fa_icon": "fas fa-microchip" - }, "analysis_batch_size": { "type": "integer", "default": 20, diff --git a/workflows/wisps.nf b/workflows/wisps.nf index c80bd7f..caa5240 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -18,7 +18,6 @@ // MODULE: Installed directly from nf-core/modules // include { MULTIQC } from '../modules/nf-core/multiqc/main' -include { PREPARE_INTERACTIONS } from '../modules/local/prepare_interactions' include { COLLECT_CONFIDENCE } from '../modules/local/collect_confidence' // // SUBWORKFLOW: Consisting entirely of nf-core/modules @@ -35,7 +34,6 @@ include { RUN_BOLTZ } from '../modules/local/run_boltz' include { RUN_ALPHAFOLD3 } from '../modules/local/run_alphafold3' include { COLABFOLD_BATCH } from '../modules/local/colabfold_batch' include { BOLTZ_FASTA } from '../modules/local/data_convertor/boltz_fasta' -include { SPLIT_MSA } from '../modules/local/msa_manager/split_msa' include { IPSAE } from '../modules/local/ipsae' include {CREATE_INTERACTIONS} from '../modules/local/data_convertor/create_interactions' include { MMSEQS_COLABFOLDSEARCH } from '../modules/local/mmseqs_colabfoldsearch' @@ -64,7 +62,6 @@ workflow WISPS { ch_mols ch_colabfold_db ch_uniref30 - mmseqs_batch_size ch_colabfold_params num_recycles ch_alphafold3_params @@ -172,8 +169,6 @@ workflow WISPS { }.unique() .set{ch_single_protein} - //ch_protein_pairs.view() - MMSEQS_COLABFOLDSEARCH ( CREATE_INTERACTIONS.out.interactions.map{[["id": "all_run"], it]}, ch_colabfold_db, @@ -197,123 +192,28 @@ workflow WISPS { .map{it[1]} .flatten() .map{[it.baseName, it]} - .cross( - ch_protein_pairs - .mix(ch_single_protein) - .map{[it[0].id, it[0]]} - ) - .map{[it[1][1], it[0][1]]} .set{ch_af3_json} - // Prepare interactions for boltz - ch_boltz_data = Channel.empty() - ch_split_msa_in = Channel.empty() - ch_boltz_interactions_in = Channel.empty() - + // Prepare interactions for boltz directly from MMSEQS outputs + ch_boltz_in = Channel.empty() if ("boltz" in tools.split(",")){ - ch_a3m - .join(ch_protein_pairs.map{it[0]}) - .set{ch_split_msa_in} - ch_boltz_interactions_in = ch_interaction_in - } - - split_batch_id = 0 - SPLIT_MSA( - ch_split_msa_in + MMSEQS_COLABFOLDSEARCH.out.yaml .map{it[1]} - .buffer( size: mmseqs_batch_size, remainder: true ) - .map{ split_batch_id += 1; [["id" : "batch-${split_batch_id}-${it.size()}"], it]} - ) - - ch_versions = ch_versions.mix(SPLIT_MSA.out.versions) - - // Adding non protein for boltz - ch_boltz_data = - ch_boltz_data - .mix(ch_boltz_interactions_in - .filter{it[1][0].type != "protein" && it[1][1].type != "protein"} - .map{[it, ["", ""]]} - ) - - // Adding single protein for boltz - ch_boltz_data = ch_boltz_data.mix( - ch_boltz_interactions_in - .filter{[it[1][0].type, it[1][1].type].count("protein") == 1} - .map{ - if (it[1][0].type == "protein"){ - [it[1][0], it] - }else if (it[1][1].type == "protein"){ - [it[1][1], it] - } - } - .combine(ch_a3m.filter{it[0].type == "protein"}) - .filter{it[0] == it[2]} - .map{ - if (it[1][1][0].type == "protein") - [it[1], [it[3], ""]] - else - [it[1], ["", it[3]]] - } - ) - - SPLIT_MSA.out.msa_csv - .map{it[1]} - .flatten() - .map{[["id": it.baseName.replaceFirst(/_\d+$/, '')], it]} - .groupTuple(sort: true) - .set{ch_split_msa_out} - - ch_boltz_data = ch_boltz_data - .mix(ch_boltz_interactions_in - .filter{it[1][0].type == "protein" && it[1][1].type == "protein"} - .map{[["id": it[0].id], it]} + .flatten() + .map{[it.baseName, it]} .join( - ch_split_msa_out - .map{ - if (it[1].size() == 1){ - it[1] = [it[1][0], it[1][0]] - } - it - } - + MMSEQS_COLABFOLDSEARCH.out.msa_csv + .map{it[1]} + .flatten() + .map{[it.baseName.replaceFirst(/_[A-Z]+$/, '').replace("_boltz_interaction_input", ""), it]} + .groupTuple(sort: true), + remainder: true ) - .map{[it[1], it[2]]} - ) - - batch_id = 0 - - PREPARE_INTERACTIONS( - ch_boltz_data - .map{it[0][0].id} - .buffer( size: analysis_batch_size, remainder: true ) - .map{ batch_id += 1; [["id" : "batch-${batch_id}-${it.size()}"], it]}, - ch_boltz_data - .map{it[0][2].collect{it.name}} - .buffer( size: analysis_batch_size, remainder: true ), - ch_boltz_data - .map{it[1].collect{it ? it.name: ""}} - .buffer( size: analysis_batch_size, remainder: true ), - ch_boltz_data - .map{[it[0][1][0].type, it[0][1][1].type]} - .buffer( size: analysis_batch_size, remainder: true ), - ch_boltz_data - .map{[it[0][2][0], it[0][2][1], it[1][0], it[1][1]]} - .buffer( size: analysis_batch_size, remainder: true ) - .map{it.flatten()findAll{it}.unique{it.toUriString()}} - - ) - - PREPARE_INTERACTIONS.out.yaml - .map{it[1]} - .flatten() - .map{[it.baseName.replace("_boltz_interaction_input", ""), it]} - .join( - ch_boltz_data - .map{[it[0][0].id, [it[1][0], it[1][1]]]} - ) - .buffer( size: analysis_batch_size, remainder: true ) - .set{ch_boltz_in} + .map{id, yaml, msa_csv -> [id, yaml, msa_csv ?: []]} + .buffer( size: analysis_batch_size, remainder: true ) + .set{ch_boltz_in} + } boltz_batch = 0 @@ -389,7 +289,8 @@ workflow WISPS { af3_batch = 0 ch_alphafold3_interaction_in = Channel.empty() if ("alphafold3" in tools.split(",")){ - ch_af3_json.join(ch_protein_pairs.map{it[0]}) + //ch_af3_json.join(ch_protein_pairs.map{it[0]}) + ch_af3_json .map{it[1]} .buffer( size: analysis_batch_size, remainder: true ) .map{ From 5419e40da5fc8dc434b054966a5a4e6d5a872999 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Sun, 12 Apr 2026 11:53:50 +1000 Subject: [PATCH 41/70] support ipsae for higher order complexes --- workflows/wisps.nf | 179 ++++++++++++++++++++++++++------------------- 1 file changed, 105 insertions(+), 74 deletions(-) diff --git a/workflows/wisps.nf b/workflows/wisps.nf index caa5240..2cb6e18 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -127,26 +127,28 @@ workflow WISPS { interaction_threshold ) - ch_samplesheet - .collect(flat: false) - .flatMap { data_ls -> - def list = data_ls.toList() + CREATE_INTERACTIONS.out.interactions + .flatMap { interactions_fasta -> def out = [] - for (int i = 0; i < list.size(); i++) { - for (int j = i; j < list.size(); j++) { - def key = [list[i][0]['group'].toString(), list[j][0]['group'].toString()].sort().join('-') - if ((interaction_mode[0] != "all-all" && interaction_mode.contains(key)) || (interaction_mode[0] == "all-all" && (interaction_threshold == 0 || Math.abs(i-j) <= interaction_threshold))) - { - out << [ - [ - "id": list[i][0]["id"] + "-" + list[j][0]["id"], - "group": key - ], - [list[i][0], list[j][0]], - [list[i][1], list[j][1]], - ] - } + def lines = interactions_fasta.readLines().findAll { it?.trim() } + if (lines.size() % 2 != 0) { + throw new IllegalStateException("Invalid interactions FASTA layout in ${interactions_fasta}: expected an even number of non-empty lines.") + } + + lines.collate(2).each { chunk -> + def header = chunk[0] + if (!header.startsWith(">")) { + throw new IllegalStateException("Invalid FASTA header in ${interactions_fasta}: '${header}'") } + + def interaction_id = header.substring(1).trim() + def sequence_line = chunk[1].trim() + //def has_protein = sequence_line.split(":").any { !it.contains("|") } + def has_protein = sequence_line.split(":").count { !it.contains("|") } > 1 + out << [ + ["id": interaction_id], + has_protein + ] } out } @@ -155,20 +157,6 @@ workflow WISPS { ch_interaction_in.count().subscribe{print("total final: ${it}")} - ch_interaction_in - .filter{it[1][0].type == "protein" && it[1][1].type == "protein"} - .set {ch_protein_pairs} - - ch_interaction_in - .map{ - if (it[1][0].type != "protein" && it[1][1].type == "protein"){ - [it[1][1], it[2][1]] - }else if (it[1][1].type != "protein" && it[1][0].type == "protein"){ - [it[1][0], it[2][0]] - } - }.unique() - .set{ch_single_protein} - MMSEQS_COLABFOLDSEARCH ( CREATE_INTERACTIONS.out.interactions.map{[["id": "all_run"], it]}, ch_colabfold_db, @@ -180,12 +168,6 @@ workflow WISPS { .map{it[1]} .flatten() .map{[it.baseName, it]} - .cross( - ch_protein_pairs - .mix(ch_single_protein) - .map{[it[0].id, it[0]]} - ) - .map{[it[1][1], it[0][1]]} .set{ch_a3m} MMSEQS_COLABFOLDSEARCH.out.json @@ -229,32 +211,33 @@ workflow WISPS { RUN_BOLTZ.out.confidence .map{it[1]} .flatten() - .map{[["id": it.baseName.split("_boltz_")[0].split("confidence_")[1], "model": "boltz"], it]} + .map{[["id": it.baseName.split("_model_0")[0].split("confidence_")[1], "model": "boltz"], it]} .set{ch_boltz_confidence} RUN_BOLTZ.out.affinity .map{it[1]} .flatten() - .map{[["id": it.baseName.split("_boltz_")[0].split("affinity_")[1], "model": "boltz"], it]} + .map{[["id": it.baseName.split("_model_0")[0].split("affinity_")[1], "model": "boltz"], it]} .set{ch_boltz_affinity} RUN_BOLTZ.out.pae .map{it[1]} .flatten() - .map{[["id": it.baseName.split("_boltz_")[0].split("pae_")[1], "model": "boltz"], it]} + .map{[["id": it.baseName.split("_model_0")[0].split("pae_")[1], "model": "boltz"], it]} .set{ch_boltz_pae} RUN_BOLTZ.out.cif .map{it[1]} .flatten() - .map{[["id": it.baseName.split("_boltz_")[0], "model": "boltz"], it]} + .map{[["id": it.baseName.split("_model_0")[0], "model": "boltz"], it]} .set{ch_boltz_cif} //prepare interactions for colabfold ch_colabfold_interaction_in = Channel.empty() if ("colabfold" in tools.split(",")){ colabfold_batch = 0 - ch_a3m.join(ch_protein_pairs.map{it[0]}) + //ch_a3m.join(ch_protein_pairs.map{it[0]}) + ch_a3m .map{it[1]} .buffer( size: colabfold_batch_size, remainder: true ) .map{ @@ -349,8 +332,8 @@ workflow WISPS { .join(ch_colabfold_pdb) .map{[["id": it[0].id], it]} .join(ch_interaction_in - .filter{it[1][0].type == "protein" || it[1][1].type == "protein"} - .map{["id": it[0].id]} + .filter{it[1]} + .map{it[0]} ) .map{[it[1][1], it[1][2], []]} .buffer( size: analysis_batch_size, remainder: true ) @@ -364,8 +347,8 @@ workflow WISPS { .join(ch_boltz_confidence) .map{[["id": it[0].id], [it[0], it[1], it[2]], it[3]]} .join(ch_interaction_in - .filter{it[1][0].type == "protein" || it[1][1].type == "protein"} - .map{["id": it[0].id]} + .filter{it[1]} + .map{it[0]} ) .map{[it[1][1], it[1][2], it[2]]} .buffer( size: analysis_batch_size, remainder: true ) @@ -378,8 +361,8 @@ workflow WISPS { ch_alphafold3_confidence.join(ch_alphafold3_cif) .map{[["id": it[0].id], it]} .join(ch_interaction_in - .filter{it[1][0].type == "protein" || it[1][1].type == "protein"} - .map{["id": it[0].id]} + .filter{it[1]} + .map{it[0]} ) .map{[it[1][1], it[1][2], []]} .buffer( size: analysis_batch_size, remainder: true ) @@ -399,23 +382,32 @@ workflow WISPS { ch_versions = ch_versions.mix(IPSAE.out.versions) + def parseIpsaeMaxRows = { file, model, sampleId -> + def lines = file.text + .split("\n") + .findAll { line -> + def cols = line.split() + cols.size() > 5 && cols[4].trim() == "max" + } + def entries = lines.collect { line -> + def cols = line.split() + def pairId = "${cols[0].trim()}_${cols[1].trim()}" + [pairId, new BigDecimal(cols[5].trim())] + } + [sampleId, entries] + } + IPSAE.out.txt .transpose() .branch { boltz: it[0].model == "boltz" - lines = it[1].text.split("\n").findAll{line -> line.split().size() > 4 && line.split()[4].trim() == "max" } - max_vals = lines.collect{new BigDecimal(it.split()[5].trim())} - return [it[1].baseName.split("_boltz_")[0], max_vals ? (max_vals.sum() / max_vals.size()) : null] + return parseIpsaeMaxRows(it[1], "boltz", it[1].baseName.split("_model_0")[0]) alphafold3: it[0].model == "alphafold3" - lines = it[1].text.split("\n").findAll{line -> line.split().size() > 4 && line.split()[4].trim() == "max" } - max_vals = lines.collect{new BigDecimal(it.split()[5].trim())} - return [it[1].baseName.split("_model_")[0], max_vals ? (max_vals.sum() / max_vals.size()) : null] + return parseIpsaeMaxRows(it[1], "alphafold3", it[1].baseName.split("_model_")[0]) colabfold: it[0].model == "colabfold" - lines = it[1].text.split("\n").findAll{line -> line.split().size() > 4 && line.split()[4].trim() == "max" } - max_vals = lines.collect{new BigDecimal(it.split()[5].trim())} - return [it[1].baseName.split("_unrelaxed_")[0], max_vals ? (max_vals.sum() / max_vals.size()) : null] + return parseIpsaeMaxRows(it[1], "colabfold", it[1].baseName.split("_unrelaxed_")[0]) } .set{ch_ipsae_out} @@ -424,42 +416,81 @@ workflow WISPS { .collect { it.trim() } .findAll { it in ['boltz','colabfold','alphafold3'] } - def header = "Sample," + active_modes.collect { "${it}_ipsae" }.join(",") + "\n" - - // 1) Long format: [sample_id, model, score] + // 1) Long format: [sample_id, pair_id, model, score] ch_long = Channel.empty() if ('boltz' in active_modes) - ch_long = ch_long.mix(ch_ipsae_out.boltz.map { id, score -> [id, 'boltz', score] }) + ch_long = ch_long.mix(ch_ipsae_out.boltz.flatMap { id, entries -> entries.collect { e -> [id, e[0], 'boltz', e[1]] } }) if ('colabfold' in active_modes) - ch_long = ch_long.mix(ch_ipsae_out.colabfold.map { id, score -> [id, 'colabfold', score] }) + ch_long = ch_long.mix(ch_ipsae_out.colabfold.flatMap { id, entries -> entries.collect { e -> [id, e[0], 'colabfold', e[1]] } }) if ('alphafold3' in active_modes) - ch_long = ch_long.mix(ch_ipsae_out.alphafold3.map { id, score -> [id, 'alphafold3', score] }) + ch_long = ch_long.mix(ch_ipsae_out.alphafold3.flatMap { id, entries -> entries.collect { e -> [id, e[0], 'alphafold3', e[1]] } }) - // 2) Pivot per sample: [sample_id, modelScoreMap] - ch_wide = ch_long - .map { id, model, score -> [id, [model, score]] } + // 2) Pivot per pair: [pair_id, sampleModelScoreMap] + ch_pair_wide = ch_long + .map { sampleId, pairId, model, score -> [pairId, [sampleId, model, score]] } .groupTuple() - .map { id, pairs -> + .map { pairId, rows -> + def bySample = [:].withDefault { [:] } + rows.each { r -> + bySample[r[0]][r[1]] = r[2] + } + [pairId, bySample] + } + + // 3) Create one CSV per pair with model-only headers + ch_interaction_in.map { it[0].id }.unique().toSortedList().map { [sample_ids: it] } + .combine(ch_pair_wide.collect(flat: false).map { [pairs: it] }) + .flatMap { left, right -> + def ids = left.sample_ids + def pairs = right.pairs + pairs.collect { pairEntry -> + def pairId = pairEntry[0] + def bySample = pairEntry[1] + def header = "Sample," + active_modes.join(",") + "\n" + def body = ids.collect { id -> + def mm = bySample[id] ?: [:] + def vals = active_modes.collect { mode -> mm[mode] != null ? mm[mode] : "" } + "${id},${vals.join(',')}\n" + }.join("") + def safePairId = pairId.replaceAll(/[^A-Za-z0-9._-]+/, "_") + ["ipsae_scores_${safePairId}.csv", header + body] + } + } + .collectFile( + storeDir: "${outdir}/ipsae", + newLine: false + ) { item -> [item[0], item[1]] } + .set { ch_ipsae_scores_by_pair } + + // 4) Additional summary file: max score per sample/model across all pair ids + ch_model_wide = ch_long + .map { sampleId, pairId, model, score -> [[sampleId, model], score] } + .groupTuple() + .map { key, scores -> [key[0], [key[1], scores.max()]] } + .groupTuple() + .map { sampleId, pairs -> def m = pairs.collectEntries { p -> [(p[0]): p[1]] } - [id, m] + [sampleId, m] } - // 3) Left-join against all expected samples and render rows by active_modes order + def summary_header = "Sample," + active_modes.join(",") + "\n" ch_interaction_in.map { it[0].id }.unique().map { [it, true] } - .join(ch_wide, remainder: true) + .join(ch_model_wide, remainder: true) .map { id, _, m -> def mm = m ?: [:] def vals = active_modes.collect { mode -> mm[mode] != null ? mm[mode] : "" } "${id},${vals.join(',')}\n" } .toSortedList() - .flatMap{ it } + .flatMap { it } .collectFile( storeDir: "${outdir}/ipsae", name: 'ipsae_scores.csv', - seed: header + seed: summary_header ) - .set { ch_ipsae_scores } + .set { ch_ipsae_scores_max } + + ch_ipsae_scores = ch_ipsae_scores_by_pair.mix(ch_ipsae_scores_max) ch_boltz_confidence From 397b79a77e953dc0bd5c4c839b79d650840df6bc Mon Sep 17 00:00:00 2001 From: tlitfin Date: Sun, 12 Apr 2026 14:54:13 +1000 Subject: [PATCH 42/70] colabfold chainwise scores --- conf/modules.config | 4 ++++ modules/local/colabfold_batch/main.nf | 3 ++- 2 files changed, 6 insertions(+), 1 deletion(-) diff --git a/conf/modules.config b/conf/modules.config index a050bd2..47061dc 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -68,6 +68,10 @@ process { ext.args = "--write_full_pae --output_format mmcif" } + withName: 'COLABFOLD_BATCH' { + ext.args = "--calc-extra-ptm" + } + withName: 'IPSAE' { ext.args = "${params.ipsae_pae_cutoff} ${params.ipsae_dist_cutoff}" } diff --git a/modules/local/colabfold_batch/main.nf b/modules/local/colabfold_batch/main.nf index dc922cb..9284f42 100644 --- a/modules/local/colabfold_batch/main.nf +++ b/modules/local/colabfold_batch/main.nf @@ -3,7 +3,8 @@ process COLABFOLD_BATCH { label 'process_medium' label 'process_gpu' - container "nf-core/proteinfold_colabfold:dev" + //container "nf-core/proteinfold_colabfold:dev" + container "ghcr.io/tlitfin/wisps-colabfold-batch:1.1" input: tuple val(meta), path("alignment/*") From a574cd7f254c0ae895b929605aea930d524635b8 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Sun, 12 Apr 2026 20:49:36 +1000 Subject: [PATCH 43/70] track chainwise scores by group --- bin/collect_confidence.py | 147 ++++++++++++++++-- modules/local/collect_confidence.nf | 6 + .../data_convertor/create_interactions.nf | 37 ++++- workflows/wisps.nf | 68 ++++++-- 4 files changed, 233 insertions(+), 25 deletions(-) diff --git a/bin/collect_confidence.py b/bin/collect_confidence.py index b2457fd..4494314 100755 --- a/bin/collect_confidence.py +++ b/bin/collect_confidence.py @@ -1,6 +1,5 @@ #!/usr/bin/env python3 -import os, sys import json import csv import statistics @@ -72,10 +71,114 @@ def parse_boltz_json_file(json_file): return "affinity", m.group(1) return None, None -def extract_boltz_results(json_files, output_csv): +def build_sample_meta_by_id(sample_metadata): + sample_meta_by_id = {} + if not sample_metadata: + return sample_meta_by_id + + for item in sample_metadata: + if isinstance(item, dict) and "id" in item: + sample_id = str(item["id"]) + sample_meta_by_id[sample_id] = { + "int_chain_map": item.get("int_chain_map", ""), + "str_chain_map": item.get("str_chain_map", ""), + } + return sample_meta_by_id + +def add_mapping_fields(row, sample_id, sample_meta_by_id): + meta = sample_meta_by_id.get(sample_id, {}) + row["int_chain_map"] = meta.get("int_chain_map", "") + row["str_chain_map"] = meta.get("str_chain_map", "") + +def parse_int_chain_map(int_chain_map): + if not int_chain_map or ":" not in int_chain_map: + return [], [] + + left, right = int_chain_map.split(":", 1) + left_ids = [int(x) for x in left.split(",") if x.strip() != ""] + right_ids = [int(x) for x in right.split(",") if x.strip() != ""] + return left_ids, right_ids + +def parse_str_chain_map(str_chain_map): + if not str_chain_map or ":" not in str_chain_map: + return [], [] + + left, right = str_chain_map.split(":", 1) + left_ids = [x.strip() for x in left.split(",") if x.strip() != ""] + right_ids = [x.strip() for x in right.split(",") if x.strip() != ""] + return left_ids, right_ids + +def compute_max_cross_group_metric(int_chain_map, value_getter): + left_ids, right_ids = parse_int_chain_map(int_chain_map) + if not left_ids or not right_ids: + return None + + values = [] + for li in left_ids: + for rj in right_ids: + v_lr = value_getter(li, rj) + v_rl = value_getter(rj, li) + + if isinstance(v_lr, (int, float)): + values.append(v_lr) + if isinstance(v_rl, (int, float)): + values.append(v_rl) + + return max(values) if values else None + +def compute_max_cross_group_metric_from_groups(left_ids, right_ids, value_getter): + if not left_ids or not right_ids: + return None + + values = [] + for left_id in left_ids: + for right_id in right_ids: + v_lr = value_getter(left_id, right_id) + v_rl = value_getter(right_id, left_id) + + if isinstance(v_lr, (int, float)): + values.append(v_lr) + if isinstance(v_rl, (int, float)): + values.append(v_rl) + + return max(values) if values else None + +def compute_max_cross_group_pair_chains_iptm(pair_chains_iptm, int_chain_map): + if not isinstance(pair_chains_iptm, dict): + return None + + def get_dict_value(i, j): + return pair_chains_iptm.get(str(i), {}).get(str(j)) + + return compute_max_cross_group_metric(int_chain_map, get_dict_value) + +def compute_max_cross_group_chain_pair_iptm(chain_pair_iptm, int_chain_map): + if not isinstance(chain_pair_iptm, list): + return None + + def get_list_value(i, j): + if 0 <= i < len(chain_pair_iptm) and isinstance(chain_pair_iptm[i], list): + if 0 <= j < len(chain_pair_iptm[i]): + return chain_pair_iptm[i][j] + return None + + return compute_max_cross_group_metric(int_chain_map, get_list_value) + +def compute_max_cross_group_pairwise_iptm(pairwise_iptm, str_chain_map): + if not isinstance(pairwise_iptm, dict): + return None + + left_ids, right_ids = parse_str_chain_map(str_chain_map) + + def get_pairwise_value(i, j): + return pairwise_iptm.get(f"{i}-{j}") + + return compute_max_cross_group_metric_from_groups(left_ids, right_ids, get_pairwise_value) + +def extract_boltz_results(json_files, output_csv, sample_meta_by_id): rows_by_id = {} all_keys = ["confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde", "chains_ptm"] - writing_keys = ["id", "confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde"] + writing_keys = ["id", "iptm", "ptm", "int_chain_map", "str_chain_map", "max_cross_group_pair_chains_iptm", "confidence_score", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde"] writing_keys_extra = set() for file in json_files: @@ -91,6 +194,11 @@ def extract_boltz_results(json_files, output_csv): flat_data = rows_by_id[sample_id] if record_type == "confidence": + int_chain_map = sample_meta_by_id.get(sample_id, {}).get("int_chain_map", "") + flat_data["max_cross_group_pair_chains_iptm"] = compute_max_cross_group_pair_chains_iptm( + data.get("pair_chains_iptm"), + int_chain_map + ) for key, value in data.items(): if key not in all_keys: continue @@ -125,15 +233,16 @@ def extract_boltz_results(json_files, output_csv): writer.writeheader() for sample_id in sorted(rows_by_id.keys()): row = rows_by_id[sample_id] + add_mapping_fields(row, sample_id, sample_meta_by_id) writer.writerow({key: row.get(key, "") for key in final_writing_vals}) -def extract_colabfold_results(json_files, samples, output_csv): +def extract_colabfold_results(json_files, samples, output_csv, sample_meta_by_id): def parse_colabfold_metrics(json_file): with open(json_file, "r") as f: data = json.load(f) result = {} - for key in ["iptm", "max_pae", "pae", "ptm", "plddt"]: + for key in ["iptm", "max_pae", "pae", "ptm", "plddt", "pairwise_iptm"]: if key not in data: result[key] = None continue @@ -148,12 +257,17 @@ def parse_colabfold_metrics(json_file): return result rows = [] - all_keys = ["id", "plddt", "ptm", "iptm", "max_pae"] + all_keys = ["id", "ptm", "iptm", "int_chain_map", "str_chain_map", "max_cross_group_pairwise_iptm", "plddt", "max_pae"] writing_keys = all_keys cntr = 0 for file in json_files: flat_data = parse_colabfold_metrics(file) flat_data["id"] = samples[cntr] + add_mapping_fields(flat_data, flat_data["id"], sample_meta_by_id) + flat_data["max_cross_group_pairwise_iptm"] = compute_max_cross_group_pairwise_iptm( + flat_data.get("pairwise_iptm"), + flat_data.get("str_chain_map", "") + ) cntr += 1 rows.append(flat_data) @@ -164,10 +278,10 @@ def parse_colabfold_metrics(json_file): for row in rows: writer.writerow({key: row.get(key, "") for key in writing_keys}) -def extract_alphafold3_results(json_files, samples, output_csv): +def extract_alphafold3_results(json_files, samples, output_csv, sample_meta_by_id): rows = [] all_keys = ["chain_iptm","chain_pair_iptm", "chain_pair_pae_min", "ptm", "iptm", "chain_ptm", "fraction_disordered", "has_clash", "ranking_score"] - writing_keys = ["id", "ptm", "iptm", "fraction_disordered", "has_clash", "ranking_score"] + writing_keys = ["id", "ptm", "iptm", "int_chain_map", "str_chain_map", "max_cross_group_chain_pair_iptm", "fraction_disordered", "has_clash", "ranking_score"] writing_keys_extra = set() # First pass: read and collect keys cntr = 0 @@ -175,6 +289,11 @@ def extract_alphafold3_results(json_files, samples, output_csv): with open(file) as f: data = json.load(f) flat_data = {"id": samples[cntr]} + add_mapping_fields(flat_data, flat_data["id"], sample_meta_by_id) + flat_data["max_cross_group_chain_pair_iptm"] = compute_max_cross_group_chain_pair_iptm( + data.get("chain_pair_iptm"), + flat_data.get("int_chain_map", "") + ) cntr += 1 for key, value in data.items(): if key not in all_keys: @@ -203,18 +322,24 @@ def main(): parser.add_argument("-i", "--input", help="Path to input directory containing all json files") parser.add_argument("-o", "--output", default="output_msa", help="output CSV file") parser.add_argument("--model", default="boltz", help="model generating the input files can be one of [boltz, alphafold3, and colabfold]") + parser.add_argument("--sample-metadata", default=None, help="JSON file with list of sample metadata maps including id/int_chain_map/str_chain_map") args = parser.parse_args() json_files = [str(f) for f in Path(args.input).glob("*.json") if f.is_file()] + sample_meta_by_id = {} + if args.sample_metadata: + with open(args.sample_metadata, "r") as f: + sample_metadata = json.load(f) + sample_meta_by_id = build_sample_meta_by_id(sample_metadata) if args.model.lower() == "boltz": - extract_boltz_results(json_files, args.output) + extract_boltz_results(json_files, args.output, sample_meta_by_id) elif args.model.lower() == "colabfold": samples = [Path(p).name.split("_scores_")[0] for p in json_files] - extract_colabfold_results(json_files, samples, args.output) + extract_colabfold_results(json_files, samples, args.output, sample_meta_by_id) elif args.model.lower() == "alphafold3": samples = [Path(p).name.split("_summary_confidences.json")[0] for p in json_files] - extract_alphafold3_results(json_files, samples, args.output) + extract_alphafold3_results(json_files, samples, args.output, sample_meta_by_id) print(f"CSV file created at: {args.output}") diff --git a/modules/local/collect_confidence.nf b/modules/local/collect_confidence.nf index 8a0fade..e153032 100644 --- a/modules/local/collect_confidence.nf +++ b/modules/local/collect_confidence.nf @@ -19,11 +19,17 @@ process COLLECT_CONFIDENCE { script: def args = task.ext.args ?: '' + def samples_json = groovy.json.JsonOutput.toJson(samples) """ + cat << 'EOF' > sample_metadata.json + ${samples_json} + EOF + collect_confidence.py \\ --input input_json_files \\ --model "${meta.model}"\\ + --sample-metadata sample_metadata.json \\ --output "${meta.model}_confidence_scores_full.csv" cat <<-END_VERSIONS > versions.yml diff --git a/modules/local/data_convertor/create_interactions.nf b/modules/local/data_convertor/create_interactions.nf index f5983dd..9b0948a 100644 --- a/modules/local/data_convertor/create_interactions.nf +++ b/modules/local/data_convertor/create_interactions.nf @@ -17,6 +17,7 @@ process CREATE_INTERACTIONS { output: path ("interactions.fasta"), emit: interactions + path ("interaction_mapping.tsv"), emit: interaction_mapping path "versions.yml" , emit: versions when: @@ -59,7 +60,22 @@ process CREATE_INTERACTIONS { return f"{parsed_type}|{parsed_seq}" - with open("interactions.fasta", "w") as target_interactions: + def chain_count(entity_type, entity_seq): + if entity_type.lower() == "protein": + return len([chain for chain in entity_seq.split(":") if chain]) + return 1 + + def int_id_to_str_id(i): + if i < 0: + raise ValueError(f"int_id_to_str_id: Only positive integers allowed, got {i}") + output = [] + while i >= 0: + output.append(chr(i % 26 + ord("A"))) + i = i // 26 - 1 + return "".join(output) + + with open("interactions.fasta", "w") as target_interactions, open("interaction_mapping.tsv", "w") as mapping_file: + mapping_file.write("interaction_id\\tint_chain_map\\tstr_chain_map\\n") for i in range(n): for j in range(i, n): if interaction_mode[0] != "all-all" and groups[i] not in group_ls: @@ -67,15 +83,27 @@ process CREATE_INTERACTIONS { if (interaction_mode[0] != "all-all" and "-".join(sorted([groups[i], groups[j]])) in interaction_mode) or (interaction_mode[0] == "all-all" and (${interaction_threshold} == 0 or abs(i-j) <= ${interaction_threshold})): interactions_cntr += 1 + left_chain_count = chain_count(types[i], seqs[i]) + right_chain_count = chain_count(types[j], seqs[j]) + left_chain_indices = ",".join(str(idx) for idx in range(0, left_chain_count)) + right_chain_indices = ",".join(str(idx) for idx in range(left_chain_count, left_chain_count + right_chain_count)) + left_chain_str_ids = ",".join(int_id_to_str_id(idx) for idx in range(0, left_chain_count)) + right_chain_str_ids = ",".join(int_id_to_str_id(idx) for idx in range(left_chain_count, left_chain_count + right_chain_count)) + interaction_id = f"{ids[i]}-{ids[j]}" + interaction_header = f">{interaction_id}\\n" + mapping_file.write( + f"{interaction_id}\\t{left_chain_indices}:{right_chain_indices}\\t{left_chain_str_ids}:{right_chain_str_ids}\\n" + ) + if types[i] == "protein" and types[j] == "protein": - target_interactions.write(f">{ids[i]}-{ids[j]}\\n{seqs[i]}:{seqs[j]}\\n") + target_interactions.write(f"{interaction_header}{seqs[i]}:{seqs[j]}\\n") elif types[i] == "protein": target_interactions.write( - f">{ids[i]}-{ids[j]}\\n{seqs[i]}:{format_non_protein_entry(types[j], seqs[j])}\\n" + f"{interaction_header}{seqs[i]}:{format_non_protein_entry(types[j], seqs[j])}\\n" ) elif types[j] == "protein": target_interactions.write( - f">{ids[i]}-{ids[j]}\\n{format_non_protein_entry(types[i], seqs[i])}:{seqs[j]}\\n" + f"{interaction_header}{format_non_protein_entry(types[i], seqs[i])}:{seqs[j]}\\n" ) if interactions_cntr == 0: print("No Interactions found!!") @@ -88,6 +116,7 @@ process CREATE_INTERACTIONS { stub: """ touch interactions.fasta + touch interaction_mapping.tsv cat <<-END_VERSIONS > versions.yml "${task.process}": diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 2cb6e18..0f8c0aa 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -127,7 +127,28 @@ workflow WISPS { interaction_threshold ) - CREATE_INTERACTIONS.out.interactions + ch_interaction_info = CREATE_INTERACTIONS.out.interaction_mapping + .flatMap { mapping_tsv -> + def out = [] + def lines = mapping_tsv.readLines().findAll { it?.trim() } + if (lines.isEmpty()) { + throw new IllegalStateException("Invalid interaction mapping file ${mapping_tsv}: file is empty.") + } + + lines.drop(1).each { line -> + def cols = line.split("\t", -1) + if (cols.size() != 3) { + throw new IllegalStateException("Invalid interaction mapping row in ${mapping_tsv}: '${line}'") + } + def interaction_id = cols[0].trim() + def int_chain_map = cols[1].trim() + def str_chain_map = cols[2].trim() + out << [interaction_id, int_chain_map, str_chain_map] + } + out + } + + ch_interaction_raw = CREATE_INTERACTIONS.out.interactions .flatMap { interactions_fasta -> def out = [] def lines = interactions_fasta.readLines().findAll { it?.trim() } @@ -145,13 +166,22 @@ workflow WISPS { def sequence_line = chunk[1].trim() //def has_protein = sequence_line.split(":").any { !it.contains("|") } def has_protein = sequence_line.split(":").count { !it.contains("|") } > 1 - out << [ - ["id": interaction_id], - has_protein - ] + out << [interaction_id, has_protein] } out } + ch_interaction_raw + .join(ch_interaction_info) + .map { interaction_id, has_protein, int_chain_map, str_chain_map -> + [ + [ + "id": interaction_id, + "int_chain_map": int_chain_map, + "str_chain_map": str_chain_map + ], + has_protein + ] + } .set{ch_interaction_in} @@ -492,23 +522,41 @@ workflow WISPS { ch_ipsae_scores = ch_ipsae_scores_by_pair.mix(ch_ipsae_scores_max) + ch_interaction_meta_by_id = ch_interaction_in + .map { [it[0].id, it[0]] } + + ch_boltz_confidence_with_meta = ch_boltz_confidence + .map { [it[0].id, it[1]] } + .join(ch_interaction_meta_by_id) + .map { id, json_file, interaction_meta -> [interaction_meta, json_file] } + + ch_boltz_affinity_with_meta = ch_boltz_affinity + .map { [it[0].id, it[1]] } + .join(ch_interaction_meta_by_id) + .map { id, json_file, interaction_meta -> [interaction_meta, json_file] } - ch_boltz_confidence - .mix(ch_boltz_affinity) + ch_boltz_confidence_with_meta + .mix(ch_boltz_affinity_with_meta) .collect(flat: false, sort: true).multiMap{json_list -> - ids: json_list.collect{it[0].id}.unique() + ids: json_list.collect{it[0]}.unique{it.id} json: json_list.collect{it[1]} }.set{ch_boltz_confidence_scores} ch_alphafold3_summary_confidences + .map { [it[0].id, it[1]] } + .join(ch_interaction_meta_by_id) + .map { id, json_file, interaction_meta -> [interaction_meta, json_file] } .collect(flat: false, sort: true).multiMap{json_list -> - ids: json_list.collect{it[0].id} + ids: json_list.collect{it[0]}.unique{it.id} json: json_list.collect{it[1]} }.set{ch_alphafold3_confidence_scores} ch_colabfold_scores + .map { [it[0].id, it[1]] } + .join(ch_interaction_meta_by_id) + .map { id, json_file, interaction_meta -> [interaction_meta, json_file] } .collect(flat: false, sort: true).multiMap{json_list -> - ids: json_list.collect{it[0].id} + ids: json_list.collect{it[0]}.unique{it.id} json: json_list.collect{it[1]} }.set{ch_colabfold_confidence_scores} From 4b4d7ee78e80bf4d9e2d68bd55f890f9eb8b125f Mon Sep 17 00:00:00 2001 From: tlitfin Date: Sun, 12 Apr 2026 22:04:58 +1000 Subject: [PATCH 44/70] add manual mode --- workflows/wisps.nf | 82 ++++++++++++++++++++++++++++------------------ 1 file changed, 50 insertions(+), 32 deletions(-) diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 0f8c0aa..d4fa5cb 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -85,7 +85,7 @@ workflow WISPS { } if ("all-all" in interaction_mode) { interaction_mode = ["all-all"] - }else{ + } else if (!("manual" in interaction_mode)) { required = interaction_mode.collect{it.split("-")}.flatten().unique() ch_samplesheet .map{it[0].group} @@ -106,7 +106,7 @@ workflow WISPS { .multiMap{ if (it[1].extension == "fasta" || it[1].extension == "fa") {seq = getFastaSequences(it[1].text).sequence.join(":")} - else if (it[1].extension == "yaml" || it[1].extension == ".yml") + else if (it[1].extension == "yaml" || it[1].extension == "yml") {seq = getYamlSequences(it[1].text).sequence.join(":")} else if (it[1].extension == "json") {seq = ""} @@ -118,38 +118,52 @@ workflow WISPS { }.set{ch_raw_sample_sheet} - CREATE_INTERACTIONS( - ch_raw_sample_sheet.ids.collect(), - ch_raw_sample_sheet.types.collect(), - ch_raw_sample_sheet.groups.collect(), - ch_raw_sample_sheet.seqs.collect(), - interaction_mode, - interaction_threshold - ) + ch_interaction_raw = Channel.empty() + ch_interaction_info = Channel.empty() - ch_interaction_info = CREATE_INTERACTIONS.out.interaction_mapping - .flatMap { mapping_tsv -> - def out = [] - def lines = mapping_tsv.readLines().findAll { it?.trim() } - if (lines.isEmpty()) { - throw new IllegalStateException("Invalid interaction mapping file ${mapping_tsv}: file is empty.") - } + if (!("manual" in interaction_mode)) { + CREATE_INTERACTIONS( + ch_raw_sample_sheet.ids.collect(), + ch_raw_sample_sheet.types.collect(), + ch_raw_sample_sheet.groups.collect(), + ch_raw_sample_sheet.seqs.collect(), + interaction_mode, + interaction_threshold + ) - lines.drop(1).each { line -> - def cols = line.split("\t", -1) - if (cols.size() != 3) { - throw new IllegalStateException("Invalid interaction mapping row in ${mapping_tsv}: '${line}'") + ch_interaction_info = CREATE_INTERACTIONS.out.interaction_mapping + .flatMap { mapping_tsv -> + def out = [] + def lines = mapping_tsv.readLines().findAll { it?.trim() } + if (lines.isEmpty()) { + throw new IllegalStateException("Invalid interaction mapping file ${mapping_tsv}: file is empty.") + } + + lines.drop(1).each { line -> + def cols = line.split("\t", -1) + if (cols.size() != 3) { + throw new IllegalStateException("Invalid interaction mapping row in ${mapping_tsv}: '${line}'") + } + def interaction_id = cols[0].trim() + def int_chain_map = cols[1].trim() + def str_chain_map = cols[2].trim() + out << [interaction_id, int_chain_map, str_chain_map] } - def interaction_id = cols[0].trim() - def int_chain_map = cols[1].trim() - def str_chain_map = cols[2].trim() - out << [interaction_id, int_chain_map, str_chain_map] + out } - out + + ch_interaction_raw = CREATE_INTERACTIONS.out.interactions + } else { + ch_interaction_raw = ch_samplesheet + .map { it[1] } + .filter { it.extension == "fasta" || it.extension == "fa" } + .ifEmpty { error("Manual mode requires at least one FASTA file in the samplesheet sequence column.") } + .collectFile(name: "manual_interactions.fasta", newLine: false) { fasta_file -> + ["manual_interactions.fasta", fasta_file.text.trim() + "\n"] + } } - ch_interaction_raw = CREATE_INTERACTIONS.out.interactions - .flatMap { interactions_fasta -> + ch_interaction_has_protein = ch_interaction_raw.flatMap { interactions_fasta -> def out = [] def lines = interactions_fasta.readLines().findAll { it?.trim() } if (lines.size() % 2 != 0) { @@ -164,13 +178,18 @@ workflow WISPS { def interaction_id = header.substring(1).trim() def sequence_line = chunk[1].trim() - //def has_protein = sequence_line.split(":").any { !it.contains("|") } def has_protein = sequence_line.split(":").count { !it.contains("|") } > 1 out << [interaction_id, has_protein] } out } - ch_interaction_raw + + if ("manual" in interaction_mode) { + ch_interaction_info = ch_interaction_has_protein + .map { interaction_id, _ -> [interaction_id, "", ""] } + } + + ch_interaction_has_protein .join(ch_interaction_info) .map { interaction_id, has_protein, int_chain_map, str_chain_map -> [ @@ -184,11 +203,10 @@ workflow WISPS { } .set{ch_interaction_in} - ch_interaction_in.count().subscribe{print("total final: ${it}")} MMSEQS_COLABFOLDSEARCH ( - CREATE_INTERACTIONS.out.interactions.map{[["id": "all_run"], it]}, + ch_interaction_raw.map{[["id": "all_run"], it]}, ch_colabfold_db, ch_uniref30 ) From e798c21f3acfea5566970ff79cae52d7d487de12 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Sun, 12 Apr 2026 23:40:21 +1000 Subject: [PATCH 45/70] fix ipsae join on id --- workflows/wisps.nf | 30 ++++++++++++------------------ 1 file changed, 12 insertions(+), 18 deletions(-) diff --git a/workflows/wisps.nf b/workflows/wisps.nf index d4fa5cb..1826a06 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -375,15 +375,15 @@ workflow WISPS { ipsae_batch = 0 + ch_protein_interaction_by_id = ch_interaction_in + .filter { it[1] } + .map { [it[0].id, it[0]] } ch_colabfold_scores .join(ch_colabfold_pdb) - .map{[["id": it[0].id], it]} - .join(ch_interaction_in - .filter{it[1]} - .map{it[0]} - ) - .map{[it[1][1], it[1][2], []]} + .map { [it[0].id, it[1], it[2]] } + .join(ch_protein_interaction_by_id) + .map { id, score_json, pdb_file, _ -> [score_json, pdb_file, []] } .buffer( size: analysis_batch_size, remainder: true ) .map{ ipsae_batch += 1; @@ -393,12 +393,9 @@ workflow WISPS { ch_boltz_pae .join(ch_boltz_cif) .join(ch_boltz_confidence) - .map{[["id": it[0].id], [it[0], it[1], it[2]], it[3]]} - .join(ch_interaction_in - .filter{it[1]} - .map{it[0]} - ) - .map{[it[1][1], it[1][2], it[2]]} + .map { [it[0].id, it[1], it[2], it[3]] } + .join(ch_protein_interaction_by_id) + .map { id, pae_file, cif_file, confidence_json, _ -> [pae_file, cif_file, confidence_json] } .buffer( size: analysis_batch_size, remainder: true ) .map{ ipsae_batch += 1; @@ -407,12 +404,9 @@ workflow WISPS { ) .mix( ch_alphafold3_confidence.join(ch_alphafold3_cif) - .map{[["id": it[0].id], it]} - .join(ch_interaction_in - .filter{it[1]} - .map{it[0]} - ) - .map{[it[1][1], it[1][2], []]} + .map { [it[0].id, it[1], it[2]] } + .join(ch_protein_interaction_by_id) + .map { id, confidence_json, cif_file, _ -> [confidence_json, cif_file, []] } .buffer( size: analysis_batch_size, remainder: true ) .map{ ipsae_batch += 1; From 8c8a2ad29aab0be3359eae6117e3f263911a6987 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Tue, 14 Apr 2026 07:57:55 +1000 Subject: [PATCH 46/70] report max cross group wisps --- workflows/wisps.nf | 74 ++++++++++++++++++++++++++++++++++++++++++++-- 1 file changed, 71 insertions(+), 3 deletions(-) diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 1826a06..810fc8c 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -439,6 +439,53 @@ workflow WISPS { [sampleId, entries] } + def parseStrChainMap = { strChainMap -> + if (!strChainMap || !strChainMap.contains(":")) { + return [[], []] + } + def parts = strChainMap.split(":", 2) + def leftIds = parts[0].split(",").collect { it.trim() }.findAll { it != "" } + def rightIds = parts[1].split(",").collect { it.trim() }.findAll { it != "" } + [leftIds, rightIds] + } + + def computeMaxCrossGroupIpsae = { entries, strChainMap -> + if (!entries) { + return null + } + def overallMax = entries.collect { it[1] }.findAll { it != null }.max() + + // If no chain map exists, fall back to the overall max IPSAE. + if (!strChainMap || !strChainMap.contains(":")) { + return overallMax + } + + def parsed = parseStrChainMap(strChainMap) + def leftIds = parsed[0] as Set + def rightIds = parsed[1] as Set + if (leftIds.isEmpty() || rightIds.isEmpty()) { + return overallMax + } + + def crossScores = entries.collect { pair -> + def pairId = pair[0].toString() + def score = pair[1] + def chains = pairId.split("_", 2) + if (chains.size() != 2) { + chains = pairId.split("-", 2) + } + if (chains.size() != 2) { + return null + } + def left = chains[0].trim() + def right = chains[1].trim() + ((leftIds.contains(left) && rightIds.contains(right)) || + (leftIds.contains(right) && rightIds.contains(left))) ? score : null + }.findAll { it != null } + + crossScores ? crossScores.max() : null + } + IPSAE.out.txt .transpose() .branch { @@ -504,9 +551,30 @@ workflow WISPS { ) { item -> [item[0], item[1]] } .set { ch_ipsae_scores_by_pair } - // 4) Additional summary file: max score per sample/model across all pair ids - ch_model_wide = ch_long - .map { sampleId, pairId, model, score -> [[sampleId, model], score] } + // 4) Additional summary file: max cross-group (left/right in str_chain_map) IPSAE per sample/model + ch_str_chain_map_by_id = ch_interaction_in.map { [it[0].id, it[0].str_chain_map] } + + ch_model_rows = ch_ipsae_out.boltz + .join(ch_str_chain_map_by_id, remainder: true) + .map { sampleId, entries, strChainMap -> + [[sampleId, "boltz"], computeMaxCrossGroupIpsae(entries, strChainMap)] + } + .mix( + ch_ipsae_out.colabfold + .join(ch_str_chain_map_by_id, remainder: true) + .map { sampleId, entries, strChainMap -> + [[sampleId, "colabfold"], computeMaxCrossGroupIpsae(entries, strChainMap)] + } + ) + .mix( + ch_ipsae_out.alphafold3 + .join(ch_str_chain_map_by_id, remainder: true) + .map { sampleId, entries, strChainMap -> + [[sampleId, "alphafold3"], computeMaxCrossGroupIpsae(entries, strChainMap)] + } + ) + + ch_model_wide = ch_model_rows .groupTuple() .map { key, scores -> [key[0], [key[1], scores.max()]] } .groupTuple() From 682bc823d175507e7a62d5a84254c658152f70df Mon Sep 17 00:00:00 2001 From: tlitfin Date: Tue, 14 Apr 2026 08:34:39 +1000 Subject: [PATCH 47/70] fix envdb prefix bug --- nextflow_schema.json | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nextflow_schema.json b/nextflow_schema.json index c47699e..900c8c7 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -125,7 +125,7 @@ "type": "string", "description": "Link to the ColabFold database", "fa_icon": "fas fa-folder-open", - "default": "colabfold_uniref30/uniref30_2302_db" + "default": "colabfold_envdb/colabfold_envdb_202108_db" }, "spire_db": { "type": "string", From 17b7462fc85bec6ead3a3ab5a6952b412e4d27f5 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Tue, 14 Apr 2026 09:23:11 +1000 Subject: [PATCH 48/70] update param names --- conf/gadi.config | 4 ++-- conf/test_gadi.config | 6 +++--- docs/usage.md | 2 +- main.nf | 6 +++--- modules/local/data_convertor/create_interactions.nf | 4 ++-- nextflow.config | 5 ++--- nextflow_schema.json | 12 ++---------- subworkflows/local/msa.nf | 8 ++++---- workflows/wisps.nf | 12 ++++++------ 9 files changed, 25 insertions(+), 34 deletions(-) diff --git a/conf/gadi.config b/conf/gadi.config index 4df154a..1fade99 100644 --- a/conf/gadi.config +++ b/conf/gadi.config @@ -28,8 +28,8 @@ params { boltz2_conf = "/g/data/li87/struct_bio/params/boltz/boltz2_conf.ckpt" boltz2_mols = "/g/data/li87/struct_bio/params/boltz/mols" - uniref30 = "/g/data/li87/proteinfold_dbs/colabfold_uniref30/" - colabfold_db = "/g/data/li87/proteinfold_dbs/colabfold_envdb/" + colabfold_uniref30 = "/g/data/li87/proteinfold_dbs/colabfold_uniref30/" + colabfold_envdb = "/g/data/li87/proteinfold_dbs/colabfold_envdb/" colabfold_alphafold2_params = "/g/data/li87/struct_bio/params/alphafold2/" diff --git a/conf/test_gadi.config b/conf/test_gadi.config index 1f58f54..cca3175 100644 --- a/conf/test_gadi.config +++ b/conf/test_gadi.config @@ -25,9 +25,9 @@ params { boltz2_aff = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz2_aff.ckpt" boltz2_conf = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz2_conf.ckpt" boltz2_mols = "/g/data/if89/proteinfold_dbs/boltz_dbs/mols" - colabfold_db = "/g/data/if89/proteinfold_dbs/miniature_databases/colabfold_envdb_202108/" - uniref30 = "/g/data/za08/tom/colabfold_uniref30" - colabfold_alphafold2_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params/alphafold_params_colab_2022-12-06/" + colabfold_envdb = "/g/data/if89/proteinfold_dbs/miniature_databases/colabfold_envdb_202108/" + colabfold_uniref30 = "/g/data/za08/tom/colabfold_uniref30" + colabfold_alphafold2_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params/alphafold_params_2022-12-06/" alphafold3_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" diff --git a/docs/usage.md b/docs/usage.md index 7ce1ac0..ca45b6c 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -40,7 +40,7 @@ An [example samplesheet](../assets/samplesheet.csv) has been provided with the p The created interactions generated from the sample sheet are customised through the parameter `--mode`. Two different ways to customise what interactions are generated from the sample sheet: -1. The default behavior is for `--mode all-all`. In this case, the workflow will generate interaction pairs for all samples in the sample sheet against each other (all possible combinations) and keep the unique pairs after ignoring the order of the samples. This does not require the group column to be provided in the sample sheet, and this is the default behavior of the workflow unless the `--mode` parameter is customised. When using this mode, the user can liit the number of formed interactions through the parameter `interaction_threshold` which takes a numeric value. by default the value is 0 and all interactions are formed. For any positive value `n`, onlye the neighboring paires that are within `n` neighbors will be considered. In this case, teh order of the samples in teh sample sheet matters. For example, if `--interaction_threshold 2`, the 2 nighbouring samples (2 before and 2 after) will be consdered. +1. The default behavior is for `--mode all-all`. In this case, the workflow will generate interaction pairs for all samples in the sample sheet against each other (all possible combinations) and keep the unique pairs after ignoring the order of the samples. This does not require the group column to be provided in the sample sheet, and this is the default behavior of the workflow unless the `--mode` parameter is customised. When using this mode, the user can liit the number of formed interactions through the parameter `interaction_neighbours` which takes a numeric value. by default the value is 0 and all interactions are formed. For any positive value `n`, onlye the neighboring paires that are within `n` neighbors will be considered. In this case, teh order of the samples in teh sample sheet matters. For example, if `--interaction_neighbours 2`, the 2 nighbouring samples (2 before and 2 after) will be consdered. 2. A custom combination can be achieved through the column group in the sample sheet. You can use a combination of the group values. You can use multiple combinations by separating them with a comma (`,`). For example, there are group `A` and group `B1` in the example sample sheet above, running the pipeline with `--mode A-A,A-B` will generate the followiong pairs `S1-S1`, `S3-S3`, and `S1-S3` from the combination `A-A` and add to it the pait `S1-S2` and `S2-S3` from teh combination `A-B`. diff --git a/main.nf b/main.nf index 9571eee..e8ba6ba 100644 --- a/main.nf +++ b/main.nf @@ -47,8 +47,8 @@ workflow NFCORE_WISPS { Channel.fromPath(params.boltz2_aff, checkIfExists: true).first(), Channel.fromPath(params.boltz2_conf, checkIfExists: true).first(), Channel.fromPath(params.boltz2_mols, checkIfExists: true).first(), - Channel.fromPath(params.colabfold_db, checkIfExists: true).first(), - Channel.fromPath(params.uniref30, checkIfExists: true).first(), + Channel.fromPath(params.colabfold_envdb, checkIfExists: true).first(), + Channel.fromPath(params.colabfold_uniref30, checkIfExists: true).first(), Channel.fromPath(params.colabfold_alphafold2_params, checkIfExists: true).first(), params.colabfold_num_recycles, Channel.fromPath(params.alphafold3_params, checkIfExists: true).first(), @@ -60,7 +60,7 @@ workflow NFCORE_WISPS { params.outdir, params.analysis_batch_size, params.colabfold_batch_size, - params.interaction_threshold + params.interaction_neighbours ) ch_versions = ch_versions.mix(WISPS.out.versions) diff --git a/modules/local/data_convertor/create_interactions.nf b/modules/local/data_convertor/create_interactions.nf index 9b0948a..96316a8 100644 --- a/modules/local/data_convertor/create_interactions.nf +++ b/modules/local/data_convertor/create_interactions.nf @@ -13,7 +13,7 @@ process CREATE_INTERACTIONS { val(groups) val(seqs) val(interaction_mode) - val(interaction_threshold) + val(interaction_neighbours) output: path ("interactions.fasta"), emit: interactions @@ -81,7 +81,7 @@ process CREATE_INTERACTIONS { if interaction_mode[0] != "all-all" and groups[i] not in group_ls: continue - if (interaction_mode[0] != "all-all" and "-".join(sorted([groups[i], groups[j]])) in interaction_mode) or (interaction_mode[0] == "all-all" and (${interaction_threshold} == 0 or abs(i-j) <= ${interaction_threshold})): + if (interaction_mode[0] != "all-all" and "-".join(sorted([groups[i], groups[j]])) in interaction_mode) or (interaction_mode[0] == "all-all" and (${interaction_neighbours} == 0 or abs(i-j) <= ${interaction_neighbours})): interactions_cntr += 1 left_chain_count = chain_count(types[i], seqs[i]) right_chain_count = chain_count(types[j], seqs[j]) diff --git a/nextflow.config b/nextflow.config index e49f8fe..8df2de3 100644 --- a/nextflow.config +++ b/nextflow.config @@ -13,7 +13,7 @@ params { // Input options input = null mode = "all-all" - interaction_threshold = 0 + interaction_neighbours = 0 mmseqs_gpu = false use_gpu = true analysis_batch_size = 20 @@ -28,8 +28,7 @@ params { boltz2_conf = 'https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_conf.ckpt' boltz2_mols = null // extract this file locally: 'https://huggingface.co/boltz-community/boltz-2/resolve/main/mols.tar' - colabfold_db = null - uniref30 = null + colabfold_uniref30 = null colabfold_alphafold2_params = null colabfold_envdb = null alphafold3_params = null diff --git a/nextflow_schema.json b/nextflow_schema.json index 900c8c7..1400753 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -55,7 +55,7 @@ "description": "Number of ColabFold samples to be processed in the analysis after multiple single alignment", "fa_icon": "fas fa-microchip" }, - "interaction_threshold": { + "interaction_neighbours": { "type": "integer", "default": 0, "description": "Local neighbourhood to model in all-by-all mode", @@ -97,15 +97,7 @@ "description": "Define where the pipeline should find input data and save output data.", "required": ["input", "outdir"], "properties": { - "colabfold_db": { - "type": "string", - "format": "path", - "exists": true, - "description": "Specifies the PARAMS and DB path used by 'colabfold' mode", - "fa_icon": "fas fa-folder-open", - "errorMessage": "Please provide a valid path to ColabFold database" - }, - "uniref30": { + "colabfold_uniref30": { "type": "string", "description": "Link to the UniRef30 database", "fa_icon": "fas fa-folder-open" diff --git a/subworkflows/local/msa.nf b/subworkflows/local/msa.nf index d1b2bf4..7810742 100644 --- a/subworkflows/local/msa.nf +++ b/subworkflows/local/msa.nf @@ -11,8 +11,8 @@ workflow MSA { take: ch_samplesheet - ch_colabfold_db // channel: path(colabfold_db) - ch_uniref30 // channel: path(uniref30) + ch_colabfold_envdb // channel: path(colabfold_envdb) + ch_colabfold_uniref30 // channel: path(colabfold_uniref30) batch_size main: @@ -69,8 +69,8 @@ workflow MSA { MMSEQS_COLABFOLDSEARCH ( ch_input_seqs, - ch_colabfold_db, - ch_uniref30 + ch_colabfold_envdb, + ch_colabfold_uniref30 ) ch_versions = ch_versions.mix(MMSEQS_COLABFOLDSEARCH.out.versions) diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 810fc8c..212ed56 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -60,8 +60,8 @@ workflow WISPS { ch_boltz2_aff ch_boltz2_conf ch_mols - ch_colabfold_db - ch_uniref30 + ch_colabfold_envdb + ch_colabfold_uniref30 ch_colabfold_params num_recycles ch_alphafold3_params @@ -73,7 +73,7 @@ workflow WISPS { outdir analysis_batch_size colabfold_batch_size - interaction_threshold + interaction_neighbours main: ch_multiqc_files = Channel.empty() @@ -128,7 +128,7 @@ workflow WISPS { ch_raw_sample_sheet.groups.collect(), ch_raw_sample_sheet.seqs.collect(), interaction_mode, - interaction_threshold + interaction_neighbours ) ch_interaction_info = CREATE_INTERACTIONS.out.interaction_mapping @@ -207,8 +207,8 @@ workflow WISPS { MMSEQS_COLABFOLDSEARCH ( ch_interaction_raw.map{[["id": "all_run"], it]}, - ch_colabfold_db, - ch_uniref30 + ch_colabfold_envdb, + ch_colabfold_uniref30 ) ch_versions = ch_versions.mix(MMSEQS_COLABFOLDSEARCH.out.versions) From df2060ae33d80df7db8f3b697c3599df560f85b3 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Tue, 14 Apr 2026 18:27:14 +1000 Subject: [PATCH 49/70] Update documentation --- README.md | 73 ++++++++++++++++++++++------------ conf/dbs.config | 16 ++++++++ conf/modules_alphafold3.config | 15 +++++++ conf/modules_boltz.config | 17 ++++++++ conf/modules_colabfold.config | 14 +++++++ docs/output.md | 70 +++++++++++++++++++++++++++++++- docs/usage.md | 20 +++++++--- nextflow.config | 47 +++++++++++++++++----- nextflow_schema.json | 28 ++++++++----- 9 files changed, 249 insertions(+), 51 deletions(-) create mode 100644 conf/dbs.config create mode 100644 conf/modules_alphafold3.config create mode 100644 conf/modules_boltz.config create mode 100644 conf/modules_colabfold.config diff --git a/README.md b/README.md index 6514708..fc9a1e4 100644 --- a/README.md +++ b/README.md @@ -19,50 +19,73 @@ ## Introduction -**nf-core/wisps** is a bioinformatics pipeline that ... - - +**nf-core/wisps** is a bioinformatics pipeline for interaction screening by structure prediction. It ingests a samplesheet of sequence entries (FASTA format) and generates interaction sets based on all-vs-all or group-based modes. The workflow then runs MSA/search and structure prediction with supported models (Boltz, ColabFold, and/or AlphaFold3), computes confidence/interface metrics (including IPSAE), and produces per-interaction result files alongside run-level reports such as MultiQC. - - -2. Present QC for raw reads ([`MultiQC`](http://multiqc.info/)) +- Validate and parse sequence inputs from the samplesheet (FASTA). +- Build interaction sets in manual, all-vs-all or group-based screening mode. +- Generated paired MSAs for each interaction using ColabFold Search powered by MMSeqs2. +- Run structure prediction for each interaction with the configured model(s) (Boltz, ColabFold, and/or AlphaFold3). +- Compute confidence and interface metrics, including IPSAE. +- Aggregate run metrics and QC summaries in [`MultiQC`](http://multiqc.info/). ## Usage > [!NOTE] > If you are new to Nextflow and nf-core, please refer to [this page](https://nf-co.re/docs/usage/installation) on how to set-up Nextflow. Make sure to [test your setup](https://nf-co.re/docs/usage/introduction#how-to-run-a-pipeline) with `-profile test` before running the workflow on actual data. - +To run the pipeline with the minimum required inputs: + +1. Create a samplesheet CSV with at least `id` and `sequence` columns (`type` and `group` are optional). +2. Put one sequence entry per row; `sequence` must point to a `.fasta` file. Each fasta file may contain multiple entities which will be considered as a single unit when building candidate interactions. +3. Run `nextflow run` with `--input`, `--outdir`, and a compute `-profile`. + +`samplesheet.csv`: + +```csv +id,sequence,type,group +S1,./data/S1.fasta,protein,A +S2,./data/S2.fasta,protein,B +S3,./data/S3.fasta,rna,A +``` -Now, you can run the pipeline using: +In this file, each row represents a single unit (can contain multiple sequences) to be used to generate candidate interactions. - +Now, to model molecules in group A partnered with molecules in group B you can run the pipeline using: ```bash -nextflow run nf-core/wisps \ - -profile \ - --input samplesheet.csv \ - --outdir +nextflow run Australian-Structural-Biology-Computing/wisps \ + --input ./samplesheet.csv \ + --outdir ./results \ + --db WISPS-DB \ + --mode A-B \ + -profile docker ``` > [!WARNING] diff --git a/conf/dbs.config b/conf/dbs.config new file mode 100644 index 0000000..f5a2d0e --- /dev/null +++ b/conf/dbs.config @@ -0,0 +1,16 @@ +/* +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + Nextflow config file for database links and paths +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + Centralizes URLs and local paths for all external resources used in the workflow. + Update version numbers and base directories in one place for maintainability. +---------------------------------------------------------------------------------------- +*/ + +params { + + // Colabfold + colabfold_uniref30 = "${params.db}/colabfold_uniref30/" + colabfold_envdb = "${params.db}/colabfold_envdb/" + +} \ No newline at end of file diff --git a/conf/modules_alphafold3.config b/conf/modules_alphafold3.config new file mode 100644 index 0000000..51f1efe --- /dev/null +++ b/conf/modules_alphafold3.config @@ -0,0 +1,15 @@ +/* +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + Nextflow config file for database links and paths +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + Centralizes URLs and local paths for all external resources used in the workflow. + Update version numbers and base directories in one place for maintainability. +---------------------------------------------------------------------------------------- +*/ + +params { + + // AlphaFold3 + alphafold3_params = "${params.db}/params/af3.bin" + +} \ No newline at end of file diff --git a/conf/modules_boltz.config b/conf/modules_boltz.config new file mode 100644 index 0000000..cd860a7 --- /dev/null +++ b/conf/modules_boltz.config @@ -0,0 +1,17 @@ +/* +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + Nextflow config file for database links and paths +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + Centralizes URLs and local paths for all external resources used in the workflow. + Update version numbers and base directories in one place for maintainability. +---------------------------------------------------------------------------------------- +*/ + +params { + + // Boltz-2 + boltz2_aff = "${params.db}/params/boltz2_aff.ckpt" + boltz2_conf = "${params.db}/params/boltz2_conf.ckpt" + boltz2_mols = "${params.db}/params/mols" + +} \ No newline at end of file diff --git a/conf/modules_colabfold.config b/conf/modules_colabfold.config new file mode 100644 index 0000000..21a8e05 --- /dev/null +++ b/conf/modules_colabfold.config @@ -0,0 +1,14 @@ +/* +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + Nextflow config file for database links and paths +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + Centralizes URLs and local paths for all external resources used in the workflow. + Update version numbers and base directories in one place for maintainability. +---------------------------------------------------------------------------------------- +*/ + +params { + + colabfold_alphafold2_params = "${params.db}/params/alphafold_params_2022-12-06" + +} \ No newline at end of file diff --git a/docs/output.md b/docs/output.md index aa34f33..b5b9512 100644 --- a/docs/output.md +++ b/docs/output.md @@ -6,13 +6,81 @@ This document describes the output produced by the pipeline. Most of the plots a The directories listed below will be created in the results directory after the pipeline has finished. All paths are relative to the top-level results directory. - +## WISPS-specific outputs + +### Interaction generation + +

    +Output files + +- `create/` + - `interactions.fasta`: generated interaction sequences used as model input. + - `interaction_mapping.tsv`: mapping between interaction IDs and chain indices / chain labels. + +
    + +This step expands the samplesheet inputs into pairwise interactions according to `--mode` and `--interaction_neighbours`. + +### MSA and model-input preparation + +
    +Output files + +- `mmseqs/` + - `*.a3m`: MSA files produced by `colabfold_search`. + - `*.json`: AlphaFold3 JSON input files (when AlphaFold3 is enabled). + - `*.yaml`: Boltz YAML input files (when Boltz is enabled). + - `*.csv`: Paired MSA in CSV format used by Boltz (when Boltz is enabled). + +
    + +These files are generated once from the interaction FASTA and reused by downstream structure prediction tools. + +### Structure prediction results + +
    +Output files + +- `run/` (outputs from both Boltz and AlphaFold3 modules) + - Boltz: + - `boltz_results_*/predictions/*/*.cif` and optional `*.pdb`: predicted structures. + - `boltz_results_*/predictions/*/confidence_*.json`: confidence metrics. + - `boltz_results_*/predictions/*/affinity_*.json`: affinity predictions (if produced). + - `boltz_results_*/predictions/*/pae_*.npz`: PAE matrices. + - `boltz_results_*/predictions/*/plddt_*.npz`: per-residue confidence arrays. + - `boltz_results_*/processed/structures/*.npz`: processed structure arrays. + - `boltz_results_*/processed/msa/*.npz`: processed MSA arrays. + - AlphaFold3: + - `out/*/*_model.cif`: top-ranked model structures. + - `out/*/*_confidences.json`: detailed confidence output. + - `out/*/*_summary_confidences.json`: summary confidence output. +- `colabfold/` + - `*_relaxed_rank_001_*_model_*.pdb`: relaxed top-ranked ColabFold structures. + - `*_scores_rank_001_*.json`: model score summaries. + - `*_coverage.png`: MSA coverage plots. + +
    + +### IPSAE and confidence summaries + +
    +Output files + +- `ipsae/` + - `*.pml`, `*_byres.txt`, `*.txt`: IPSAE per-structure analysis outputs. + - `ipsae_scores.csv`: per-interaction summary table with maximum cross-group IPSAE scores by model. + - `ipsae_scores_.csv`: per-chain-pair IPSAE tables across all interactions. +- `collect/` + - `*_confidence_scores_full.csv`: model-specific confidence summary tables used by MultiQC including a maximum cross-group chainwise ipTM score. + +
    ## Pipeline overview The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes data using the following steps: - [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline +- [WISPS-specific outputs](#wisps-specific-outputs) - Interaction files, model inputs, structure predictions, and summary tables - [Pipeline information](#pipeline-information) - Report metrics generated during the workflow execution ### MultiQC diff --git a/docs/usage.md b/docs/usage.md index ca45b6c..55c8aba 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -24,25 +24,35 @@ An example of the sample sheet used for the pipeline is shown below: id,sequence,group,type S1,S1.fasta,A,protein S2,Sample2.fasta,B,protein -S3,S3.yaml,A,rna +S3,S3.fasta,A,rna ``` | Column | Description | | ---------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `id` | The `id` identifiers have to be unique in the sample sheet and **must not** have an underscore or hyphen (`_`, `-`). | -| `sequence` | Full path to Fasta/YAML file for sample sequence. File has to have the extension ".fasta", ".fa", or "yaml". | +| `sequence` | Full path to FASTA file for sample sequence. File has to have the extension ".fasta", or ".fa" | | `type` | The sequence type, can be either `protein`, `rna`, `smiles`. It is an optional column; by default, it will be considered as `protein`. | | `group` | It is a way to group samples together to create custom interactions. It is an optional column and **must not** have a hyphen (`-`). If not provided, the interactions will be `all-all`, which means all samples against all samples, or you can use `group.a-group.b` to only consider the samples from `group.a` against samples from `group.b`. | +A sequence file can contain multiple entities but if the entities are different types, they must adhere to the colabfold standard described below. + An [example samplesheet](../assets/samplesheet.csv) has been provided with the pipeline. ## Creating Interactions from sample sheet -The created interactions generated from the sample sheet are customised through the parameter `--mode`. Two different ways to customise what interactions are generated from the sample sheet: +The interactions generated from the sample sheet are controlled with `--mode`. There are three supported modes: + +1. `--mode all-all` (default): the workflow generates all unique sample pairs (order-independent) across the full sample sheet. This mode does not require the `group` column. You can limit pair generation with `--interaction_neighbours `. The default is `0` (no limit). For any positive `n`, only pairs within `n` neighbours in the sample sheet order are kept. For example, with `--interaction_neighbours 2`, each sample is paired with up to 2 samples before and 2 samples after it. + +2. Group-based mode (for example, `--mode A-A,A-B`): interactions are generated only for the requested group combinations from the `group` column (comma-separated, no spaces). With groups `A` and `B`, `--mode A-A,A-B` will include all `A-A` pairs plus all `A-B` pairs. -1. The default behavior is for `--mode all-all`. In this case, the workflow will generate interaction pairs for all samples in the sample sheet against each other (all possible combinations) and keep the unique pairs after ignoring the order of the samples. This does not require the group column to be provided in the sample sheet, and this is the default behavior of the workflow unless the `--mode` parameter is customised. When using this mode, the user can liit the number of formed interactions through the parameter `interaction_neighbours` which takes a numeric value. by default the value is 0 and all interactions are formed. For any positive value `n`, onlye the neighboring paires that are within `n` neighbors will be considered. In this case, teh order of the samples in teh sample sheet matters. For example, if `--interaction_neighbours 2`, the 2 nighbouring samples (2 before and 2 after) will be consdered. +3. `--mode manual`: no interaction pairing is generated from the sample sheet. Instead, each FASTA record is treated as one interaction input directly. In this mode, provide interaction FASTA entries in the required ColabFold format: + - One FASTA record per interaction (`>interaction_id` then one sequence line). + - Use `:` to separate entities/chains in a complex. + - Use `molecule_type|sequence` for non-protein entities (for example `dna|ATCG`, `rna|AUGC`, `ccd|ATP`, `smiles|...`; optional copies like `ccd|ATP|2`). + - If SMILES contains aromatic bonds, replace `:` with `;` as required by ColabFold parsing. -2. A custom combination can be achieved through the column group in the sample sheet. You can use a combination of the group values. You can use multiple combinations by separating them with a comma (`,`). For example, there are group `A` and group `B1` in the example sample sheet above, running the pipeline with `--mode A-A,A-B` will generate the followiong pairs `S1-S1`, `S3-S3`, and `S1-S3` from the combination `A-A` and add to it the pait `S1-S2` and `S2-S3` from teh combination `A-B`. +Reference: ColabFold input format examples in the official repository README: . ## Running the pipeline diff --git a/nextflow.config b/nextflow.config index 8df2de3..d73aa38 100644 --- a/nextflow.config +++ b/nextflow.config @@ -12,21 +12,22 @@ params { // TODO nf-core: Specify your pipeline's command line flags // Input options input = null - mode = "all-all" - interaction_neighbours = 0 - mmseqs_gpu = false - use_gpu = true - analysis_batch_size = 20 - colabfold_batch_size = 10 - colabfold_num_recycles = 3 - tools = "boltz,colabfold" + mode = "all-all" + interaction_neighbours = 0 + mmseqs_gpu = false + use_gpu = true + analysis_batch_size = 20 + colabfold_batch_size = 10 + colabfold_num_recycles = 3 + tools = "boltz,colabfold" + db = null ipsae_pae_cutoff = 10 ipsae_dist_cutoff = 10 - boltz2_aff = 'https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_aff.ckpt' - boltz2_conf = 'https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_conf.ckpt' - boltz2_mols = null // extract this file locally: 'https://huggingface.co/boltz-community/boltz-2/resolve/main/mols.tar' + boltz2_aff = null // 'https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_aff.ckpt' + boltz2_conf = null // 'https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_conf.ckpt' + boltz2_mols = null // 'https://huggingface.co/boltz-community/boltz-2/resolve/main/mols.tar' colabfold_uniref30 = null colabfold_alphafold2_params = null @@ -290,3 +291,27 @@ validation { // Load modules.config for DSL2 module specific options includeConfig 'conf/modules.config' + +includeConfig ({ + if (params.tools.toLowerCase().split(",").contains("alphafold3")) { + return 'conf/modules_alphafold3.config' + } + return '/dev/null' +}()) + +includeConfig ({ + if (params.tools.toLowerCase().split(",").contains("boltz")) { + return 'conf/modules_boltz.config' + } + return '/dev/null' +}()) + +includeConfig ({ + if (params.tools.toLowerCase().split(",").contains("colabfold")) { + return 'conf/modules_colabfold.config' + } + return '/dev/null' +}()) + +// Load links to DBs and parameters +includeConfig 'conf/dbs.config' diff --git a/nextflow_schema.json b/nextflow_schema.json index 1400753..f6168f0 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -97,15 +97,22 @@ "description": "Define where the pipeline should find input data and save output data.", "required": ["input", "outdir"], "properties": { + "db": { + "type": "string", + "description": "Path to reference data and model parameters", + "fa_icon": "fas fa-folder-open" + }, "colabfold_uniref30": { "type": "string", "description": "Link to the UniRef30 database", - "fa_icon": "fas fa-folder-open" + "fa_icon": "fas fa-folder-open", + "default": "null/colabfold_uniref30/" }, "colabfold_envdb": { "type": "string", "description": "Link to the ColabFold database", - "fa_icon": "fas fa-folder-open" + "fa_icon": "fas fa-folder-open", + "default": "null/colabfold_envdb/" }, "colabfold_uniref30_prefix": { "type": "string", @@ -127,25 +134,28 @@ "colabfold_alphafold2_params": { "type": "string", "description": "Link to the Alphafold2 parameters for Colabfold", - "fa_icon": "fas fa-folder-open" + "fa_icon": "fas fa-folder-open", + "default": "null/params/alphafold_params_2022-12-06" }, "boltz2_aff": { "type": "string", - "default": "https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_aff.ckpt", - "description": "Path to boltz affinity file" + "description": "Path to boltz affinity file", + "default": "null/params/boltz2_aff.ckpt" }, "boltz2_conf": { "type": "string", - "default": "https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_conf.ckpt", - "description": "Path to boltz-2 conf file" + "description": "Path to boltz-2 conf file", + "default": "null/params/boltz2_conf.ckpt" }, "boltz2_mols": { "type": "string", - "description": "Path to boltz-2 mols" + "description": "Path to boltz-2 mols", + "default": "null/params/mols" }, "alphafold3_params": { "type": "string", - "description": "Path to Alphafold3 params" + "description": "Path to Alphafold3 params", + "default": "null/params/af3.bin" } } }, From fc5311a6e5a45cf9070f1de99f5955dc89651f3b Mon Sep 17 00:00:00 2001 From: tlitfin Date: Tue, 14 Apr 2026 19:51:41 +1000 Subject: [PATCH 50/70] fix single mode db bug --- main.nf | 27 ++++++++++++++++++++++----- 1 file changed, 22 insertions(+), 5 deletions(-) diff --git a/main.nf b/main.nf index e8ba6ba..cfcbf59 100644 --- a/main.nf +++ b/main.nf @@ -28,6 +28,7 @@ workflow NFCORE_WISPS { take: samplesheet // channel: samplesheet read in from --input main: + tool_set = params.tools.toLowerCase().split(",") as Set ch_samplesheet = samplesheet ch_multiqc = Channel.empty() ch_versions = Channel.empty() @@ -36,6 +37,22 @@ workflow NFCORE_WISPS { ch_multiqc_custom_config = params.multiqc_config ? Channel.fromPath( params.multiqc_config ).first() : Channel.empty() ch_multiqc_logo = params.multiqc_logo ? Channel.fromPath( params.multiqc_logo ).first() : Channel.empty() ch_multiqc_methods_description = params.multiqc_methods_description ? file(params.multiqc_methods_description, checkIfExists: true) : file("$projectDir/assets/methods_description_template.yml", checkIfExists: true) + + ch_boltz2_aff = ("boltz" in tool_set) + ? Channel.fromPath(params.boltz2_aff, checkIfExists: true).first() + : Channel.empty() + ch_boltz2_conf = ("boltz" in tool_set) + ? Channel.fromPath(params.boltz2_conf, checkIfExists: true).first() + : Channel.empty() + ch_boltz2_mols = ("boltz" in tool_set) + ? Channel.fromPath(params.boltz2_mols, checkIfExists: true).first() + : Channel.empty() + ch_colabfold_alphafold2_params = ("colabfold" in tool_set) + ? Channel.fromPath(params.colabfold_alphafold2_params, checkIfExists: true).first() + : Channel.empty() + ch_alphafold3_params = ("alphafold3" in tool_set) + ? Channel.fromPath(params.alphafold3_params, checkIfExists: true).first() + : Channel.empty() // // WORKFLOW: Run pipeline // @@ -44,14 +61,14 @@ workflow NFCORE_WISPS { ch_samplesheet, params.mode, ch_versions, - Channel.fromPath(params.boltz2_aff, checkIfExists: true).first(), - Channel.fromPath(params.boltz2_conf, checkIfExists: true).first(), - Channel.fromPath(params.boltz2_mols, checkIfExists: true).first(), + ch_boltz2_aff, + ch_boltz2_conf, + ch_boltz2_mols, Channel.fromPath(params.colabfold_envdb, checkIfExists: true).first(), Channel.fromPath(params.colabfold_uniref30, checkIfExists: true).first(), - Channel.fromPath(params.colabfold_alphafold2_params, checkIfExists: true).first(), + ch_colabfold_alphafold2_params, params.colabfold_num_recycles, - Channel.fromPath(params.alphafold3_params, checkIfExists: true).first(), + ch_alphafold3_params, params.tools, ch_multiqc_config, ch_multiqc_custom_config, From 95766a007811fa388402247bf26a6f4fe3701498 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Tue, 14 Apr 2026 19:54:03 +1000 Subject: [PATCH 51/70] minimal boltz outputs --- modules/local/run_boltz/main.nf | 12 ++---------- 1 file changed, 2 insertions(+), 10 deletions(-) diff --git a/modules/local/run_boltz/main.nf b/modules/local/run_boltz/main.nf index ef78d0c..b53e5dd 100644 --- a/modules/local/run_boltz/main.nf +++ b/modules/local/run_boltz/main.nf @@ -16,13 +16,9 @@ process RUN_BOLTZ { path ('mols') output: - tuple val(meta), path ("boltz_results_*/processed/msa/*.npz") , optional: true, emit: msa - tuple val(meta), path ("boltz_results_*/processed/structures/*.npz") , emit: structures tuple val(meta), path ("boltz_results_*/predictions/*/confidence*.json") , emit: confidence - tuple val(meta), path ("boltz_results_*/predictions/*/*.pdb") , optional: true, emit: pdb - tuple val(meta), path ("boltz_results_*/predictions/*/*model_0.cif") , optional: true, emit: cif - tuple val(meta), path ("boltz_results_*/predictions/*/plddt_*model_0.npz") , emit: plddt - tuple val(meta), path ("boltz_results_*/predictions/*/pae_*model_0.npz") , optional: true, emit: pae + tuple val(meta), path ("boltz_results_*/predictions/*/*model_0.cif") , emit: cif + tuple val(meta), path ("boltz_results_*/predictions/*/pae_*model_0.npz") , emit: pae tuple val(meta), path ("boltz_results_*/predictions/*/affinity_*.json") , optional: true, emit: affinity path "versions.yml", emit: versions @@ -62,13 +58,9 @@ process RUN_BOLTZ { fname=\${f##*/} id=\${fname%%_*} mkdir -p boltz_results_fasta/predictions/\${id}_boltz_interaction_input - touch boltz_results_fasta/predictions/\${id}_boltz_interaction_input/\${id}_boltz_interaction_input_model_0.pdb touch boltz_results_fasta/predictions/\${id}_boltz_interaction_input/\${id}_boltz_interaction_input_model_0.cif touch boltz_results_fasta/predictions/\${id}_boltz_interaction_input/confidence_\${id}_boltz_interaction_input_model_0.json touch boltz_results_fasta/predictions/\${id}_boltz_interaction_input/pae_\${id}_boltz_interaction_input_model_0.npz - touch boltz_results_fasta/predictions/\${id}_boltz_interaction_input/plddt_\${id}_boltz_interaction_input_model_0.npz - touch boltz_results_fasta/processed/msa/\${id}_boltz_interaction_input_0.npz - touch boltz_results_fasta/processed/structures/\${id}_boltz_interaction_input.npz done cat <<-END_VERSIONS > versions.yml From 84ad1ff1962948d6dd743cf2e53b3fd91f8df6a5 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Tue, 14 Apr 2026 20:13:56 +1000 Subject: [PATCH 52/70] cleanup unused db path print to log --- nextflow_schema.json | 21 +++++++-------------- 1 file changed, 7 insertions(+), 14 deletions(-) diff --git a/nextflow_schema.json b/nextflow_schema.json index f6168f0..fb4ddbc 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -105,14 +105,12 @@ "colabfold_uniref30": { "type": "string", "description": "Link to the UniRef30 database", - "fa_icon": "fas fa-folder-open", - "default": "null/colabfold_uniref30/" + "fa_icon": "fas fa-folder-open" }, "colabfold_envdb": { "type": "string", "description": "Link to the ColabFold database", - "fa_icon": "fas fa-folder-open", - "default": "null/colabfold_envdb/" + "fa_icon": "fas fa-folder-open" }, "colabfold_uniref30_prefix": { "type": "string", @@ -134,28 +132,23 @@ "colabfold_alphafold2_params": { "type": "string", "description": "Link to the Alphafold2 parameters for Colabfold", - "fa_icon": "fas fa-folder-open", - "default": "null/params/alphafold_params_2022-12-06" + "fa_icon": "fas fa-folder-open" }, "boltz2_aff": { "type": "string", - "description": "Path to boltz affinity file", - "default": "null/params/boltz2_aff.ckpt" + "description": "Path to boltz affinity file" }, "boltz2_conf": { "type": "string", - "description": "Path to boltz-2 conf file", - "default": "null/params/boltz2_conf.ckpt" + "description": "Path to boltz-2 conf file" }, "boltz2_mols": { "type": "string", - "description": "Path to boltz-2 mols", - "default": "null/params/mols" + "description": "Path to boltz-2 mols" }, "alphafold3_params": { "type": "string", - "description": "Path to Alphafold3 params", - "default": "null/params/af3.bin" + "description": "Path to Alphafold3 params" } } }, From 822fc1600c1db9fea43cdfc8b05a727f46684f36 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Tue, 14 Apr 2026 23:53:11 +1000 Subject: [PATCH 53/70] initial pool mode --- main.nf | 4 +- .../create_interaction_pools.nf | 227 ++++++++++++++++++ nextflow.config | 2 + nextflow_schema.json | 12 + workflows/wisps.nf | 75 +++++- 5 files changed, 312 insertions(+), 8 deletions(-) create mode 100644 modules/local/data_convertor/create_interaction_pools.nf diff --git a/main.nf b/main.nf index cfcbf59..7240eb2 100644 --- a/main.nf +++ b/main.nf @@ -77,7 +77,9 @@ workflow NFCORE_WISPS { params.outdir, params.analysis_batch_size, params.colabfold_batch_size, - params.interaction_neighbours + params.interaction_neighbours, + params.pool, + params.pool_size ) ch_versions = ch_versions.mix(WISPS.out.versions) diff --git a/modules/local/data_convertor/create_interaction_pools.nf b/modules/local/data_convertor/create_interaction_pools.nf new file mode 100644 index 0000000..6e10a12 --- /dev/null +++ b/modules/local/data_convertor/create_interaction_pools.nf @@ -0,0 +1,227 @@ +process CREATE_INTERACTION_POOLS { + tag "all_run" + label 'process_single' + + conda "${moduleDir}/environment.yml" + container "${ workflow.containerEngine == 'singularity' && !task.ext.singularity_pull_docker_container ? + 'https://depot.galaxyproject.org/singularity/python:3.8.3' : + 'quay.io/biocontainers/python:3.8.3' }" + + input: + val(ids) + val(types) + val(groups) + val(seqs) + val(pool_mode) + val(pool_max_total_length) + + output: + path ("interactions.fasta"), emit: interactions + path ("interaction_mapping.tsv"), emit: interaction_mapping + path "versions.yml" , emit: versions + + when: + task.ext.when == null || task.ext.when + + script: + """ + #!/usr/bin/env python3 + import sys + + seqs = [${"\"" + seqs.join('", "') + "\""}] + ids = [${"\"" + ids.join('", "') + "\""}] + types = [${"\"" + types.join('", "') + "\""}] + groups = [${"\"" + groups.join('", "') + "\""}] + pool_mode = [${"\"" + pool_mode.join('", "') + "\""}] + + pool_max_total_length = int(${pool_max_total_length}) + + if pool_max_total_length <= 0: + raise ValueError(f"pool_max_total_length must be > 0, got {pool_max_total_length}") + + n = len(seqs) + interactions_cntr = 0 + supported = {"dna", "rna", "ccd", "smiles"} + + def format_non_protein_entry(entity_type, entity_seq): + parsed_type = entity_type.lower() + parsed_seq = entity_seq + + # If sequence is already in colabfold format, keep it and normalize type. + if "|" in entity_seq: + parts = entity_seq.split("|") + if len(parts) > 1 and parts[0].lower() in supported: + parsed_type = parts[0].lower() + parsed_seq = "|".join(parts[1:]) + + if parsed_type == "smiles": + # ColabFold expects aromatic bonds to be written with ';' instead of ':'. + if "|" in parsed_seq: + smi_parts = parsed_seq.split("|") + smi_parts[0] = smi_parts[0].replace(":", ";") + parsed_seq = "|".join(smi_parts) + else: + parsed_seq = parsed_seq.replace(":", ";") + + return f"{parsed_type}|{parsed_seq}" + + def chain_count(entity_type, entity_seq): + if entity_type.lower() == "protein": + return len([chain for chain in entity_seq.split(":") if chain]) + return 1 + + def sequence_length(entity_type, entity_seq): + parsed_type = entity_type.lower() + parsed_seq = entity_seq + + # Handle already-prefixed non-protein entries: type|seq(|copies) + if "|" in entity_seq: + parts = entity_seq.split("|") + if len(parts) > 1 and parts[0].lower() in supported: + parsed_type = parts[0].lower() + parsed_seq = "|".join(parts[1:]) + + if parsed_type == "protein": + return sum(len(chain) for chain in parsed_seq.split(":") if chain) + + # For non-protein entities, use payload length and optional copies. + non_protein_parts = parsed_seq.split("|") + payload = non_protein_parts[0] + copies = 1 + if len(non_protein_parts) > 1 and non_protein_parts[-1].isdigit(): + copies = int(non_protein_parts[-1]) + return len(payload) * copies + + def entity_to_fasta(entity_type, entity_seq): + if entity_type.lower() == "protein": + return entity_seq + return format_non_protein_entry(entity_type, entity_seq) + + def int_id_to_str_id(i): + if i < 0: + raise ValueError(f"int_id_to_str_id: Only positive integers allowed, got {i}") + output = [] + while i >= 0: + output.append(chr(i % 26 + ord("A"))) + i = i // 26 - 1 + return "".join(output) + + def best_fit_decreasing_pool(indices, lengths, capacity): + # Bin-packing heuristic: keeps pools close to capacity without going over. + items = sorted(indices, key=lambda idx: lengths[idx], reverse=True) + bins = [] + + for idx in items: + item_len = lengths[idx] + if item_len > capacity: + raise ValueError( + f"Sequence '{ids[idx]}' length {item_len} exceeds available pool capacity {capacity}." + ) + + best_bin_pos = -1 + best_remaining_after = None + for b_idx, b in enumerate(bins): + if b["remaining"] >= item_len: + rem_after = b["remaining"] - item_len + if best_remaining_after is None or rem_after < best_remaining_after: + best_remaining_after = rem_after + best_bin_pos = b_idx + + if best_bin_pos == -1: + bins.append({"items": [idx], "remaining": capacity - item_len}) + else: + bins[best_bin_pos]["items"].append(idx) + bins[best_bin_pos]["remaining"] -= item_len + + return [b["items"] for b in bins] + + pool_pairs = [] + for mode_spec in pool_mode: + parts = mode_spec.split("-") + if len(parts) != 2 or any(not p.strip() for p in parts): + raise ValueError( + f"Invalid pooled mode entry '{mode_spec}'. Expected '-'." + ) + pool_pairs.append((parts[0].strip(), parts[1].strip())) + + seq_lengths = [sequence_length(types[i], seqs[i]) for i in range(n)] + + with open("interactions.fasta", "w") as target_interactions, open("interaction_mapping.tsv", "w") as mapping_file: + mapping_file.write("interaction_id\\tint_chain_map\\tstr_chain_map\\n") + + for pool_group_1, pool_group_2 in pool_pairs: + left_indices = [i for i in range(n) if groups[i] == pool_group_1] + right_indices = [i for i in range(n) if groups[i] == pool_group_2] + + if not left_indices: + raise ValueError(f"No entries found in pool group '{pool_group_1}'.") + if not right_indices: + raise ValueError(f"No entries found in pool group '{pool_group_2}'.") + + for left_i in left_indices: + left_len = seq_lengths[left_i] + pool_capacity = pool_max_total_length - left_len + if pool_capacity <= 0: + raise ValueError( + f"Left sequence '{ids[left_i]}' length {left_len} is >= pool_max_total_length {pool_max_total_length}." + ) + + # If groups are identical, do not self-pool with the same row. + current_right_indices = [idx for idx in right_indices if idx != left_i] + if not current_right_indices: + raise ValueError( + f"No valid group2 entries available for left entry '{ids[left_i]}' after self-exclusion." + ) + + pools = best_fit_decreasing_pool(current_right_indices, seq_lengths, pool_capacity) + + for pool_idx, pooled_right in enumerate(pools, start=1): + # Keep only pools that include at least one protein partner overall. + has_left_protein = types[left_i].lower() == "protein" + has_any_right_protein = any(types[r].lower() == "protein" for r in pooled_right) + if not (has_left_protein or has_any_right_protein): + continue + + left_chain_count = chain_count(types[left_i], seqs[left_i]) + right_chain_counts = [chain_count(types[r], seqs[r]) for r in pooled_right] + right_total_chain_count = sum(right_chain_counts) + + left_chain_indices = ",".join(str(idx) for idx in range(0, left_chain_count)) + right_chain_indices_int = ",".join( + str(idx) for idx in range(left_chain_count, left_chain_count + right_total_chain_count) + ) + left_chain_str_ids = ",".join(int_id_to_str_id(idx) for idx in range(0, left_chain_count)) + right_chain_str_ids = ",".join( + int_id_to_str_id(idx) for idx in range(left_chain_count, left_chain_count + right_total_chain_count) + ) + + interaction_id = f"{pool_group_1}-{pool_group_2}__{ids[left_i]}-pool{pool_idx:03d}" + mapping_file.write( + f"{interaction_id}\\t{left_chain_indices}:{right_chain_indices_int}\\t{left_chain_str_ids}:{right_chain_str_ids}\\n" + ) + + entities = [entity_to_fasta(types[left_i], seqs[left_i])] + entities.extend(entity_to_fasta(types[r], seqs[r]) for r in pooled_right) + target_interactions.write(f">{interaction_id}\\n{':'.join(entities)}\\n") + interactions_cntr += 1 + + if interactions_cntr == 0: + print("No interaction pools found!!") + exit(1) + + print(f"{interactions_cntr} Interaction pools found!!") + with open ("versions.yml", "w") as version_file: + version_file.write("\\"${task.process}\\":\\n python: {}\\n".format(sys.version.split()[0].strip())) + """ + + stub: + """ + touch interactions.fasta + touch interaction_mapping.tsv + + cat <<-END_VERSIONS > versions.yml + "${task.process}": + python: \$(python3 --version | sed 's/Python //g') + END_VERSIONS + """ +} diff --git a/nextflow.config b/nextflow.config index d73aa38..c508fdf 100644 --- a/nextflow.config +++ b/nextflow.config @@ -14,6 +14,8 @@ params { input = null mode = "all-all" interaction_neighbours = 0 + pool = false + pool_size = 2000 mmseqs_gpu = false use_gpu = true analysis_batch_size = 20 diff --git a/nextflow_schema.json b/nextflow_schema.json index fb4ddbc..fff75a4 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -61,6 +61,18 @@ "description": "Local neighbourhood to model in all-by-all mode", "fa_icon": "fas fa-microchip" }, + "pool": { + "type": "boolean", + "default": false, + "description": "Enable interaction pooling mode. When true, group pairs are read from --mode instead of standard interaction pairing.", + "fa_icon": "fas fa-layer-group" + }, + "pool_size": { + "type": "integer", + "default": 2000, + "description": "Maximum total sequence length per interaction pool (required when --pool is set).", + "fa_icon": "fas fa-ruler-horizontal" + }, "use_gpu": { "type": "boolean", "description": "Run on CPUs (default) or GPUs for the models", diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 212ed56..9bfb66d 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -36,6 +36,7 @@ include { COLABFOLD_BATCH } from '../modules/local/colabfold_batch' include { BOLTZ_FASTA } from '../modules/local/data_convertor/boltz_fasta' include { IPSAE } from '../modules/local/ipsae' include {CREATE_INTERACTIONS} from '../modules/local/data_convertor/create_interactions' +include {CREATE_INTERACTION_POOLS} from '../modules/local/data_convertor/create_interaction_pools' include { MMSEQS_COLABFOLDSEARCH } from '../modules/local/mmseqs_colabfoldsearch' // @@ -74,33 +75,61 @@ workflow WISPS { analysis_batch_size colabfold_batch_size interaction_neighbours + pool + pool_size main: ch_multiqc_files = Channel.empty() ch_confidence_scores = Channel.empty() - + use_interaction_pools = (pool instanceof Boolean) ? pool : pool.toString().toBoolean() interaction_mode = mode.split(",").collect { pair -> pair.split('-').sort().join('-') } if ("all-all" in interaction_mode) { interaction_mode = ["all-all"] - } else if (!("manual" in interaction_mode)) { - required = interaction_mode.collect{it.split("-")}.flatten().unique() + } + + if (use_interaction_pools) { + if ((pool_size as Integer) <= 0) { + error("When using --pool, --pool_size must be a positive integer. Received: ${pool_size}") + } + if ("manual" in interaction_mode || "all-all" in interaction_mode) { + error("When using --pool, --mode must be explicit group pairs (e.g. 'A-B' or 'A-A,A-B'). 'manual' and 'all-all' are not supported.") + } + + required_pool_groups = interaction_mode.collect{it.split("-")}.flatten().unique() ch_samplesheet .map{it[0].group} .unique() .toList() .subscribe{ emitted -> { - if (required - emitted){ - log.error "The groups ${required - emitted} is not in the sample sheet!" + if (required_pool_groups - emitted){ + log.error "The groups ${required_pool_groups - emitted} are not in the sample sheet!" exit 1 } } } + log.info "Using interaction pooling with modes: ${interaction_mode.join(',')} and max total sequence length ${pool_size}" + } else { + if (!("manual" in interaction_mode) && !("all-all" in interaction_mode)) { + required = interaction_mode.collect{it.split("-")}.flatten().unique() + ch_samplesheet + .map{it[0].group} + .unique() + .toList() + .subscribe{ + emitted -> { + if (required - emitted){ + log.error "The groups ${required - emitted} is not in the sample sheet!" + exit 1 + } + } + } + } + log.info "Used Interactions (Sorted): ${interaction_mode.join(',')}" } - log.info "Used Interactions (Sorted): ${interaction_mode.join(',')}" ch_samplesheet .multiMap{ @@ -121,7 +150,39 @@ workflow WISPS { ch_interaction_raw = Channel.empty() ch_interaction_info = Channel.empty() - if (!("manual" in interaction_mode)) { + if (use_interaction_pools) { + CREATE_INTERACTION_POOLS( + ch_raw_sample_sheet.ids.collect(), + ch_raw_sample_sheet.types.collect(), + ch_raw_sample_sheet.groups.collect(), + ch_raw_sample_sheet.seqs.collect(), + interaction_mode, + pool_size + ) + + ch_interaction_info = CREATE_INTERACTION_POOLS.out.interaction_mapping + .flatMap { mapping_tsv -> + def out = [] + def lines = mapping_tsv.readLines().findAll { it?.trim() } + if (lines.isEmpty()) { + throw new IllegalStateException("Invalid interaction mapping file ${mapping_tsv}: file is empty.") + } + + lines.drop(1).each { line -> + def cols = line.split("\t", -1) + if (cols.size() != 3) { + throw new IllegalStateException("Invalid interaction mapping row in ${mapping_tsv}: '${line}'") + } + def interaction_id = cols[0].trim() + def int_chain_map = cols[1].trim() + def str_chain_map = cols[2].trim() + out << [interaction_id, int_chain_map, str_chain_map] + } + out + } + + ch_interaction_raw = CREATE_INTERACTION_POOLS.out.interactions + } else if (!("manual" in interaction_mode)) { CREATE_INTERACTIONS( ch_raw_sample_sheet.ids.collect(), ch_raw_sample_sheet.types.collect(), From b602a2fdcad80ff72a72432efdc4a367faf5720c Mon Sep 17 00:00:00 2001 From: tlitfin Date: Wed, 15 Apr 2026 21:10:38 +1000 Subject: [PATCH 54/70] pool mode and reporting bugfixes --- bin/collect_confidence.py | 243 ++++++++++++++---- docs/output.md | 8 +- modules/local/colabfold_batch/main.nf | 4 +- .../create_interaction_pools.nf | 31 ++- modules/local/ipsae/main.nf | 2 - modules/local/mmseqs_colabfoldsearch/main.nf | 1 - workflows/wisps.nf | 194 +++++++------- 7 files changed, 321 insertions(+), 162 deletions(-) diff --git a/bin/collect_confidence.py b/bin/collect_confidence.py index 4494314..ab0022b 100755 --- a/bin/collect_confidence.py +++ b/bin/collect_confidence.py @@ -79,16 +79,66 @@ def build_sample_meta_by_id(sample_metadata): for item in sample_metadata: if isinstance(item, dict) and "id" in item: sample_id = str(item["id"]) - sample_meta_by_id[sample_id] = { + sample_meta_by_id.setdefault(sample_id, []).append({ + "id": sample_id, + "report_id": item.get("report_id", sample_id), "int_chain_map": item.get("int_chain_map", ""), "str_chain_map": item.get("str_chain_map", ""), - } + "left_source_id": item.get("left_source_id", ""), + "right_source_id": item.get("right_source_id", ""), + }) return sample_meta_by_id -def add_mapping_fields(row, sample_id, sample_meta_by_id): - meta = sample_meta_by_id.get(sample_id, {}) +def get_meta_entries(sample_id, sample_meta_by_id): + entries = sample_meta_by_id.get(sample_id, []) + if entries: + return entries + return [{ + "id": sample_id, + "report_id": sample_id, + "int_chain_map": "", + "str_chain_map": "", + "left_source_id": "", + "right_source_id": "", + }] + +def apply_mapping_fields(row, meta): + row["id"] = meta.get("report_id", row.get("id", "")) + row["model_input_id"] = meta.get("id", "") row["int_chain_map"] = meta.get("int_chain_map", "") row["str_chain_map"] = meta.get("str_chain_map", "") + row["left_source_id"] = meta.get("left_source_id", "") + row["right_source_id"] = meta.get("right_source_id", "") + +def is_empty_value(value): + if value is None: + return True + if isinstance(value, str): + return value.strip() == "" + return False + +def prune_empty_columns(rows, fieldnames): + retained = [] + for field in fieldnames: + if any(not is_empty_value(row.get(field)) for row in rows): + retained.append(field) + return retained + +def format_row_for_multiqc_csv(row, fieldnames): + """ + Emit deterministic table rows for MultiQC: + - no empty cells (use 'NA') + - avoid commas in chain-map display fields + """ + formatted = {} + for field in fieldnames: + value = row.get(field, "") + if is_empty_value(value): + value = "NA" + if field in {"int_chain_map", "str_chain_map"} and isinstance(value, str): + value = value.replace(",", ";") + formatted[field] = value + return formatted def parse_int_chain_map(int_chain_map): if not int_chain_map or ":" not in int_chain_map: @@ -143,18 +193,80 @@ def compute_max_cross_group_metric_from_groups(left_ids, right_ids, value_getter return max(values) if values else None +def compute_overall_max_pair_chains_iptm(pair_chains_iptm): + if not isinstance(pair_chains_iptm, dict): + return None + + values = [] + for left_id, right_map in pair_chains_iptm.items(): + if not isinstance(right_map, dict): + continue + for right_id, value in right_map.items(): + if str(left_id).strip() == str(right_id).strip(): + continue + if isinstance(value, (int, float)): + values.append(value) + + return max(values) if values else None + +def compute_overall_max_chain_pair_iptm(chain_pair_iptm): + if not isinstance(chain_pair_iptm, list): + return None + + values = [] + for i, row in enumerate(chain_pair_iptm): + if not isinstance(row, list): + continue + for j, value in enumerate(row): + if i == j: + continue + if isinstance(value, (int, float)): + values.append(value) + + return max(values) if values else None + +def split_pair_key(pair_key): + key = str(pair_key).strip() + if "-" in key: + parts = key.split("-", 1) + elif "_" in key: + parts = key.split("_", 1) + else: + return None, None + + if len(parts) != 2: + return None, None + return parts[0].strip(), parts[1].strip() + +def compute_overall_max_pairwise_iptm(pairwise_iptm): + if not isinstance(pairwise_iptm, dict): + return None + + values = [] + for pair_key, value in pairwise_iptm.items(): + left_id, right_id = split_pair_key(pair_key) + if left_id is not None and right_id is not None and left_id == right_id: + continue + if isinstance(value, (int, float)): + values.append(value) + + return max(values) if values else None + def compute_max_cross_group_pair_chains_iptm(pair_chains_iptm, int_chain_map): if not isinstance(pair_chains_iptm, dict): return None + overall_max = compute_overall_max_pair_chains_iptm(pair_chains_iptm) def get_dict_value(i, j): return pair_chains_iptm.get(str(i), {}).get(str(j)) - return compute_max_cross_group_metric(int_chain_map, get_dict_value) + cross_group_max = compute_max_cross_group_metric(int_chain_map, get_dict_value) + return cross_group_max if cross_group_max is not None else overall_max def compute_max_cross_group_chain_pair_iptm(chain_pair_iptm, int_chain_map): if not isinstance(chain_pair_iptm, list): return None + overall_max = compute_overall_max_chain_pair_iptm(chain_pair_iptm) def get_list_value(i, j): if 0 <= i < len(chain_pair_iptm) and isinstance(chain_pair_iptm[i], list): @@ -162,23 +274,26 @@ def get_list_value(i, j): return chain_pair_iptm[i][j] return None - return compute_max_cross_group_metric(int_chain_map, get_list_value) + cross_group_max = compute_max_cross_group_metric(int_chain_map, get_list_value) + return cross_group_max if cross_group_max is not None else overall_max def compute_max_cross_group_pairwise_iptm(pairwise_iptm, str_chain_map): if not isinstance(pairwise_iptm, dict): return None + overall_max = compute_overall_max_pairwise_iptm(pairwise_iptm) left_ids, right_ids = parse_str_chain_map(str_chain_map) def get_pairwise_value(i, j): return pairwise_iptm.get(f"{i}-{j}") - return compute_max_cross_group_metric_from_groups(left_ids, right_ids, get_pairwise_value) + cross_group_max = compute_max_cross_group_metric_from_groups(left_ids, right_ids, get_pairwise_value) + return cross_group_max if cross_group_max is not None else overall_max def extract_boltz_results(json_files, output_csv, sample_meta_by_id): rows_by_id = {} all_keys = ["confidence_score", "ptm", "iptm", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde", "chains_ptm"] - writing_keys = ["id", "iptm", "ptm", "int_chain_map", "str_chain_map", "max_cross_group_pair_chains_iptm", "confidence_score", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde"] + writing_keys = ["id", "model_input_id", "left_source_id", "right_source_id", "iptm", "ptm", "int_chain_map", "str_chain_map", "max_cross_group_pair_chains_iptm", "confidence_score", "ligand_iptm", "protein_iptm", "complex_plddt", "complex_iplddt", "complex_pde", "complex_ipde"] writing_keys_extra = set() for file in json_files: @@ -194,11 +309,7 @@ def extract_boltz_results(json_files, output_csv, sample_meta_by_id): flat_data = rows_by_id[sample_id] if record_type == "confidence": - int_chain_map = sample_meta_by_id.get(sample_id, {}).get("int_chain_map", "") - flat_data["max_cross_group_pair_chains_iptm"] = compute_max_cross_group_pair_chains_iptm( - data.get("pair_chains_iptm"), - int_chain_map - ) + flat_data["_pair_chains_iptm"] = data.get("pair_chains_iptm") for key, value in data.items(): if key not in all_keys: continue @@ -225,16 +336,31 @@ def extract_boltz_results(json_files, output_csv, sample_meta_by_id): flat_data[key_name] = value writing_keys_extra.add(key_name) - # Write to CSV + # Prepare output rows and prune columns with no data final_writing_vals = writing_keys + sorted(writing_keys_extra - set(writing_keys)) + output_rows = [] + + for sample_id in sorted(rows_by_id.keys()): + base_row = rows_by_id[sample_id] + for meta in get_meta_entries(sample_id, sample_meta_by_id): + row = dict(base_row) + apply_mapping_fields(row, meta) + row["max_cross_group_pair_chains_iptm"] = compute_max_cross_group_pair_chains_iptm( + row.get("_pair_chains_iptm"), + row.get("int_chain_map", "") + ) + output_rows.append({key: row.get(key, "") for key in final_writing_vals}) + + final_writing_vals = prune_empty_columns( + output_rows, + final_writing_vals + ) with open(output_csv, "w", newline="") as f: writer = csv.DictWriter(f, fieldnames=final_writing_vals) writer.writeheader() - for sample_id in sorted(rows_by_id.keys()): - row = rows_by_id[sample_id] - add_mapping_fields(row, sample_id, sample_meta_by_id) - writer.writerow({key: row.get(key, "") for key in final_writing_vals}) + for row in output_rows: + writer.writerow(format_row_for_multiqc_csv(row, final_writing_vals)) def extract_colabfold_results(json_files, samples, output_csv, sample_meta_by_id): def parse_colabfold_metrics(json_file): @@ -242,7 +368,7 @@ def parse_colabfold_metrics(json_file): data = json.load(f) result = {} - for key in ["iptm", "max_pae", "pae", "ptm", "plddt", "pairwise_iptm"]: + for key in ["iptm", "pae", "ptm", "plddt", "pairwise_iptm"]: if key not in data: result[key] = None continue @@ -257,63 +383,80 @@ def parse_colabfold_metrics(json_file): return result rows = [] - all_keys = ["id", "ptm", "iptm", "int_chain_map", "str_chain_map", "max_cross_group_pairwise_iptm", "plddt", "max_pae"] + all_keys = ["id", "model_input_id", "left_source_id", "right_source_id", "ptm", "iptm", "int_chain_map", "str_chain_map", "max_cross_group_pairwise_iptm", "plddt"] writing_keys = all_keys cntr = 0 for file in json_files: - flat_data = parse_colabfold_metrics(file) - flat_data["id"] = samples[cntr] - add_mapping_fields(flat_data, flat_data["id"], sample_meta_by_id) - flat_data["max_cross_group_pairwise_iptm"] = compute_max_cross_group_pairwise_iptm( - flat_data.get("pairwise_iptm"), - flat_data.get("str_chain_map", "") - ) + sample_id = samples[cntr] + base_data = parse_colabfold_metrics(file) + base_data["id"] = sample_id cntr += 1 - rows.append(flat_data) + for meta in get_meta_entries(sample_id, sample_meta_by_id): + flat_data = dict(base_data) + apply_mapping_fields(flat_data, meta) + flat_data["max_cross_group_pairwise_iptm"] = compute_max_cross_group_pairwise_iptm( + flat_data.get("pairwise_iptm"), + flat_data.get("str_chain_map", "") + ) + rows.append(flat_data) + + # Prune columns with no data across all rows + writing_keys = prune_empty_columns( + rows, + writing_keys + ) # Write to CSV with open(output_csv, "w", newline="") as f: writer = csv.DictWriter(f, fieldnames=writing_keys) writer.writeheader() for row in rows: - writer.writerow({key: row.get(key, "") for key in writing_keys}) + writer.writerow(format_row_for_multiqc_csv(row, writing_keys)) def extract_alphafold3_results(json_files, samples, output_csv, sample_meta_by_id): rows = [] all_keys = ["chain_iptm","chain_pair_iptm", "chain_pair_pae_min", "ptm", "iptm", "chain_ptm", "fraction_disordered", "has_clash", "ranking_score"] - writing_keys = ["id", "ptm", "iptm", "int_chain_map", "str_chain_map", "max_cross_group_chain_pair_iptm", "fraction_disordered", "has_clash", "ranking_score"] + writing_keys = ["id", "model_input_id", "left_source_id", "right_source_id", "ptm", "iptm", "int_chain_map", "str_chain_map", "max_cross_group_chain_pair_iptm", "fraction_disordered", "has_clash", "ranking_score"] writing_keys_extra = set() # First pass: read and collect keys cntr = 0 for file in json_files: with open(file) as f: data = json.load(f) - flat_data = {"id": samples[cntr]} - add_mapping_fields(flat_data, flat_data["id"], sample_meta_by_id) - flat_data["max_cross_group_chain_pair_iptm"] = compute_max_cross_group_chain_pair_iptm( - data.get("chain_pair_iptm"), - flat_data.get("int_chain_map", "") - ) + sample_id = samples[cntr] cntr += 1 - for key, value in data.items(): - if key not in all_keys: - continue - if isinstance(value, dict) or isinstance(value, list): - sub_data = flatten_deep(value, index_lists=True) - for sub_key, sub_value in sub_data.items(): - flat_data[f"{key}_{sub_key}"] = sub_value - writing_keys_extra.add(f"{key}_{sub_key}") - else: - flat_data[key] = value - rows.append(flat_data) + for meta in get_meta_entries(sample_id, sample_meta_by_id): + flat_data = {"id": sample_id} + apply_mapping_fields(flat_data, meta) + flat_data["max_cross_group_chain_pair_iptm"] = compute_max_cross_group_chain_pair_iptm( + data.get("chain_pair_iptm"), + flat_data.get("int_chain_map", "") + ) + for key, value in data.items(): + if key not in all_keys: + continue + if isinstance(value, dict) or isinstance(value, list): + sub_data = flatten_deep(value, index_lists=True) + for sub_key, sub_value in sub_data.items(): + flat_data[f"{key}_{sub_key}"] = sub_value + writing_keys_extra.add(f"{key}_{sub_key}") + else: + flat_data[key] = value + rows.append(flat_data) - # Write to CSV + # Prune columns with no data across all rows final_writing_vals = writing_keys + sorted(writing_keys_extra) + final_writing_vals = prune_empty_columns( + rows, + final_writing_vals, + ) + + # Write to CSV with open(output_csv, "w", newline="") as f: writer = csv.DictWriter(f, fieldnames=final_writing_vals) writer.writeheader() for row in rows: - writer.writerow({key: row.get(key, "") for key in final_writing_vals}) + writer.writerow(format_row_for_multiqc_csv(row, final_writing_vals)) @@ -322,7 +465,7 @@ def main(): parser.add_argument("-i", "--input", help="Path to input directory containing all json files") parser.add_argument("-o", "--output", default="output_msa", help="output CSV file") parser.add_argument("--model", default="boltz", help="model generating the input files can be one of [boltz, alphafold3, and colabfold]") - parser.add_argument("--sample-metadata", default=None, help="JSON file with list of sample metadata maps including id/int_chain_map/str_chain_map") + parser.add_argument("--sample-metadata", default=None, help="JSON file with list of sample metadata maps including id/report_id/int_chain_map/str_chain_map") args = parser.parse_args() json_files = [str(f) for f in Path(args.input).glob("*.json") if f.is_file()] diff --git a/docs/output.md b/docs/output.md index b5b9512..316461b 100644 --- a/docs/output.md +++ b/docs/output.md @@ -43,13 +43,10 @@ These files are generated once from the interaction FASTA and reused by downstre - `run/` (outputs from both Boltz and AlphaFold3 modules) - Boltz: - - `boltz_results_*/predictions/*/*.cif` and optional `*.pdb`: predicted structures. + - `boltz_results_*/predictions/*/*.cif`: predicted structures. - `boltz_results_*/predictions/*/confidence_*.json`: confidence metrics. - `boltz_results_*/predictions/*/affinity_*.json`: affinity predictions (if produced). - `boltz_results_*/predictions/*/pae_*.npz`: PAE matrices. - - `boltz_results_*/predictions/*/plddt_*.npz`: per-residue confidence arrays. - - `boltz_results_*/processed/structures/*.npz`: processed structure arrays. - - `boltz_results_*/processed/msa/*.npz`: processed MSA arrays. - AlphaFold3: - `out/*/*_model.cif`: top-ranked model structures. - `out/*/*_confidences.json`: detailed confidence output. @@ -57,7 +54,6 @@ These files are generated once from the interaction FASTA and reused by downstre - `colabfold/` - `*_relaxed_rank_001_*_model_*.pdb`: relaxed top-ranked ColabFold structures. - `*_scores_rank_001_*.json`: model score summaries. - - `*_coverage.png`: MSA coverage plots.
    @@ -67,7 +63,7 @@ These files are generated once from the interaction FASTA and reused by downstre Output files - `ipsae/` - - `*.pml`, `*_byres.txt`, `*.txt`: IPSAE per-structure analysis outputs. + - `data/*.txt`: IPSAE per-structure analysis outputs. - `ipsae_scores.csv`: per-interaction summary table with maximum cross-group IPSAE scores by model. - `ipsae_scores_.csv`: per-chain-pair IPSAE tables across all interactions. - `collect/` diff --git a/modules/local/colabfold_batch/main.nf b/modules/local/colabfold_batch/main.nf index 9284f42..c45edd0 100644 --- a/modules/local/colabfold_batch/main.nf +++ b/modules/local/colabfold_batch/main.nf @@ -13,7 +13,7 @@ process COLABFOLD_BATCH { output: tuple val(meta), path ("*relaxed_rank_001_*_model_*.pdb") , emit: pdb - tuple val(meta), path ("*_coverage.png") , emit: msa + //tuple val(meta), path ("*_coverage.png") , emit: msa tuple val(meta), path ("*_scores_rank_001_*.json") , emit: top_ranked_scores path "versions.yml" , emit: versions @@ -44,6 +44,7 @@ process COLABFOLD_BATCH { cat <<-END_VERSIONS > versions.yml "${task.process}": colabfold_batch: \$(pip list | grep "^colabfold" | awk '{print \$2}') + alphafold_colabfold: \$(pip list | grep "^alphafold-colabfold" | awk '{print \$2}') END_VERSIONS """ @@ -63,6 +64,7 @@ process COLABFOLD_BATCH { cat <<-END_VERSIONS > versions.yml "${task.process}": colabfold_batch: \$(pip list | grep "^colabfold" | awk '{print \$2}') + alphafold_colabfold: \$(pip list | grep "^alphafold-colabfold" | awk '{print \$2}') END_VERSIONS """ } diff --git a/modules/local/data_convertor/create_interaction_pools.nf b/modules/local/data_convertor/create_interaction_pools.nf index 6e10a12..f28f635 100644 --- a/modules/local/data_convertor/create_interaction_pools.nf +++ b/modules/local/data_convertor/create_interaction_pools.nf @@ -147,7 +147,7 @@ process CREATE_INTERACTION_POOLS { seq_lengths = [sequence_length(types[i], seqs[i]) for i in range(n)] with open("interactions.fasta", "w") as target_interactions, open("interaction_mapping.tsv", "w") as mapping_file: - mapping_file.write("interaction_id\\tint_chain_map\\tstr_chain_map\\n") + mapping_file.write("interaction_id\\tint_chain_map\\tstr_chain_map\\treport_id\\tleft_source_id\\tright_source_id\\n") for pool_group_1, pool_group_2 in pool_pairs: left_indices = [i for i in range(n) if groups[i] == pool_group_1] @@ -184,27 +184,36 @@ process CREATE_INTERACTION_POOLS { left_chain_count = chain_count(types[left_i], seqs[left_i]) right_chain_counts = [chain_count(types[r], seqs[r]) for r in pooled_right] - right_total_chain_count = sum(right_chain_counts) left_chain_indices = ",".join(str(idx) for idx in range(0, left_chain_count)) - right_chain_indices_int = ",".join( - str(idx) for idx in range(left_chain_count, left_chain_count + right_total_chain_count) - ) left_chain_str_ids = ",".join(int_id_to_str_id(idx) for idx in range(0, left_chain_count)) - right_chain_str_ids = ",".join( - int_id_to_str_id(idx) for idx in range(left_chain_count, left_chain_count + right_total_chain_count) - ) interaction_id = f"{pool_group_1}-{pool_group_2}__{ids[left_i]}-pool{pool_idx:03d}" - mapping_file.write( - f"{interaction_id}\\t{left_chain_indices}:{right_chain_indices_int}\\t{left_chain_str_ids}:{right_chain_str_ids}\\n" - ) entities = [entity_to_fasta(types[left_i], seqs[left_i])] entities.extend(entity_to_fasta(types[r], seqs[r]) for r in pooled_right) target_interactions.write(f">{interaction_id}\\n{':'.join(entities)}\\n") interactions_cntr += 1 + # Emit one mapping row per original cross-group pair in this pool. + right_start = left_chain_count + for ridx, right_i in enumerate(pooled_right): + right_count = right_chain_counts[ridx] + right_indices_pair = ",".join( + str(idx) for idx in range(right_start, right_start + right_count) + ) + right_str_ids_pair = ",".join( + int_id_to_str_id(idx) for idx in range(right_start, right_start + right_count) + ) + report_id = f"{ids[left_i]}-{ids[right_i]}" + mapping_file.write( + f"{interaction_id}\\t" + f"{left_chain_indices}:{right_indices_pair}\\t" + f"{left_chain_str_ids}:{right_str_ids_pair}\\t" + f"{report_id}\\t{ids[left_i]}\\t{ids[right_i]}\\n" + ) + right_start += right_count + if interactions_cntr == 0: print("No interaction pools found!!") exit(1) diff --git a/modules/local/ipsae/main.nf b/modules/local/ipsae/main.nf index 8973233..a707de3 100644 --- a/modules/local/ipsae/main.nf +++ b/modules/local/ipsae/main.nf @@ -12,8 +12,6 @@ process IPSAE { path ("data/") output: - tuple val(meta), path ("data/*.pml"), emit: pml - tuple val(meta), path ("data/*_byres.txt"), emit: byres tuple val(meta), path ("data/*[0-9].txt"), emit: txt path "versions.yml" , emit: versions diff --git a/modules/local/mmseqs_colabfoldsearch/main.nf b/modules/local/mmseqs_colabfoldsearch/main.nf index ebec523..2233898 100644 --- a/modules/local/mmseqs_colabfoldsearch/main.nf +++ b/modules/local/mmseqs_colabfoldsearch/main.nf @@ -37,7 +37,6 @@ process MMSEQS_COLABFOLDSEARCH { cat <<-END_VERSIONS > versions.yml "${task.process}": colabfold_search: \$(pip list | grep "^colabfold" | awk '{print \$2}') - alphafold_colabfold: \$(pip list | grep "^alphafold-colabfold" | awk '{print \$2}') mmseqs: \$(mmseqs version) END_VERSIONS """ diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 9bfb66d..7ccfc6b 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -18,7 +18,9 @@ // MODULE: Installed directly from nf-core/modules // include { MULTIQC } from '../modules/nf-core/multiqc/main' -include { COLLECT_CONFIDENCE } from '../modules/local/collect_confidence' +include { COLLECT_CONFIDENCE as COLLECT_CONFIDENCE_BOLTZ } from '../modules/local/collect_confidence' +include { COLLECT_CONFIDENCE as COLLECT_CONFIDENCE_COLABFOLD } from '../modules/local/collect_confidence' +include { COLLECT_CONFIDENCE as COLLECT_CONFIDENCE_AF3 } from '../modules/local/collect_confidence' // // SUBWORKFLOW: Consisting entirely of nf-core/modules // @@ -170,13 +172,16 @@ workflow WISPS { lines.drop(1).each { line -> def cols = line.split("\t", -1) - if (cols.size() != 3) { + if (cols.size() < 3) { throw new IllegalStateException("Invalid interaction mapping row in ${mapping_tsv}: '${line}'") } def interaction_id = cols[0].trim() def int_chain_map = cols[1].trim() def str_chain_map = cols[2].trim() - out << [interaction_id, int_chain_map, str_chain_map] + def report_id = cols.size() > 3 && cols[3].trim() ? cols[3].trim() : interaction_id + def left_source_id = cols.size() > 4 ? cols[4].trim() : "" + def right_source_id = cols.size() > 5 ? cols[5].trim() : "" + out << [interaction_id, int_chain_map, str_chain_map, report_id, left_source_id, right_source_id] } out } @@ -208,7 +213,7 @@ workflow WISPS { def interaction_id = cols[0].trim() def int_chain_map = cols[1].trim() def str_chain_map = cols[2].trim() - out << [interaction_id, int_chain_map, str_chain_map] + out << [interaction_id, int_chain_map, str_chain_map, interaction_id, "", ""] } out } @@ -247,22 +252,28 @@ workflow WISPS { if ("manual" in interaction_mode) { ch_interaction_info = ch_interaction_has_protein - .map { interaction_id, _ -> [interaction_id, "", ""] } + .map { interaction_id, _ -> [interaction_id, "", "", interaction_id, "", ""] } } - ch_interaction_has_protein - .join(ch_interaction_info) - .map { interaction_id, has_protein, int_chain_map, str_chain_map -> - [ - [ + ch_interaction_has_protein_map = ch_interaction_has_protein + .collect(flat: false) + .map { rows -> + rows.collectEntries { row -> [(row[0]): row[1]] } + } + + ch_interaction_in = ch_interaction_info + .combine(ch_interaction_has_protein_map) + .map { interaction_id, int_chain_map, str_chain_map, report_id, left_source_id, right_source_id, has_protein_map -> + def has_protein = has_protein_map.containsKey(interaction_id) ? has_protein_map[interaction_id] : false + [[ "id": interaction_id, + "report_id": report_id, "int_chain_map": int_chain_map, - "str_chain_map": str_chain_map - ], - has_protein - ] - } - .set{ch_interaction_in} + "str_chain_map": str_chain_map, + "left_source_id": left_source_id, + "right_source_id": right_source_id + ], has_protein] + } ch_interaction_in.count().subscribe{print("total final: ${it}")} @@ -436,9 +447,9 @@ workflow WISPS { ipsae_batch = 0 - ch_protein_interaction_by_id = ch_interaction_in + ch_protein_interaction_by_id = ch_interaction_has_protein .filter { it[1] } - .map { [it[0].id, it[0]] } + .map { [it[0], true] } ch_colabfold_scores .join(ch_colabfold_pdb) @@ -567,6 +578,11 @@ workflow WISPS { .findAll { it in ['boltz','colabfold','alphafold3'] } // 1) Long format: [sample_id, pair_id, model, score] + ch_report_meta_grouped_by_input_id = ch_interaction_in + .map { [it[0].id, it[0]] } + .groupTuple() + .map { inputId, metas -> [inputId, metas] } + ch_long = Channel.empty() if ('boltz' in active_modes) ch_long = ch_long.mix(ch_ipsae_out.boltz.flatMap { id, entries -> entries.collect { e -> [id, e[0], 'boltz', e[1]] } }) @@ -574,6 +590,17 @@ workflow WISPS { ch_long = ch_long.mix(ch_ipsae_out.colabfold.flatMap { id, entries -> entries.collect { e -> [id, e[0], 'colabfold', e[1]] } }) if ('alphafold3' in active_modes) ch_long = ch_long.mix(ch_ipsae_out.alphafold3.flatMap { id, entries -> entries.collect { e -> [id, e[0], 'alphafold3', e[1]] } }) + ch_long = ch_long + .join(ch_report_meta_grouped_by_input_id, remainder: true) + .flatMap { inputId, pairId, model, score, metaList -> + def metas = (metaList instanceof List && !metaList.isEmpty()) + ? metaList + : [[report_id: inputId, str_chain_map: ""]] + metas.collect { interaction_meta -> + def reportId = interaction_meta?.report_id ?: inputId + [reportId, pairId, model, score] + } + } // 2) Pivot per pair: [pair_id, sampleModelScoreMap] ch_pair_wide = ch_long @@ -588,7 +615,7 @@ workflow WISPS { } // 3) Create one CSV per pair with model-only headers - ch_interaction_in.map { it[0].id }.unique().toSortedList().map { [sample_ids: it] } + ch_interaction_in.map { it[0].report_id }.unique().toSortedList().map { [sample_ids: it] } .combine(ch_pair_wide.collect(flat: false).map { [pairs: it] }) .flatMap { left, right -> def ids = left.sample_ids @@ -613,27 +640,26 @@ workflow WISPS { .set { ch_ipsae_scores_by_pair } // 4) Additional summary file: max cross-group (left/right in str_chain_map) IPSAE per sample/model - ch_str_chain_map_by_id = ch_interaction_in.map { [it[0].id, it[0].str_chain_map] } - - ch_model_rows = ch_ipsae_out.boltz - .join(ch_str_chain_map_by_id, remainder: true) - .map { sampleId, entries, strChainMap -> - [[sampleId, "boltz"], computeMaxCrossGroupIpsae(entries, strChainMap)] + ch_ipsae_entries = Channel.empty() + if ('boltz' in active_modes) + ch_ipsae_entries = ch_ipsae_entries.mix(ch_ipsae_out.boltz.map { inputId, entries -> [inputId, "boltz", entries] }) + if ('colabfold' in active_modes) + ch_ipsae_entries = ch_ipsae_entries.mix(ch_ipsae_out.colabfold.map { inputId, entries -> [inputId, "colabfold", entries] }) + if ('alphafold3' in active_modes) + ch_ipsae_entries = ch_ipsae_entries.mix(ch_ipsae_out.alphafold3.map { inputId, entries -> [inputId, "alphafold3", entries] }) + + ch_model_rows = ch_ipsae_entries + .combine(ch_report_meta_grouped_by_input_id, by: 0) + .flatMap { inputId, model, entries, metaList -> + def metas = (metaList instanceof List && !metaList.isEmpty()) + ? metaList + : [[report_id: inputId, str_chain_map: ""]] + metas.collect { interaction_meta -> + def reportId = interaction_meta?.report_id ?: inputId + def strChainMap = interaction_meta?.str_chain_map ?: "" + [[reportId, model], computeMaxCrossGroupIpsae(entries, strChainMap)] + } } - .mix( - ch_ipsae_out.colabfold - .join(ch_str_chain_map_by_id, remainder: true) - .map { sampleId, entries, strChainMap -> - [[sampleId, "colabfold"], computeMaxCrossGroupIpsae(entries, strChainMap)] - } - ) - .mix( - ch_ipsae_out.alphafold3 - .join(ch_str_chain_map_by_id, remainder: true) - .map { sampleId, entries, strChainMap -> - [[sampleId, "alphafold3"], computeMaxCrossGroupIpsae(entries, strChainMap)] - } - ) ch_model_wide = ch_model_rows .groupTuple() @@ -645,7 +671,7 @@ workflow WISPS { } def summary_header = "Sample," + active_modes.join(",") + "\n" - ch_interaction_in.map { it[0].id }.unique().map { [it, true] } + ch_interaction_in.map { it[0].report_id }.unique().map { [it, true] } .join(ch_model_wide, remainder: true) .map { id, _, m -> def mm = m ?: [:] @@ -663,59 +689,45 @@ workflow WISPS { ch_ipsae_scores = ch_ipsae_scores_by_pair.mix(ch_ipsae_scores_max) - ch_interaction_meta_by_id = ch_interaction_in - .map { [it[0].id, it[0]] } + ch_confidence_meta = ch_interaction_in + .map { it[0] } + .unique { it.report_id ?: "${it.id}:${it.int_chain_map}:${it.str_chain_map}" } + .collect(flat: false, sort: true) - ch_boltz_confidence_with_meta = ch_boltz_confidence - .map { [it[0].id, it[1]] } - .join(ch_interaction_meta_by_id) - .map { id, json_file, interaction_meta -> [interaction_meta, json_file] } - - ch_boltz_affinity_with_meta = ch_boltz_affinity - .map { [it[0].id, it[1]] } - .join(ch_interaction_meta_by_id) - .map { id, json_file, interaction_meta -> [interaction_meta, json_file] } - - ch_boltz_confidence_with_meta - .mix(ch_boltz_affinity_with_meta) - .collect(flat: false, sort: true).multiMap{json_list -> - ids: json_list.collect{it[0]}.unique{it.id} - json: json_list.collect{it[1]} - }.set{ch_boltz_confidence_scores} - - ch_alphafold3_summary_confidences - .map { [it[0].id, it[1]] } - .join(ch_interaction_meta_by_id) - .map { id, json_file, interaction_meta -> [interaction_meta, json_file] } - .collect(flat: false, sort: true).multiMap{json_list -> - ids: json_list.collect{it[0]}.unique{it.id} - json: json_list.collect{it[1]} - }.set{ch_alphafold3_confidence_scores} + ch_boltz_confidence_json = ch_boltz_confidence + .map { it[1] } + .mix(ch_boltz_affinity.map { it[1] }) + .collect(flat: false, sort: true) - ch_colabfold_scores - .map { [it[0].id, it[1]] } - .join(ch_interaction_meta_by_id) - .map { id, json_file, interaction_meta -> [interaction_meta, json_file] } - .collect(flat: false, sort: true).multiMap{json_list -> - ids: json_list.collect{it[0]}.unique{it.id} - json: json_list.collect{it[1]} - }.set{ch_colabfold_confidence_scores} - - - COLLECT_CONFIDENCE( - ch_boltz_confidence_scores.ids - .map{[["id": "all-boltz", "model": "boltz"], it]} - .mix(ch_colabfold_confidence_scores.ids - .map{[["id": "all-colabfold", "model": "colabfold"], it]} - ) - .mix(ch_alphafold3_confidence_scores.ids - .map{[["id": "all-alphafold3", "model": "alphafold3"], it]} - ), - ch_boltz_confidence_scores.json - .mix(ch_colabfold_confidence_scores.json) - .mix(ch_alphafold3_confidence_scores.json) + ch_alphafold3_confidence_json = ch_alphafold3_summary_confidences + .map { it[1] } + .collect(flat: false, sort: true) + + ch_colabfold_confidence_json = ch_colabfold_scores + .map { it[1] } + .collect(flat: false, sort: true) + + + COLLECT_CONFIDENCE_BOLTZ( + ch_confidence_meta.map{[["id": "all-boltz", "model": "boltz"], it]}, + ch_boltz_confidence_json + ) + ch_versions = ch_versions.mix(COLLECT_CONFIDENCE_BOLTZ.out.versions) + ch_confidence_scores_all = COLLECT_CONFIDENCE_BOLTZ.out.confidence + + COLLECT_CONFIDENCE_COLABFOLD( + ch_confidence_meta.map{[["id": "all-colabfold", "model": "colabfold"], it]}, + ch_colabfold_confidence_json + ) + ch_versions = ch_versions.mix(COLLECT_CONFIDENCE_COLABFOLD.out.versions) + ch_confidence_scores_all = ch_confidence_scores_all.mix(COLLECT_CONFIDENCE_COLABFOLD.out.confidence) + + COLLECT_CONFIDENCE_AF3( + ch_confidence_meta.map{[["id": "all-alphafold3", "model": "alphafold3"], it]}, + ch_alphafold3_confidence_json ) - ch_versions = ch_versions.mix(COLLECT_CONFIDENCE.out.versions) + ch_versions = ch_versions.mix(COLLECT_CONFIDENCE_AF3.out.versions) + ch_confidence_scores_all = ch_confidence_scores_all.mix(COLLECT_CONFIDENCE_AF3.out.confidence) @@ -742,7 +754,7 @@ workflow WISPS { ch_multiqc_files = ch_multiqc_files.mix(ch_methods_description.collectFile(name: 'methods_description_mqc.yaml')) ch_multiqc_files = ch_multiqc_files.mix(ch_collated_versions) ch_multiqc_files = ch_multiqc_files - .mix(COLLECT_CONFIDENCE.out.confidence.map{it[1]}) + .mix(ch_confidence_scores_all.map{it[1]}) .mix(ch_ipsae_scores) MULTIQC ( ch_multiqc_files.collect(sort: true), From 057324070566fa979cf5e88b8b77dffba100fdf1 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Tue, 21 Apr 2026 09:11:05 +1000 Subject: [PATCH 55/70] avoid pae in colabfold collect confidence --- bin/collect_confidence.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/bin/collect_confidence.py b/bin/collect_confidence.py index ab0022b..ecb4e21 100755 --- a/bin/collect_confidence.py +++ b/bin/collect_confidence.py @@ -368,7 +368,7 @@ def parse_colabfold_metrics(json_file): data = json.load(f) result = {} - for key in ["iptm", "pae", "ptm", "plddt", "pairwise_iptm"]: + for key in ["iptm", "ptm", "plddt", "pairwise_iptm"]: if key not in data: result[key] = None continue From e5f729bf060f8372af3005edebbb00281c327c4d Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Tue, 21 Apr 2026 11:19:22 +1000 Subject: [PATCH 56/70] update --- conf/gadi.config | 28 +++++++++++++++++++++------- conf/modules.config | 4 ++-- 2 files changed, 23 insertions(+), 9 deletions(-) diff --git a/conf/gadi.config b/conf/gadi.config index 5a81ee6..fc2ff7a 100644 --- a/conf/gadi.config +++ b/conf/gadi.config @@ -48,24 +48,38 @@ process { storage = "gdata/li87+gdata/if89+scratch/${params.project}+gdata/${params.project}" withName: 'MMSEQS_COLABFOLDSEARCH' { - memory = 300.GB - time = 24.h - cpus = 24 + memory = 350.GB + time = 48.h + cpus = 16 } + withName: 'RUN_BOLTZ' { - queue = "gpuvolta" + if (params.use_dgxa100){ + queue = "dgxa100" + cpus = 16 + }else{ + queue = "gpuvolta" + cpus = 12 + } time = 48.h memory = 128.GB - cpus = 12 gpus = 1 } + withName: 'COLABFOLD_BATCH' { - queue = "gpuvolta" + if (params.use_dgxa100){ + queue = "dgxa100" + cpus = 16 + }else{ + queue = "gpuvolta" + cpus = 12 + } time = 16.h memory = 128.GB - cpus = 12 + gpus = 1 } + resourceLimits = [ cpus: 1000, memory: '2000.GB', diff --git a/conf/modules.config b/conf/modules.config index f9953fa..028c3f0 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -58,8 +58,8 @@ process { } withName: 'RUN_BOLTZ' { - cpus = 12 - time = 24.h + cpus = 16 + time = 48.h memory = 128.GB ext.args = "--write_full_pae --output_format mmcif" } From c4e02adc3a84c751e112f466881f77341766321a Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Fri, 24 Apr 2026 10:54:40 +1000 Subject: [PATCH 57/70] cleaning --- .github/CONTRIBUTING.md | 125 ------------ .github/ISSUE_TEMPLATE/bug_report.yml | 7 +- .github/ISSUE_TEMPLATE/config.yml | 2 +- .github/ISSUE_TEMPLATE/feature_request.yml | 2 +- .github/PULL_REQUEST_TEMPLATE.md | 9 +- .github/workflows/awsfulltest.yml | 2 +- .github/workflows/awstest.yml | 2 +- .github/workflows/branch.yml | 4 +- .github/workflows/ci.yml | 2 +- .github/workflows/fix-linting.yml | 4 +- .nf-core.yml | 23 --- CHANGELOG.md | 6 +- CITATIONS.md | 2 +- CODE_OF_CONDUCT.md | 182 ------------------ README.md | 39 +--- assets/adaptivecard.json | 2 +- assets/email_template.html | 14 +- assets/email_template.txt | 15 +- assets/methods_description_template.yml | 6 +- assets/multiqc_config.yml | 2 +- assets/schema_input.json | 4 +- assets/slackreport.json | 2 +- conf/base.config | 2 +- conf/gadi.config | 99 ---------- conf/test.config | 2 +- conf/test_full.config | 2 +- conf/test_gadi.config | 92 --------- docs/README.md | 5 +- docs/output.md | 2 +- docs/usage.md | 62 ++---- main.nf | 14 +- modules.json | 4 +- modules/local/run_boltz/Dockerfile | 27 +-- modules/local/run_boltz/main.nf | 2 +- nextflow.config | 16 +- nextflow_schema.json | 4 +- .../local/utils_nfcore_wisps_pipeline/main.nf | 2 +- 37 files changed, 100 insertions(+), 691 deletions(-) delete mode 100644 .github/CONTRIBUTING.md delete mode 100644 .nf-core.yml delete mode 100644 CODE_OF_CONDUCT.md delete mode 100644 conf/gadi.config delete mode 100644 conf/test_gadi.config diff --git a/.github/CONTRIBUTING.md b/.github/CONTRIBUTING.md deleted file mode 100644 index 8cbfea7..0000000 --- a/.github/CONTRIBUTING.md +++ /dev/null @@ -1,125 +0,0 @@ -# nf-core/wisps: Contributing Guidelines - -Hi there! -Many thanks for taking an interest in improving nf-core/wisps. - -We try to manage the required tasks for nf-core/wisps using GitHub issues, you probably came to this page when creating one. -Please use the pre-filled template to save time. - -However, don't be put off by this template - other more general issues and suggestions are welcome! -Contributions to the code are even more welcome ;) - -> [!NOTE] -> If you need help using or modifying nf-core/wisps then the best place to ask is on the nf-core Slack [#wisps](https://nfcore.slack.com/channels/wisps) channel ([join our Slack here](https://nf-co.re/join/slack)). - -## Contribution workflow - -If you'd like to write some code for nf-core/wisps, the standard workflow is as follows: - -1. Check that there isn't already an issue about your idea in the [nf-core/wisps issues](https://github.com/nf-core/wisps/issues) to avoid duplicating work. If there isn't one already, please create one so that others know you're working on this -2. [Fork](https://help.github.com/en/github/getting-started-with-github/fork-a-repo) the [nf-core/wisps repository](https://github.com/nf-core/wisps) to your GitHub account -3. Make the necessary changes / additions within your forked repository following [Pipeline conventions](#pipeline-contribution-conventions) -4. Use `nf-core pipelines schema build` and add any new parameters to the pipeline JSON schema (requires [nf-core tools](https://github.com/nf-core/tools) >= 1.10). -5. Submit a Pull Request against the `dev` branch and wait for the code to be reviewed and merged - -If you're not used to this workflow with git, you can start with some [docs from GitHub](https://help.github.com/en/github/collaborating-with-issues-and-pull-requests) or even their [excellent `git` resources](https://try.github.io/). - -## Tests - -You have the option to test your changes locally by running the pipeline. For receiving warnings about process selectors and other `debug` information, it is recommended to use the debug profile. Execute all the tests with the following command: - -```bash -nf-test test --profile debug,test,docker --verbose -``` - -When you create a pull request with changes, [GitHub Actions](https://github.com/features/actions) will run automatic tests. -Typically, pull-requests are only fully reviewed when these tests are passing, though of course we can help out before then. - -There are typically two types of tests that run: - -### Lint tests - -`nf-core` has a [set of guidelines](https://nf-co.re/developers/guidelines) which all pipelines must adhere to. -To enforce these and ensure that all pipelines stay in sync, we have developed a helper tool which runs checks on the pipeline code. This is in the [nf-core/tools repository](https://github.com/nf-core/tools) and once installed can be run locally with the `nf-core pipelines lint ` command. - -If any failures or warnings are encountered, please follow the listed URL for more documentation. - -### Pipeline tests - -Each `nf-core` pipeline should be set up with a minimal set of test-data. -`GitHub Actions` then runs the pipeline on this data to ensure that it exits successfully. -If there are any failures then the automated tests fail. -These tests are run both with the latest available version of `Nextflow` and also the minimum required version that is stated in the pipeline code. - -## Patch - -:warning: Only in the unlikely and regretful event of a release happening with a bug. - -- On your own fork, make a new branch `patch` based on `upstream/master`. -- Fix the bug, and bump version (X.Y.Z+1). -- A PR should be made on `master` from patch to directly this particular bug. - -## Getting help - -For further information/help, please consult the [nf-core/wisps documentation](https://nf-co.re/wisps/usage) and don't hesitate to get in touch on the nf-core Slack [#wisps](https://nfcore.slack.com/channels/wisps) channel ([join our Slack here](https://nf-co.re/join/slack)). - -## Pipeline contribution conventions - -To make the nf-core/wisps code and processing logic more understandable for new contributors and to ensure quality, we semi-standardise the way the code and other contributions are written. - -### Adding a new step - -If you wish to contribute a new step, please use the following coding standards: - -1. Define the corresponding input channel into your new process from the expected previous process channel -2. Write the process block (see below). -3. Define the output channel if needed (see below). -4. Add any new parameters to `nextflow.config` with a default (see below). -5. Add any new parameters to `nextflow_schema.json` with help text (via the `nf-core pipelines schema build` tool). -6. Add sanity checks and validation for all relevant parameters. -7. Perform local tests to validate that the new code works as expected. -8. If applicable, add a new test command in `.github/workflow/ci.yml`. -9. Update MultiQC config `assets/multiqc_config.yml` so relevant suffixes, file name clean up and module plots are in the appropriate order. If applicable, add a [MultiQC](https://https://multiqc.info/) module. -10. Add a description of the output files and if relevant any appropriate images from the MultiQC report to `docs/output.md`. - -### Default values - -Parameters should be initialised / defined with default values in `nextflow.config` under the `params` scope. - -Once there, use `nf-core pipelines schema build` to add to `nextflow_schema.json`. - -### Default processes resource requirements - -Sensible defaults for process resource requirements (CPUs / memory / time) for a process should be defined in `conf/base.config`. These should generally be specified generic with `withLabel:` selectors so they can be shared across multiple processes/steps of the pipeline. A nf-core standard set of labels that should be followed where possible can be seen in the [nf-core pipeline template](https://github.com/nf-core/tools/blob/main/nf_core/pipeline-template/conf/base.config), which has the default process as a single core-process, and then different levels of multi-core configurations for increasingly large memory requirements defined with standardised labels. - -The process resources can be passed on to the tool dynamically within the process with the `${task.cpus}` and `${task.memory}` variables in the `script:` block. - -### Naming schemes - -Please use the following naming schemes, to make it easy to understand what is going where. - -- initial process channel: `ch_output_from_` -- intermediate and terminal channels: `ch__for_` - -### Nextflow version bumping - -If you are using a new feature from core Nextflow, you may bump the minimum required version of nextflow in the pipeline with: `nf-core pipelines bump-version --nextflow . [min-nf-version]` - -### Images and figures - -For overview images and other documents we follow the nf-core [style guidelines and examples](https://nf-co.re/developers/design_guidelines). - -## GitHub Codespaces - -This repo includes a devcontainer configuration which will create a GitHub Codespaces for Nextflow development! This is an online developer environment that runs in your browser, complete with VSCode and a terminal. - -To get started: - -- Open the repo in [Codespaces](https://github.com/nf-core/wisps/codespaces) -- Tools installed - - nf-core - - Nextflow - -Devcontainer specs: - -- [DevContainer config](.devcontainer/devcontainer.json) diff --git a/.github/ISSUE_TEMPLATE/bug_report.yml b/.github/ISSUE_TEMPLATE/bug_report.yml index 9a16a99..6a4ff3f 100644 --- a/.github/ISSUE_TEMPLATE/bug_report.yml +++ b/.github/ISSUE_TEMPLATE/bug_report.yml @@ -7,8 +7,7 @@ body: value: | Before you post this issue, please check the documentation: - - [nf-core website: troubleshooting](https://nf-co.re/usage/troubleshooting) - - [nf-core/wisps pipeline documentation](https://nf-co.re/wisps/usage) + - [Australian-Structural-Biology-Computing/wisps pipeline documentation](https://nf-co.re/wisps/usage) - type: textarea id: description @@ -40,11 +39,11 @@ body: - type: textarea id: system attributes: - label: System information + label: System informationLearn more about contributing: [CONTRIBUTING.md](https://github.com/Australian-Structural-Biology-Computing/wisps/tree/master/.github/CONTRIBUTING.md) description: | * Nextflow version _(eg. 23.04.0)_ * Hardware _(eg. HPC, Desktop, Cloud)_ * Executor _(eg. slurm, local, awsbatch)_ * Container engine: _(e.g. Docker, Singularity, Conda, Podman, Shifter, Charliecloud, or Apptainer)_ * OS _(eg. CentOS Linux, macOS, Linux Mint)_ - * Version of nf-core/wisps _(eg. 1.1, 1.5, 1.8.2)_ + * Version of Australian-Structural-Biology-Computing/wisps _(eg. 1.1, 1.5, 1.8.2)_ diff --git a/.github/ISSUE_TEMPLATE/config.yml b/.github/ISSUE_TEMPLATE/config.yml index 7a2f690..c0f2bae 100644 --- a/.github/ISSUE_TEMPLATE/config.yml +++ b/.github/ISSUE_TEMPLATE/config.yml @@ -4,4 +4,4 @@ contact_links: about: Please join the nf-core community here - name: "Slack #wisps channel" url: https://nfcore.slack.com/channels/wisps - about: Discussion about the nf-core/wisps pipeline + about: Discussion about the Australian-Structural-Biology-Computing/wisps pipeline diff --git a/.github/ISSUE_TEMPLATE/feature_request.yml b/.github/ISSUE_TEMPLATE/feature_request.yml index 31764c1..0b3504c 100644 --- a/.github/ISSUE_TEMPLATE/feature_request.yml +++ b/.github/ISSUE_TEMPLATE/feature_request.yml @@ -1,5 +1,5 @@ name: Feature request -description: Suggest an idea for the nf-core/wisps pipeline +description: Suggest an idea for the Australian-Structural-Biology-Computing/wisps pipeline labels: enhancement body: - type: textarea diff --git a/.github/PULL_REQUEST_TEMPLATE.md b/.github/PULL_REQUEST_TEMPLATE.md index b1455da..266657a 100644 --- a/.github/PULL_REQUEST_TEMPLATE.md +++ b/.github/PULL_REQUEST_TEMPLATE.md @@ -1,22 +1,21 @@ ## PR checklist - [ ] This comment contains a description of changes (with reason). - [ ] If you've fixed a bug or added code that should be tested, add tests! -- [ ] If you've added a new tool - have you followed the pipeline conventions in the [contribution docs](https://github.com/nf-core/wisps/tree/master/.github/CONTRIBUTING.md) -- [ ] If necessary, also make a PR on the nf-core/wisps _branch_ on the [nf-core/test-datasets](https://github.com/nf-core/test-datasets) repository. +- [ ] If you've added a new tool - have you followed the pipeline conventions in the [contribution docs](https://github.com/Australian-Structural-Biology-Computing/wisps/tree/master/.github/CONTRIBUTING.md) +- [ ] If necessary, also make a PR on the Australian-Structural-Biology-Computing/wisps _branch_ on the [nf-core/test-datasets](https://github.com/nf-core/test-datasets) repository. - [ ] Make sure your code lints (`nf-core pipelines lint`). - [ ] Ensure the test suite passes (`nextflow run . -profile test,docker --outdir `). - [ ] Check for unexpected warnings in debug mode (`nextflow run . -profile debug,test,docker --outdir `). diff --git a/.github/workflows/awsfulltest.yml b/.github/workflows/awsfulltest.yml index 04cd000..c1a71f2 100644 --- a/.github/workflows/awsfulltest.yml +++ b/.github/workflows/awsfulltest.yml @@ -15,7 +15,7 @@ jobs: run-platform: name: Run AWS full tests # run only if the PR is approved by at least 2 reviewers and against the master branch or manually triggered - if: github.repository == 'nf-core/wisps' && github.event.review.state == 'approved' && github.event.pull_request.base.ref == 'master' || github.event_name == 'workflow_dispatch' + if: github.repository == 'Australian-Structural-Biology-Computing/wisps' && github.event.review.state == 'approved' && github.event.pull_request.base.ref == 'master' || github.event_name == 'workflow_dispatch' runs-on: ubuntu-latest steps: - uses: octokit/request-action@v2.x diff --git a/.github/workflows/awstest.yml b/.github/workflows/awstest.yml index a6382b8..680f514 100644 --- a/.github/workflows/awstest.yml +++ b/.github/workflows/awstest.yml @@ -7,7 +7,7 @@ on: jobs: run-platform: name: Run AWS tests - if: github.repository == 'nf-core/wisps' + if: github.repository == 'Australian-Structural-Biology-Computing/wisps' runs-on: ubuntu-latest steps: # Launch workflow using Seqera Platform CLI tool action diff --git a/.github/workflows/branch.yml b/.github/workflows/branch.yml index c055aeb..46b9278 100644 --- a/.github/workflows/branch.yml +++ b/.github/workflows/branch.yml @@ -11,9 +11,9 @@ jobs: steps: # PRs to the nf-core repo master branch are only ok if coming from the nf-core repo `dev` or any `patch` branches - name: Check PRs - if: github.repository == 'nf-core/wisps' + if: github.repository == 'Australian-Structural-Biology-Computing/wisps' run: | - { [[ ${{github.event.pull_request.head.repo.full_name }} == nf-core/wisps ]] && [[ $GITHUB_HEAD_REF == "dev" ]]; } || [[ $GITHUB_HEAD_REF == "patch" ]] + { [[ ${{github.event.pull_request.head.repo.full_name }} == Australian-Structural-Biology-Computing/wisps ]] && [[ $GITHUB_HEAD_REF == "dev" ]]; } || [[ $GITHUB_HEAD_REF == "patch" ]] # If the above check failed, post a comment on the PR explaining the failure # NOTE - this doesn't currently work if the PR is coming from a fork, due to limitations in GitHub actions secrets diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index bf1970d..49ad730 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -22,7 +22,7 @@ jobs: test: name: "Run pipeline with test data (${{ matrix.NXF_VER }} | ${{ matrix.test_name }} | ${{ matrix.profile }})" # Only run on push if this is the nf-core dev branch (merged PRs) - if: "${{ github.event_name != 'push' || (github.event_name == 'push' && github.repository == 'nf-core/wisps') }}" + if: "${{ github.event_name != 'push' || (github.event_name == 'push' && github.repository == 'Australian-Structural-Biology-Computing/wisps') }}" runs-on: ubuntu-latest strategy: matrix: diff --git a/.github/workflows/fix-linting.yml b/.github/workflows/fix-linting.yml index bdf8461..3b29764 100644 --- a/.github/workflows/fix-linting.yml +++ b/.github/workflows/fix-linting.yml @@ -9,7 +9,7 @@ jobs: if: > contains(github.event.comment.html_url, '/pull/') && contains(github.event.comment.body, '@nf-core-bot fix linting') && - github.repository == 'nf-core/wisps' + github.repository == 'Australian-Structural-Biology-Computing/wisps' runs-on: ubuntu-latest steps: # Use the @nf-core-bot token to check out so we can push later @@ -86,4 +86,4 @@ jobs: issue-number: ${{ github.event.issue.number }} body: | @${{ github.actor }} I tried to fix the linting errors, but it didn't work. Please fix them manually. - See [CI log](https://github.com/nf-core/wisps/actions/runs/${{ github.run_id }}) for more details. + See [CI log](https://github.com/Australian-Structural-Biology-Computing/wisps/actions/runs/${{ github.run_id }}) for more details. diff --git a/.nf-core.yml b/.nf-core.yml deleted file mode 100644 index d6dc0bc..0000000 --- a/.nf-core.yml +++ /dev/null @@ -1,23 +0,0 @@ -bump_version: null -lint: - files_exist: - - conf/igenomes.config - - conf/igenomes_ignored.config - - conf/igenomes.config - - conf/igenomes_ignored.config -nf_core_version: 3.0.2 -org_path: null -repository_type: pipeline -template: - author: Ziad Al-Bkhetan and Thomas Liftin - description: Workflow for Interaction Screening by predicting Structure - force: true - is_nfcore: true - name: wisps - org: nf-core - outdir: . - skip_features: - - igenomes - - fastqc - version: 1.0.0dev -update: null diff --git a/CHANGELOG.md b/CHANGELOG.md index 1f16456..284e6af 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,11 +1,11 @@ -# nf-core/wisps: Changelog +# Australian-Structural-Biology-Computing/wisps: Changelog The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/) and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). -## v1.0.0dev - [date] +## v1.0.0 - [date] -Initial release of nf-core/wisps, created with the [nf-core](https://nf-co.re/) template. +Initial release of Australian-Structural-Biology-Computing/wisps, created with the [nf-core](https://nf-co.re/) template. ### `Added` diff --git a/CITATIONS.md b/CITATIONS.md index 6c0bab4..28b9de3 100644 --- a/CITATIONS.md +++ b/CITATIONS.md @@ -1,4 +1,4 @@ -# nf-core/wisps: Citations +# Australian-Structural-Biology-Computing/wisps: Citations ## [nf-core](https://pubmed.ncbi.nlm.nih.gov/32055031/) diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md deleted file mode 100644 index c089ec7..0000000 --- a/CODE_OF_CONDUCT.md +++ /dev/null @@ -1,182 +0,0 @@ -# Code of Conduct at nf-core (v1.4) - -## Our Pledge - -In the interest of fostering an open, collaborative, and welcoming environment, we as contributors and maintainers of nf-core pledge to making participation in our projects and community a harassment-free experience for everyone, regardless of: - -- Age -- Ability -- Body size -- Caste -- Familial status -- Gender identity and expression -- Geographical location -- Level of experience -- Nationality and national origins -- Native language -- Neurodiversity -- Race or ethnicity -- Religion -- Sexual identity and orientation -- Socioeconomic status - -Please note that the list above is alphabetised and is therefore not ranked in any order of preference or importance. - -## Preamble - -:::note -This Code of Conduct (CoC) has been drafted by Renuka Kudva, Cris Tuñí, and Michael Heuer, with input from the nf-core Core Team and Susanna Marquez from the nf-core community. "We", in this document, refers to the Safety Officers and members of the nf-core Core Team, both of whom are deemed to be members of the nf-core community and are therefore required to abide by this Code of Conduct. This document will be amended periodically to keep it up-to-date. In case of any dispute, the most current version will apply. -::: - -An up-to-date list of members of the nf-core core team can be found [here](https://nf-co.re/about). - -Our Safety Officers are Saba Nafees, Cris Tuñí, and Michael Heuer. - -nf-core is a young and growing community that welcomes contributions from anyone with a shared vision for [Open Science Policies](https://www.fosteropenscience.eu/taxonomy/term/8). Open science policies encompass inclusive behaviours and we strive to build and maintain a safe and inclusive environment for all individuals. - -We have therefore adopted this CoC, which we require all members of our community and attendees of nf-core events to adhere to in all our workspaces at all times. Workspaces include, but are not limited to, Slack, meetings on Zoom, gather.town, YouTube live etc. - -Our CoC will be strictly enforced and the nf-core team reserves the right to exclude participants who do not comply with our guidelines from our workspaces and future nf-core activities. - -We ask all members of our community to help maintain supportive and productive workspaces and to avoid behaviours that can make individuals feel unsafe or unwelcome. Please help us maintain and uphold this CoC. - -Questions, concerns, or ideas on what we can include? Contact members of the Safety Team on Slack or email safety [at] nf-co [dot] re. - -## Our Responsibilities - -Members of the Safety Team (the Safety Officers) are responsible for clarifying the standards of acceptable behavior and are expected to take appropriate and fair corrective action in response to any instances of unacceptable behaviour. - -The Safety Team, in consultation with the nf-core core team, have the right and responsibility to remove, edit, or reject comments, commits, code, wiki edits, issues, and other contributions that are not aligned to this CoC, or to ban temporarily or permanently any contributor for other behaviors that they deem inappropriate, threatening, offensive, or harmful. - -Members of the core team or the Safety Team who violate the CoC will be required to recuse themselves pending investigation. They will not have access to any reports of the violations and will be subject to the same actions as others in violation of the CoC. - -## When and where does this Code of Conduct apply? - -Participation in the nf-core community is contingent on following these guidelines in all our workspaces and events, such as hackathons, workshops, bytesize, and collaborative workspaces on gather.town. These guidelines include, but are not limited to, the following (listed alphabetically and therefore in no order of preference): - -- Communicating with an official project email address. -- Communicating with community members within the nf-core Slack channel. -- Participating in hackathons organised by nf-core (both online and in-person events). -- Participating in collaborative work on GitHub, Google Suite, community calls, mentorship meetings, email correspondence, and on the nf-core gather.town workspace. -- Participating in workshops, training, and seminar series organised by nf-core (both online and in-person events). This applies to events hosted on web-based platforms such as Zoom, gather.town, Jitsi, YouTube live etc. -- Representing nf-core on social media. This includes both official and personal accounts. - -## nf-core cares 😊 - -nf-core's CoC and expectations of respectful behaviours for all participants (including organisers and the nf-core team) include, but are not limited to, the following (listed in alphabetical order): - -- Ask for consent before sharing another community member’s personal information (including photographs) on social media. -- Be respectful of differing viewpoints and experiences. We are all here to learn from one another and a difference in opinion can present a good learning opportunity. -- Celebrate your accomplishments! (Get creative with your use of emojis 🎉 🥳 💯 🙌 !) -- Demonstrate empathy towards other community members. (We don’t all have the same amount of time to dedicate to nf-core. If tasks are pending, don’t hesitate to gently remind members of your team. If you are leading a task, ask for help if you feel overwhelmed.) -- Engage with and enquire after others. (This is especially important given the geographically remote nature of the nf-core community, so let’s do this the best we can) -- Focus on what is best for the team and the community. (When in doubt, ask) -- Accept feedback, yet be unafraid to question, deliberate, and learn. -- Introduce yourself to members of the community. (We’ve all been outsiders and we know that talking to strangers can be hard for some, but remember we’re interested in getting to know you and your visions for open science!) -- Show appreciation and **provide clear feedback**. (This is especially important because we don’t see each other in person and it can be harder to interpret subtleties. Also remember that not everyone understands a certain language to the same extent as you do, so **be clear in your communication to be kind.**) -- Take breaks when you feel like you need them. -- Use welcoming and inclusive language. (Participants are encouraged to display their chosen pronouns on Zoom or in communication on Slack) - -## nf-core frowns on 😕 - -The following behaviours from any participants within the nf-core community (including the organisers) will be considered unacceptable under this CoC. Engaging or advocating for any of the following could result in expulsion from nf-core workspaces: - -- Deliberate intimidation, stalking or following and sustained disruption of communication among participants of the community. This includes hijacking shared screens through actions such as using the annotate tool in conferencing software such as Zoom. -- “Doxing” i.e. posting (or threatening to post) another person’s personal identifying information online. -- Spamming or trolling of individuals on social media. -- Use of sexual or discriminatory imagery, comments, jokes, or unwelcome sexual attention. -- Verbal and text comments that reinforce social structures of domination related to gender, gender identity and expression, sexual orientation, ability, physical appearance, body size, race, age, religion, or work experience. - -### Online Trolling - -The majority of nf-core interactions and events are held online. Unfortunately, holding events online comes with the risk of online trolling. This is unacceptable — reports of such behaviour will be taken very seriously and perpetrators will be excluded from activities immediately. - -All community members are **required** to ask members of the group they are working with for explicit consent prior to taking screenshots of individuals during video calls. - -## Procedures for reporting CoC violations - -If someone makes you feel uncomfortable through their behaviours or actions, report it as soon as possible. - -You can reach out to members of the Safety Team (Saba Nafees, Cris Tuñí, and Michael Heuer) on Slack. Alternatively, contact a member of the nf-core core team [nf-core core team](https://nf-co.re/about), and they will forward your concerns to the Safety Team. - -Issues directly concerning members of the Core Team or the Safety Team will be dealt with by other members of the core team and the safety manager — possible conflicts of interest will be taken into account. nf-core is also in discussions about having an ombudsperson and details will be shared in due course. - -All reports will be handled with the utmost discretion and confidentiality. - -You can also report any CoC violations to safety [at] nf-co [dot] re. In your email report, please do your best to include: - -- Your contact information. -- Identifying information (e.g. names, nicknames, pseudonyms) of the participant who has violated the Code of Conduct. -- The behaviour that was in violation and the circumstances surrounding the incident. -- The approximate time of the behaviour (if different than the time the report was made). -- Other people involved in the incident, if applicable. -- If you believe the incident is ongoing. -- If there is a publicly available record (e.g. mailing list record, a screenshot). -- Any additional information. - -After you file a report, one or more members of our Safety Team will contact you to follow up on your report. - -## Who will read and handle reports - -All reports will be read and handled by the members of the Safety Team at nf-core. - -If members of the Safety Team are deemed to have a conflict of interest with a report, they will be required to recuse themselves as per our Code of Conduct and will not have access to any follow-ups. - -To keep this first report confidential from any of the Safety Team members, please submit your first report by direct messaging on Slack/direct email to any of the nf-core members you are comfortable disclosing the information to, and be explicit about which member(s) you do not consent to sharing the information with. - -## Reviewing reports - -After receiving the report, members of the Safety Team will review the incident report to determine whether immediate action is required, for example, whether there is immediate threat to participants’ safety. - -The Safety Team, in consultation with members of the nf-core core team, will assess the information to determine whether the report constitutes a Code of Conduct violation, for them to decide on a course of action. - -In the case of insufficient information, one or more members of the Safety Team may contact the reporter, the reportee, or any other attendees to obtain more information. - -Once additional information is gathered, the Safety Team will collectively review and decide on the best course of action to take, if any. The Safety Team reserves the right to not act on a report. - -## Confidentiality - -All reports, and any additional information included, are only shared with the team of safety officers (and possibly members of the core team, in case the safety officer is in violation of the CoC). We will respect confidentiality requests for the purpose of protecting victims of abuse. - -We will not name harassment victims, beyond discussions between the safety officer and members of the nf-core team, without the explicit consent of the individuals involved. - -## Enforcement - -Actions taken by the nf-core’s Safety Team may include, but are not limited to: - -- Asking anyone to stop a behaviour. -- Asking anyone to leave the event and online spaces either temporarily, for the remainder of the event, or permanently. -- Removing access to the gather.town and Slack, either temporarily or permanently. -- Communicating to all participants to reinforce our expectations for conduct and remind what is unacceptable behaviour; this may be public for practical reasons. -- Communicating to all participants that an incident has taken place and how we will act or have acted — this may be for the purpose of letting event participants know we are aware of and dealing with the incident. -- Banning anyone from participating in nf-core-managed spaces, future events, and activities, either temporarily or permanently. -- No action. - -## Attribution and Acknowledgements - -- The [Contributor Covenant, version 1.4](http://contributor-covenant.org/version/1/4) -- The [OpenCon 2017 Code of Conduct](http://www.opencon2017.org/code_of_conduct) (CC BY 4.0 OpenCon organisers, SPARC and Right to Research Coalition) -- The [eLife innovation sprint 2020 Code of Conduct](https://sprint.elifesciences.org/code-of-conduct/) -- The [Mozilla Community Participation Guidelines v3.1](https://www.mozilla.org/en-US/about/governance/policies/participation/) (version 3.1, CC BY-SA 3.0 Mozilla) - -## Changelog - -### v1.4 - February 8th, 2022 - -- Included a new member of the Safety Team. Corrected a typographical error in the text. - -### v1.3 - December 10th, 2021 - -- Added a statement that the CoC applies to nf-core gather.town workspaces. Corrected typographical errors in the text. - -### v1.2 - November 12th, 2021 - -- Removed information specific to reporting CoC violations at the Hackathon in October 2021. - -### v1.1 - October 14th, 2021 - -- Updated with names of new Safety Officers and specific information for the hackathon in October 2021. - -### v1.0 - March 15th, 2021 - -- Complete rewrite from original [Contributor Covenant](http://contributor-covenant.org/) CoC. diff --git a/README.md b/README.md index fc9a1e4..13eb982 100644 --- a/README.md +++ b/README.md @@ -1,28 +1,9 @@ -

    - - - nf-core/wisps - -

    - -[![GitHub Actions CI Status](https://github.com/nf-core/wisps/actions/workflows/ci.yml/badge.svg)](https://github.com/nf-core/wisps/actions/workflows/ci.yml) -[![GitHub Actions Linting Status](https://github.com/nf-core/wisps/actions/workflows/linting.yml/badge.svg)](https://github.com/nf-core/wisps/actions/workflows/linting.yml)[![AWS CI](https://img.shields.io/badge/CI%20tests-full%20size-FF9900?labelColor=000000&logo=Amazon%20AWS)](https://nf-co.re/wisps/results)[![Cite with Zenodo](http://img.shields.io/badge/DOI-10.5281/zenodo.XXXXXXX-1073c8?labelColor=000000)](https://doi.org/10.5281/zenodo.XXXXXXX) -[![nf-test](https://img.shields.io/badge/unit_tests-nf--test-337ab7.svg)](https://www.nf-test.com) - -[![Nextflow](https://img.shields.io/badge/nextflow%20DSL2-%E2%89%A524.04.2-23aa62.svg)](https://www.nextflow.io/) -[![run with conda](http://img.shields.io/badge/run%20with-conda-3EB049?labelColor=000000&logo=anaconda)](https://docs.conda.io/en/latest/) -[![run with docker](https://img.shields.io/badge/run%20with-docker-0db7ed?labelColor=000000&logo=docker)](https://www.docker.com/) -[![run with singularity](https://img.shields.io/badge/run%20with-singularity-1d355c.svg?labelColor=000000)](https://sylabs.io/docs/) -[![Launch on Seqera Platform](https://img.shields.io/badge/Launch%20%F0%9F%9A%80-Seqera%20Platform-%234256e7)](https://cloud.seqera.io/launch?pipeline=https://github.com/nf-core/wisps) - -[![Get help on Slack](http://img.shields.io/badge/slack-nf--core%20%23wisps-4A154B?labelColor=000000&logo=slack)](https://nfcore.slack.com/channels/wisps)[![Follow on Twitter](http://img.shields.io/badge/twitter-%40nf__core-1DA1F2?labelColor=000000&logo=twitter)](https://twitter.com/nf_core)[![Follow on Mastodon](https://img.shields.io/badge/mastodon-nf__core-6364ff?labelColor=FFFFFF&logo=mastodon)](https://mstdn.science/@nf_core)[![Watch on YouTube](http://img.shields.io/badge/youtube-nf--core-FF0000?labelColor=000000&logo=youtube)](https://www.youtube.com/c/nf-core) +# wisps: *w*orkflow for *i*nteraction *s*creening by *p*redicting *s*tructures ## Introduction -**nf-core/wisps** is a bioinformatics pipeline for interaction screening by structure prediction. It ingests a samplesheet of sequence entries (FASTA format) and generates interaction sets based on all-vs-all or group-based modes. The workflow then runs MSA/search and structure prediction with supported models (Boltz, ColabFold, and/or AlphaFold3), computes confidence/interface metrics (including IPSAE), and produces per-interaction result files alongside run-level reports such as MultiQC. +**Australian-Structural-Biology-Computing/wisps** is a bioinformatics pipeline for interaction screening by structure prediction. It ingests a samplesheet of sequence entries (FASTA format) and generates interaction sets based on all-vs-all or group-based modes. The workflow then runs MSA/search and structure prediction with supported models (Boltz, ColabFold, and/or AlphaFold3), computes confidence/interface metrics (including IPSAE), and produces per-interaction result files alongside run-level reports such as MultiQC. - - Validate and parse sequence inputs from the samplesheet (FASTA). - Build interaction sets in manual, all-vs-all or group-based screening mode. - Generated paired MSAs for each interaction using ColabFold Search powered by MMSeqs2. @@ -33,7 +14,7 @@ ## Usage > [!NOTE] -> If you are new to Nextflow and nf-core, please refer to [this page](https://nf-co.re/docs/usage/installation) on how to set-up Nextflow. Make sure to [test your setup](https://nf-co.re/docs/usage/introduction#how-to-run-a-pipeline) with `-profile test` before running the workflow on actual data. +> If you are new to Nextflow, please familiarise yourself with nextflow before running the workflow on actual data. Before running the pipeline, several resources must be available on the computing infrastructure: - **All** tools require the ColabFold MMSeqs2 databases which can be set up following the instructions available [here](https://github.com/sokrypton/ColabFold/tree/main?tab=readme-ov-file#generating-msas-for-large-scale-structurecomplex-predictions) @@ -89,28 +70,24 @@ nextflow run Australian-Structural-Biology-Computing/wisps \ ``` > [!WARNING] -> Please provide pipeline parameters via the CLI or Nextflow `-params-file` option. Custom config files including those provided by the `-c` Nextflow option can be used to provide any configuration _**except for parameters**_; see [docs](https://nf-co.re/docs/usage/getting_started/configuration#custom-configuration-files). +> Please provide pipeline parameters via the CLI or Nextflow `-params-file` option. Custom config files including those provided by the `-c` Nextflow option can be used to provide any configuration _**except for parameters**_. -For more details and further functionality, please refer to the [usage documentation](https://nf-co.re/wisps/usage) and the [parameter documentation](https://nf-co.re/wisps/parameters). +For more details and further functionality, please refer to the [usage documentation](docs/usage.md). ## Pipeline output -To see the results of an example test run with a full size dataset refer to the [results](https://nf-co.re/wisps/results) tab on the nf-core website pipeline page. For more details about the output files and reports, please refer to the -[output documentation](https://nf-co.re/wisps/output). +[output documentation](docs/output.md). ## Credits -nf-core/wisps was originally written by Ziad Al-Bkhetan and Thomas Liftin. +Australian-Structural-Biology-Computing/wisps was originally written by [Ziad Al-Bkhetan](https://github.com/ziadbkh) and [Thomas Liftin](https://github.com/tlitfin/). We thank the following people for their extensive assistance in the development of this pipeline: - - ## Contributions and Support -If you would like to contribute to this pipeline, please see the [contributing guidelines](.github/CONTRIBUTING.md). +If you would like to contribute to this pipeline or for further information/help please reach out to us. -For further information or help, don't hesitate to get in touch on the [Slack `#wisps` channel](https://nfcore.slack.com/channels/wisps) (you can join with [this invite](https://nf-co.re/join/slack)). ## Citations diff --git a/assets/adaptivecard.json b/assets/adaptivecard.json index 4f01087..7f5d661 100644 --- a/assets/adaptivecard.json +++ b/assets/adaptivecard.json @@ -17,7 +17,7 @@ "size": "Large", "weight": "Bolder", "color": "<% if (success) { %>Good<% } else { %>Attention<%} %>", - "text": "nf-core/wisps v${version} - ${runName}", + "text": "Australian-Structural-Biology-Computing/wisps v${version} - ${runName}", "wrap": true }, { diff --git a/assets/email_template.html b/assets/email_template.html index 02329b1..b62c1ac 100644 --- a/assets/email_template.html +++ b/assets/email_template.html @@ -4,21 +4,21 @@ - - nf-core/wisps Pipeline Report + + Australian-Structural-Biology-Computing/wisps Pipeline Report
    -

    nf-core/wisps ${version}

    +

    Australian-Structural-Biology-Computing/wisps ${version}

    Run Name: $runName

    <% if (!success){ out << """     diff --git a/assets/email_template.txt b/assets/email_template.txt index fab93f1..7aa9cb7 100644 --- a/assets/email_template.txt +++ b/assets/email_template.txt @@ -1,18 +1,13 @@ ---------------------------------------------------- - ,--./,-. - ___ __ __ __ ___ /,-._.--~\\ - |\\ | |__ __ / ` / \\ |__) |__ } { - | \\| | \\__, \\__/ | \\ |___ \\`-._,-`-, - `._,._,' - nf-core/wisps ${version} +Australian-Structural-Biology-Computing/wisps ${version} ---------------------------------------------------- Run Name: $runName <% if (success){ - out << "## nf-core/wisps execution completed successfully! ##" + out << "## Australian-Structural-Biology-Computing/wisps execution completed successfully! ##" } else { out << """#################################################### -## nf-core/wisps execution completed unsuccessfully! ## +## Australian-Structural-Biology-Computing/wisps execution completed unsuccessfully! ## #################################################### The exit status of the task that caused the workflow execution to fail was: $exitStatus. The full error message was: @@ -35,5 +30,5 @@ Pipeline Configuration: <% out << summary.collect{ k,v -> " - $k: $v" }.join("\n") %> -- -nf-core/wisps -https://github.com/nf-core/wisps +Australian-Structural-Biology-Computing/wisps +https://github.com/Australian-Structural-Biology-Computing/wisps diff --git a/assets/methods_description_template.yml b/assets/methods_description_template.yml index c6a93ab..a891019 100644 --- a/assets/methods_description_template.yml +++ b/assets/methods_description_template.yml @@ -1,13 +1,13 @@ id: "nf-core-wisps-methods-description" description: "Suggested text and references to use when describing pipeline usage within the methods section of a publication." -section_name: "nf-core/wisps Methods Description" -section_href: "https://github.com/nf-core/wisps" +section_name: "Australian-Structural-Biology-Computing/wisps Methods Description" +section_href: "https://github.com/Australian-Structural-Biology-Computing/wisps" plot_type: "html" ## TODO nf-core: Update the HTML below to your preferred methods description, e.g. add publication citation for this pipeline ## You inject any metadata in the Nextflow '${workflow}' object data: |

    Methods

    -

    Data was processed using nf-core/wisps v${workflow.manifest.version} ${doi_text} of the nf-core collection of workflows (Ewels et al., 2020), utilising reproducible software environments from the Bioconda (Grüning et al., 2018) and Biocontainers (da Veiga Leprevost et al., 2017) projects.

    +

    Data was processed using Australian-Structural-Biology-Computing/wisps v${workflow.manifest.version} ${doi_text} of the nf-core collection of workflows (Ewels et al., 2020), utilising reproducible software environments from the Bioconda (Grüning et al., 2018) and Biocontainers (da Veiga Leprevost et al., 2017) projects.

    The pipeline was executed with Nextflow v${workflow.nextflow.version} (Di Tommaso et al., 2017) with the following command:

    ${workflow.commandLine}

    ${tool_citations}

    diff --git a/assets/multiqc_config.yml b/assets/multiqc_config.yml index 6bfa4b5..a52a9de 100644 --- a/assets/multiqc_config.yml +++ b/assets/multiqc_config.yml @@ -1,5 +1,5 @@ report_comment: > - This report has been generated by the nf-core/wisps + This report has been generated by the Australian-Structural-Biology-Computing/wisps analysis pipeline. For information about how to interpret these results, please see the documentation. report_section_order: diff --git a/assets/schema_input.json b/assets/schema_input.json index 236decb..30eae77 100644 --- a/assets/schema_input.json +++ b/assets/schema_input.json @@ -1,7 +1,7 @@ { "$schema": "https://json-schema.org/draft/2020-12/schema", - "$id": "https://raw.githubusercontent.com/nf-core/wisps/master/assets/schema_input.json", - "title": "nf-core/wisps pipeline - params.input schema", + "$id": "https://raw.githubusercontent.com/Australian-Structural-Biology-Computing/wisps/master/assets/schema_input.json", + "title": "Australian-Structural-Biology-Computing/wisps pipeline - params.input schema", "description": "Schema for the file provided with params.input", "type": "array", "items": { diff --git a/assets/slackreport.json b/assets/slackreport.json index a8f9991..1b3dde0 100644 --- a/assets/slackreport.json +++ b/assets/slackreport.json @@ -3,7 +3,7 @@ { "fallback": "Plain-text summary of the attachment.", "color": "<% if (success) { %>good<% } else { %>danger<%} %>", - "author_name": "nf-core/wisps ${version} - ${runName}", + "author_name": "Australian-Structural-Biology-Computing/wisps ${version} - ${runName}", "author_icon": "https://www.nextflow.io/docs/latest/_static/favicon.ico", "text": "<% if (success) { %>Pipeline completed successfully!<% } else { %>Pipeline completed with errors<% } %>", "fields": [ diff --git a/conf/base.config b/conf/base.config index 2aee722..4aac4e8 100644 --- a/conf/base.config +++ b/conf/base.config @@ -1,6 +1,6 @@ /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - nf-core/wisps Nextflow base config file + Australian-Structural-Biology-Computing/wisps Nextflow base config file ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ A 'blank slate' config file, appropriate for general use on most high performance compute environments. Assumes that all software is installed and available on diff --git a/conf/gadi.config b/conf/gadi.config deleted file mode 100644 index e9bf79d..0000000 --- a/conf/gadi.config +++ /dev/null @@ -1,99 +0,0 @@ -/* -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - Nextflow config file for running minimal tests -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - Defines input files and everything required to run a fast and simple pipeline test. - - Use as follows: - nextflow run nf-core/wisps -profile test, --outdir - ----------------------------------------------------------------------------------------- -*/ -includeConfig 'https://raw.githubusercontent.com/nf-core/configs/master/conf/nci_gadi.config' - -singularity.cacheDir = "/g/data/if89/singularity_cache/" -singularity.autoMounts = true -singularity.enabled = true -if (params.use_gpu) { singularity.runOptions = '--nv' } - -params { - config_profile_name = 'Test profile' - config_profile_description = 'Minimal test dataset to check pipeline function' - - // Input data - outdir = "out-test" - input = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" - - boltz2_aff = "/g/data/li87/struct_bio/params/boltz/boltz2_aff.ckpt" - boltz2_conf = "/g/data/li87/struct_bio/params/boltz/boltz2_conf.ckpt" - boltz2_mols = "/g/data/li87/struct_bio/params/boltz/mols" - - colabfold_uniref30 = "/g/data/li87/proteinfold_dbs/colabfold_uniref30/" - colabfold_envdb = "/g/data/li87/proteinfold_dbs/colabfold_envdb/" - - colabfold_alphafold2_params = "/g/data/li87/struct_bio/params/alphafold2/" - - alphafold3_params = "/g/data/li87/struct_bio/params/alphafold2" - - use_gpu = true - project = "ll61" - use_dgxa100 = false - -} - -process { - //executor = "local" - storage = "gdata/li87+gdata/if89+scratch/${params.project}+gdata/${params.project}" - - withName: 'MMSEQS_COLABFOLDSEARCH' { - memory = 350.GB - time = 48.h - cpus = 16 - } - - withName: 'RUN_BOLTZ' { - if (params.use_dgxa100){ - queue = "dgxa100" - cpus = 16 - }else{ - queue = "gpuvolta" - cpus = 12 - } - time = 48.h - memory = 128.GB - gpus = 1 - } - - withName: 'COLABFOLD_BATCH' { - if (params.use_dgxa100){ - queue = "dgxa100" - cpus = 16 - }else{ - queue = "gpuvolta" - cpus = 12 - } - time = 16.h - memory = 128.GB - - gpus = 1 - } - - resourceLimits = [ - cpus: 1000, - memory: '2000.GB', - time: '48.h' - ] - -} -executor.pollInterval = '5 sec' -executor.queueStatInterval = '1 min' -executor.submitRateLimit = '20min' - -gadi { - format = 'csv' - output = 'gadi_report.csv' -} - -plugins { - id 'nf-gadi@1.2.0' -} diff --git a/conf/test.config b/conf/test.config index e895b00..1304a59 100644 --- a/conf/test.config +++ b/conf/test.config @@ -5,7 +5,7 @@ Defines input files and everything required to run a fast and simple pipeline test. Use as follows: - nextflow run nf-core/wisps -profile test, --outdir + nextflow run Australian-Structural-Biology-Computing/wisps -profile test, --outdir ---------------------------------------------------------------------------------------- */ diff --git a/conf/test_full.config b/conf/test_full.config index aadfb23..5a973f7 100644 --- a/conf/test_full.config +++ b/conf/test_full.config @@ -5,7 +5,7 @@ Defines input files and everything required to run a full size pipeline test. Use as follows: - nextflow run nf-core/wisps -profile test_full, --outdir + nextflow run Australian-Structural-Biology-Computing/wisps -profile test_full, --outdir ---------------------------------------------------------------------------------------- */ diff --git a/conf/test_gadi.config b/conf/test_gadi.config deleted file mode 100644 index cca3175..0000000 --- a/conf/test_gadi.config +++ /dev/null @@ -1,92 +0,0 @@ -/* -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - Nextflow config file for running minimal tests -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - Defines input files and everything required to run a fast and simple pipeline test. - - Use as follows: - nextflow run nf-core/wisps -profile test, --outdir - ----------------------------------------------------------------------------------------- -*/ -singularity.cacheDir = "/g/data/if89/singularity_cache/" -singularity.autoMounts = true -singularity.enabled = true -if (params.use_gpu) { singularity.runOptions = '--nv' } - -params { - config_profile_name = 'Test profile' - config_profile_description = 'Minimal test dataset to check pipeline function' - - // Input data - outdir = "out-test" - input = "/g/data/ll61/development-space/nf-core-wisps/assets/samplesheet.csv" - - boltz2_aff = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz2_aff.ckpt" - boltz2_conf = "/g/data/if89/proteinfold_dbs/boltz_dbs/boltz2_conf.ckpt" - boltz2_mols = "/g/data/if89/proteinfold_dbs/boltz_dbs/mols" - colabfold_envdb = "/g/data/if89/proteinfold_dbs/miniature_databases/colabfold_envdb_202108/" - colabfold_uniref30 = "/g/data/za08/tom/colabfold_uniref30" - colabfold_alphafold2_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params/alphafold_params_2022-12-06/" - - alphafold3_params = "/g/data/if89/proteinfold_dbs/colabfold_dbs/params" - - use_gpu = true - project = "ll61" - use_dgxa100 = false - - colabfold_search_args = " --use-env 0 --af3-json --db1 colabfold_uniref30/uniref30_2302_db --db3 colabfold_envdb_202108/colabfold_envdb_202108_db" -} - -process { - executor = "pbspro" - //executor = "local" - storage = "gdata/za08+gdata/if89+scratch/${params.project}+gdata/${params.project}" - module = 'singularity' - cache = 'lenient' - stageInMode = 'symlink' - queue = { task.memory < 128.GB ? 'normalbw' : (task.memory >= 128.GB && task.memory <= 190.GB ? 'normal' : (task.memory > 190.GB && task.memory <= 1020.GB ? 'hugemembw' : '')) } - - withName: 'RUN_BOLTZ' { - cpus = 12 - queue = "gpuvolta" - time = 10.h - memory = 24.GB - cpus = 12 - gpus = 1 - } - withName: 'MMSEQS_COLABFOLDSEARCH' { - time = 1.h - if (params.mmseqs_gpu){ - queue = "dgxa100" - memory = 24.GB - cpus = 16 - gpus = 1 - } - } - - withName: 'COLABFOLD_BATCH' { - queue = "gpuvolta" - time = 10.h - memory = 64.GB - cpus = 12 - gpus = 1 - } - - resourceLimits = [ - cpus: 1, - memory: '4.GB', - time: '1.h' - ] - resourceLimits1 = [ - cpus: 1000, - memory: '2000.GB', - time: '24.h' - ] - resourceLimits = [ - cpus: 16, - memory: '24.GB', - time: '3.h' - ] - -} diff --git a/docs/README.md b/docs/README.md index ad6387e..5474437 100644 --- a/docs/README.md +++ b/docs/README.md @@ -1,10 +1,9 @@ -# nf-core/wisps: Documentation +# Australian-Structural-Biology-Computing/wisps: Documentation -The nf-core/wisps documentation is split into the following pages: +The Australian-Structural-Biology-Computing/wisps documentation is split into the following pages: - [Usage](usage.md) - An overview of how the pipeline works, how to run it and a description of all of the different command-line flags. - [Output](output.md) - An overview of the different results produced by the pipeline and how to interpret them. -You can find a lot more documentation about installing, configuring and running nf-core pipelines on the website: [https://nf-co.re](https://nf-co.re) diff --git a/docs/output.md b/docs/output.md index 316461b..ef62e40 100644 --- a/docs/output.md +++ b/docs/output.md @@ -1,4 +1,4 @@ -# nf-core/wisps: Output +# Australian-Structural-Biology-Computing/wisps: Output ## Introduction diff --git a/docs/usage.md b/docs/usage.md index 55c8aba..5f88da8 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -1,15 +1,13 @@ -# nf-core/wisps: Usage - -## :warning: Please read this documentation on the nf-core website: [https://nf-co.re/wisps/usage](https://nf-co.re/wisps/usage) - -> _Documentation of pipeline parameters is generated automatically from the pipeline schema and can no longer be found in markdown files._ - -## Introduction - - +# Australian-Structural-Biology-Computing/wisps: Usage ## Samplesheet input +tities/chains in a complex. + - Use `molecule_type|sequence` for non-protein entities (for example `dna|ATCG`, `rna|AUGC`, `ccd|ATP`, `smiles|...`; optional copies like `ccd|ATP|2`). + - If SMILES contains aromatic bonds, replace `:` with `;` as required by ColabFold parsing. +Reference: ColabFold input format examples in the official repository README: . + +## Running the pipeline You will need to create a samplesheet with information about the samples you would like to analyse before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row as shown in the examples below. ```bash @@ -42,7 +40,7 @@ An [example samplesheet](../assets/samplesheet.csv) has been provided with the p The interactions generated from the sample sheet are controlled with `--mode`. There are three supported modes: -1. `--mode all-all` (default): the workflow generates all unique sample pairs (order-independent) across the full sample sheet. This mode does not require the `group` column. You can limit pair generation with `--interaction_neighbours `. The default is `0` (no limit). For any positive `n`, only pairs within `n` neighbours in the sample sheet order are kept. For example, with `--interaction_neighbours 2`, each sample is paired with up to 2 samples before and 2 samples after it. +1. `--mode all-all` (default): the workflow generates all unique sample pairs (order-independent) across the full sample sheet. This mode does not require the `group` column. You can limit pair generation with `--interaction_neighbours `. The default is `0` (no limit). For any positive `n`, only pairs within `n` neighbours in the sample sheet order are kept. For example, with `--interaction_neighbours 2`, each sample is paired with itself and the next two samples in the sample sheet. 2. Group-based mode (for example, `--mode A-A,A-B`): interactions are generated only for the requested group combinations from the `group` column (comma-separated, no spaces). With groups `A` and `B`, `--mode A-A,A-B` will include all `A-A` pairs plus all `A-B` pairs. @@ -59,7 +57,7 @@ Reference: ColabFold input format examples in the official repository README: ` to specify parameters as this will result in errors. Cust The above pipeline run specified with a params file in yaml format: ```bash -nextflow run nf-core/wisps -profile docker -params-file params.yaml +nextflow run Australian-Structural-Biology-Computing/wisps -profile docker -params-file params.yaml ``` with: @@ -95,21 +93,19 @@ outdir: './results/' <...> ``` -You can also generate such `YAML`/`JSON` files via [nf-core/launch](https://nf-co.re/launch). - ### Updating the pipeline When you run the above command, Nextflow automatically pulls the pipeline code from GitHub and stores it as a cached version. When running the pipeline after this, it will always use the cached version if available - even if the pipeline has been updated since. To make sure that you're running the latest version of the pipeline, make sure that you regularly update the cached version of the pipeline: ```bash -nextflow pull nf-core/wisps +nextflow pull Australian-Structural-Biology-Computing/wisps ``` ### Reproducibility It is a good idea to specify a pipeline version when running the pipeline on your data. This ensures that a specific version of the pipeline code and software are used when you run your pipeline. If you keep using the same tag, you'll be running the same version of the pipeline, even if there have been changes to the code since. -First, go to the [nf-core/wisps releases page](https://github.com/nf-core/wisps/releases) and find the latest pipeline version - numeric only (eg. `1.3.1`). Then specify this when running the pipeline with `-r` (one hyphen) - eg. `-r 1.3.1`. Of course, you can switch to another version by changing the number after the `-r` flag. +First, go to the [Australian-Structural-Biology-Computing/wisps releases page](https://github.com/Australian-Structural-Biology-Computing/wisps/releases) and find the latest pipeline version - numeric only (eg. `1.3.1`). Then specify this when running the pipeline with `-r` (one hyphen) - eg. `-r 1.3.1`. Of course, you can switch to another version by changing the number after the `-r` flag. This version number will be logged in reports when you run the pipeline, so that you'll know what you used when you look back in the future. For example, at the bottom of the MultiQC reports. @@ -135,8 +131,6 @@ Several generic profiles are bundled with the pipeline which instruct the pipeli We highly recommend the use of Docker or Singularity containers for full pipeline reproducibility, however when this is not possible, Conda is also supported. ::: -The pipeline also dynamically loads configurations from [https://github.com/nf-core/configs](https://github.com/nf-core/configs) when it runs, making multiple config profiles for various institutional clusters available at run time. For more information and to see if your system is available in these configs please see the [nf-core/configs documentation](https://github.com/nf-core/configs#documentation). - Note that multiple profiles can be loaded, for example: `-profile test,docker` - the order of arguments is important! They are loaded in sequence, so later profiles can overwrite earlier profiles. @@ -170,36 +164,8 @@ You can also supply a run name to resume a specific run: `-resume [run-name]`. U ### `-c` -Specify the path to a specific config file (this is a core Nextflow command). See the [nf-core website documentation](https://nf-co.re/usage/configuration) for more information. - -## Custom configuration - -### Resource requests - -Whilst the default requirements set within the pipeline will hopefully work for most people and with most input data, you may find that you want to customise the compute resources that the pipeline requests. Each step in the pipeline has a default set of requirements for number of CPUs, memory and time. For most of the steps in the pipeline, if the job exits with any of the error codes specified [here](https://github.com/nf-core/rnaseq/blob/4c27ef5610c87db00c3c5a3eed10b1d161abf575/conf/base.config#L18) it will automatically be resubmitted with higher requests (2 x original, then 3 x original). If it still fails after the third attempt then the pipeline execution is stopped. - -To change the resource requests, please see the [max resources](https://nf-co.re/docs/usage/configuration#max-resources) and [tuning workflow resources](https://nf-co.re/docs/usage/configuration#tuning-workflow-resources) section of the nf-core website. - -### Custom Containers - -In some cases you may wish to change which container or conda environment a step of the pipeline uses for a particular tool. By default nf-core pipelines use containers and software from the [biocontainers](https://biocontainers.pro/) or [bioconda](https://bioconda.github.io/) projects. However in some cases the pipeline specified version maybe out of date. - -To use a different container from the default container or conda environment specified in a pipeline, please see the [updating tool versions](https://nf-co.re/docs/usage/configuration#updating-tool-versions) section of the nf-core website. - -### Custom Tool Arguments - -A pipeline might not always support every possible argument or option of a particular tool used in pipeline. Fortunately, nf-core pipelines provide some freedom to users to insert additional parameters that the pipeline does not include by default. - -To learn how to provide additional arguments to a particular tool of the pipeline, please see the [customising tool arguments](https://nf-co.re/docs/usage/configuration#customising-tool-arguments) section of the nf-core website. - -### nf-core/configs - -In most cases, you will only need to create a custom config as a one-off but if you and others within your organisation are likely to be running nf-core pipelines regularly and need to use the same settings regularly it may be a good idea to request that your custom config file is uploaded to the `nf-core/configs` git repository. Before you do this please can you test that the config file works with your pipeline of choice using the `-c` parameter. You can then create a pull request to the `nf-core/configs` repository with the addition of your config file, associated documentation file (see examples in [`nf-core/configs/docs`](https://github.com/nf-core/configs/tree/master/docs)), and amending [`nfcore_custom.config`](https://github.com/nf-core/configs/blob/master/nfcore_custom.config) to include your custom profile. - -See the main [Nextflow documentation](https://www.nextflow.io/docs/latest/config.html) for more information about creating your own configuration files. - -If you have any questions or issues please send us a message on [Slack](https://nf-co.re/join/slack) on the [`#configs` channel](https://nfcore.slack.com/channels/configs). - +Specify the path to a specific config file (this is a core Nextflow command). +Vii ## Running in the background Nextflow handles job submissions and supervises the running jobs. The Nextflow process must run until the pipeline is finished. diff --git a/main.nf b/main.nf index 7240eb2..4877381 100644 --- a/main.nf +++ b/main.nf @@ -1,11 +1,9 @@ #!/usr/bin/env nextflow /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - nf-core/wisps + Australian-Structural-Biology-Computing/wisps ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - Github : https://github.com/nf-core/wisps - Website: https://nf-co.re/wisps - Slack : https://nfcore.slack.com/channels/wisps + Github : https://github.com/Australian-Structural-Biology-Computing/wisps ---------------------------------------------------------------------------------------- */ /* @@ -24,7 +22,7 @@ include { PIPELINE_COMPLETION } from './subworkflows/local/utils_nfcore_wisp // // WORKFLOW: Run main analysis pipeline depending on type of input // -workflow NFCORE_WISPS { +workflow WF_WISPS { take: samplesheet // channel: samplesheet read in from --input main: @@ -56,7 +54,7 @@ workflow NFCORE_WISPS { // // WORKFLOW: Run pipeline // - + WISPS ( ch_samplesheet, params.mode, @@ -107,7 +105,7 @@ workflow { // // WORKFLOW: Run main workflow // - NFCORE_WISPS ( + WF_WISPS ( PIPELINE_INITIALISATION.out.samplesheet ) // @@ -120,7 +118,7 @@ workflow { params.outdir, params.monochrome_logs, params.hook_url, - NFCORE_WISPS.out.multiqc_report + WF_WISPS.out.multiqc_report ) } /* diff --git a/modules.json b/modules.json index b75bd10..96a9beb 100644 --- a/modules.json +++ b/modules.json @@ -1,6 +1,6 @@ { - "name": "nf-core/wisps", - "homePage": "https://github.com/nf-core/wisps", + "name": "Australian-Structural-Biology-Computing/wisps", + "homePage": "https://github.com/Australian-Structural-Biology-Computing/wisps", "repos": { "https://github.com/nf-core/modules.git": { "modules": { diff --git a/modules/local/run_boltz/Dockerfile b/modules/local/run_boltz/Dockerfile index 0ef3a4f..256cf36 100644 --- a/modules/local/run_boltz/Dockerfile +++ b/modules/local/run_boltz/Dockerfile @@ -1,9 +1,11 @@ FROM python:3.12-slim -LABEL authors="Ziad Al-Bkhetan " \ - title="nfcore/proteinfold_boltz" \ - Version="1.2.0dev" \ - description="Docker image containing all software requirements to run boltz using the nf-core/proteinfold pipeline" +LABEL org.opencontainers.image.title="nf-core/proteinfold_boltz" \ + org.opencontainers.image.description="Docker image containing all software requirements to run Boltz using the nf-core/proteinfold pipeline" \ + org.opencontainers.image.version="2.0.0" \ + org.opencontainers.image.authors="Jose Espinosa-Carrasco , Ziad Al-Bkhetan " \ + org.opencontainers.image.source="https://github.com/nf-core/proteinfold" \ + org.opencontainers.image.licenses="MIT" RUN apt-get update && \ apt-get install -y --no-install-recommends \ @@ -12,14 +14,13 @@ RUN apt-get update && \ && apt-get autoremove -y \ && rm -rf /var/lib/apt/lists/* -RUN pip install --no-cache-dir boltz==2.0.3 +RUN pip install --no-cache-dir boltz==2.2.1 -## To update to version 2.2.0, uncomment the following lines, though still was complaining -## about triton version, thought the error msg state to be sure of using 3.3.0 -# RUN pip install --no-cache-dir \ -# cuequivariance_ops_cu12==0.5.1\ -# cuequivariance_ops_torch_cu12==0.5.1 \ -# cuequivariance_torch==0.5.1 \ -# triton==3.3.0 +# The update to 2.2.1, was complaining about this missing dependencies +RUN pip install --no-cache-dir \ + cuequivariance_ops_cu12==0.8.1 \ + cuequivariance_ops_torch_cu12==0.8.1 \ + cuequivariance_torch==0.8.1 \ + triton==3.3.0 -CMD ["boltz"] +CMD ["boltz"] \ No newline at end of file diff --git a/modules/local/run_boltz/main.nf b/modules/local/run_boltz/main.nf index b53e5dd..7eb46f3 100644 --- a/modules/local/run_boltz/main.nf +++ b/modules/local/run_boltz/main.nf @@ -6,7 +6,7 @@ process RUN_BOLTZ { label 'process_medium' label 'process_gpu' - container "nf-core/proteinfold_boltz:dev" + container "nf-core/proteinfold_boltz:2.0.0" input: tuple val(meta), path("fasta/*") diff --git a/nextflow.config b/nextflow.config index c508fdf..8023e1d 100644 --- a/nextflow.config +++ b/nextflow.config @@ -1,6 +1,6 @@ /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - nf-core/wisps Nextflow config file + Australian-Structural-Biology-Computing/wisps Nextflow config file ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Default config options for all compute environments ---------------------------------------------------------------------------------------- @@ -9,7 +9,6 @@ // Global default params, used in configs params { - // TODO nf-core: Specify your pipeline's command line flags // Input options input = null mode = "all-all" @@ -51,7 +50,7 @@ params { // Boilerplate options outdir = null - publish_dir_mode = 'copy' + publish_dir_mode = 'symlink' email = null email_on_fail = null plaintext_email = false @@ -180,15 +179,12 @@ profiles { } test { includeConfig 'conf/test.config' } test_full { includeConfig 'conf/test_full.config' } - test_gadi { includeConfig 'conf/test_gadi.config' } - gadi { includeConfig 'conf/gadi.config' } } // Load nf-core custom profiles from different Institutions includeConfig !System.getenv('NXF_OFFLINE') && params.custom_config_base ? "${params.custom_config_base}/nfcore_custom.config" : "/dev/null" -// Load nf-core/wisps custom profiles from different institutions. -// TODO nf-core: Optionally, you can add a pipeline-specific nf-core config at https://github.com/nf-core/configs +// Load Australian-Structural-Biology-Computing/wisps custom profiles from different institutions. // includeConfig !System.getenv('NXF_OFFLINE') && params.custom_config_base ? "${params.custom_config_base}/pipeline/wisps.config" : "/dev/null" // Set default registry for Apptainer, Docker, Podman, Charliecloud and Singularity independent of -profile @@ -245,13 +241,13 @@ dag { } manifest { - name = 'nf-core/wisps' + name = 'Australian-Structural-Biology-Computing/wisps' author = """Ziad Al-Bkhetan and Thomas Liftin""" - homePage = 'https://github.com/nf-core/wisps' + homePage = 'https://github.com/Australian-Structural-Biology-Computing/wisps' description = """Workflow for Interaction Screening by predicting Structure""" mainScript = 'main.nf' nextflowVersion = '!>=24.04.2' - version = '1.0.0dev' + version = '1.0.0' doi = '' } diff --git a/nextflow_schema.json b/nextflow_schema.json index fff75a4..11aad88 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -1,7 +1,7 @@ { "$schema": "https://json-schema.org/draft/2020-12/schema", - "$id": "https://raw.githubusercontent.com/nf-core/wisps/master/nextflow_schema.json", - "title": "nf-core/wisps pipeline parameters", + "$id": "https://raw.githubusercontent.com/Australian-Structural-Biology-Computing/wisps/master/nextflow_schema.json", + "title": "Australian-Structural-Biology-Computing/wisps pipeline parameters", "description": "Workflow for Interaction Screening by predicting Structure", "type": "object", "$defs": { diff --git a/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf b/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf index 68813d6..81309be 100644 --- a/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf +++ b/subworkflows/local/utils_nfcore_wisps_pipeline/main.nf @@ -1,5 +1,5 @@ // -// Subworkflow with functionality specific to the nf-core/wisps pipeline +// Subworkflow with functionality specific to the Australian-Structural-Biology-Computing/wisps pipeline // /* From 3cb13f88b6fb6b5707e9fc0a2640cbadcdbe5201 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Fri, 24 Apr 2026 11:02:49 +1000 Subject: [PATCH 58/70] cleaning --- modules/local/colabfold_batch/main.nf | 1 - 1 file changed, 1 deletion(-) diff --git a/modules/local/colabfold_batch/main.nf b/modules/local/colabfold_batch/main.nf index c45edd0..5d3513b 100644 --- a/modules/local/colabfold_batch/main.nf +++ b/modules/local/colabfold_batch/main.nf @@ -3,7 +3,6 @@ process COLABFOLD_BATCH { label 'process_medium' label 'process_gpu' - //container "nf-core/proteinfold_colabfold:dev" container "ghcr.io/tlitfin/wisps-colabfold-batch:1.1" input: From 23ebd6662db25172f77bef0783622cfd25c4e783 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Fri, 24 Apr 2026 11:09:53 +1000 Subject: [PATCH 59/70] cleaning --- .github/ISSUE_TEMPLATE/bug_report.yml | 2 +- README.md | 2 +- conf/dbs.config | 2 +- conf/modules_alphafold3.config | 2 +- conf/modules_boltz.config | 2 +- conf/modules_colabfold.config | 2 +- docs/README.md | 1 - docs/usage.md | 10 +++++++--- main.nf | 2 +- modules/local/run_boltz/Dockerfile | 2 +- workflows/wisps.nf | 2 +- 11 files changed, 16 insertions(+), 13 deletions(-) diff --git a/.github/ISSUE_TEMPLATE/bug_report.yml b/.github/ISSUE_TEMPLATE/bug_report.yml index 6a4ff3f..187706b 100644 --- a/.github/ISSUE_TEMPLATE/bug_report.yml +++ b/.github/ISSUE_TEMPLATE/bug_report.yml @@ -39,7 +39,7 @@ body: - type: textarea id: system attributes: - label: System informationLearn more about contributing: [CONTRIBUTING.md](https://github.com/Australian-Structural-Biology-Computing/wisps/tree/master/.github/CONTRIBUTING.md) + label: Learn more about contributing description: | * Nextflow version _(eg. 23.04.0)_ * Hardware _(eg. HPC, Desktop, Cloud)_ diff --git a/README.md b/README.md index 13eb982..788048a 100644 --- a/README.md +++ b/README.md @@ -17,6 +17,7 @@ > If you are new to Nextflow, please familiarise yourself with nextflow before running the workflow on actual data. Before running the pipeline, several resources must be available on the computing infrastructure: + - **All** tools require the ColabFold MMSeqs2 databases which can be set up following the instructions available [here](https://github.com/sokrypton/ColabFold/tree/main?tab=readme-ov-file#generating-msas-for-large-scale-structurecomplex-predictions) - **ColabFold** requires AlphaFold2 model parameters available from the download [link](https://storage.googleapis.com/alphafold/alphafold_params_2022-12-06.tar). - **Boltz** requires model parameters for the Boltz-2 structure prediction model ([link](https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_conf.ckpt)), affinity prediction model ([link](https://huggingface.co/boltz-community/boltz-2/resolve/main/boltz2_aff.ckpt)) and CCD files ([link](https://huggingface.co/boltz-community/boltz-2/resolve/main/mols.tar)) @@ -89,5 +90,4 @@ We thank the following people for their extensive assistance in the development If you would like to contribute to this pipeline or for further information/help please reach out to us. - ## Citations diff --git a/conf/dbs.config b/conf/dbs.config index f5a2d0e..98fe1fd 100644 --- a/conf/dbs.config +++ b/conf/dbs.config @@ -13,4 +13,4 @@ params { colabfold_uniref30 = "${params.db}/colabfold_uniref30/" colabfold_envdb = "${params.db}/colabfold_envdb/" -} \ No newline at end of file +} diff --git a/conf/modules_alphafold3.config b/conf/modules_alphafold3.config index 51f1efe..c690b69 100644 --- a/conf/modules_alphafold3.config +++ b/conf/modules_alphafold3.config @@ -12,4 +12,4 @@ params { // AlphaFold3 alphafold3_params = "${params.db}/params/af3.bin" -} \ No newline at end of file +} diff --git a/conf/modules_boltz.config b/conf/modules_boltz.config index cd860a7..f4b571f 100644 --- a/conf/modules_boltz.config +++ b/conf/modules_boltz.config @@ -14,4 +14,4 @@ params { boltz2_conf = "${params.db}/params/boltz2_conf.ckpt" boltz2_mols = "${params.db}/params/mols" -} \ No newline at end of file +} diff --git a/conf/modules_colabfold.config b/conf/modules_colabfold.config index 21a8e05..e9bf9a8 100644 --- a/conf/modules_colabfold.config +++ b/conf/modules_colabfold.config @@ -11,4 +11,4 @@ params { colabfold_alphafold2_params = "${params.db}/params/alphafold_params_2022-12-06" -} \ No newline at end of file +} diff --git a/docs/README.md b/docs/README.md index 5474437..c7f5a1b 100644 --- a/docs/README.md +++ b/docs/README.md @@ -6,4 +6,3 @@ The Australian-Structural-Biology-Computing/wisps documentation is split into th - An overview of how the pipeline works, how to run it and a description of all of the different command-line flags. - [Output](output.md) - An overview of the different results produced by the pipeline and how to interpret them. - diff --git a/docs/usage.md b/docs/usage.md index 5f88da8..1d297d0 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -1,13 +1,16 @@ # Australian-Structural-Biology-Computing/wisps: Usage ## Samplesheet input + tities/chains in a complex. - - Use `molecule_type|sequence` for non-protein entities (for example `dna|ATCG`, `rna|AUGC`, `ccd|ATP`, `smiles|...`; optional copies like `ccd|ATP|2`). - - If SMILES contains aromatic bonds, replace `:` with `;` as required by ColabFold parsing. + +- Use `molecule_type|sequence` for non-protein entities (for example `dna|ATCG`, `rna|AUGC`, `ccd|ATP`, `smiles|...`; optional copies like `ccd|ATP|2`). +- If SMILES contains aromatic bonds, replace `:` with `;` as required by ColabFold parsing. Reference: ColabFold input format examples in the official repository README: . ## Running the pipeline + You will need to create a samplesheet with information about the samples you would like to analyse before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row as shown in the examples below. ```bash @@ -28,7 +31,7 @@ S3,S3.fasta,A,rna | Column | Description | | ---------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `id` | The `id` identifiers have to be unique in the sample sheet and **must not** have an underscore or hyphen (`_`, `-`). | -| `sequence` | Full path to FASTA file for sample sequence. File has to have the extension ".fasta", or ".fa" | +| `sequence` | Full path to FASTA file for sample sequence. File has to have the extension ".fasta", or ".fa" | | `type` | The sequence type, can be either `protein`, `rna`, `smiles`. It is an optional column; by default, it will be considered as `protein`. | | `group` | It is a way to group samples together to create custom interactions. It is an optional column and **must not** have a hyphen (`-`). If not provided, the interactions will be `all-all`, which means all samples against all samples, or you can use `group.a-group.b` to only consider the samples from `group.a` against samples from `group.b`. | @@ -166,6 +169,7 @@ You can also supply a run name to resume a specific run: `-resume [run-name]`. U Specify the path to a specific config file (this is a core Nextflow command). Vii + ## Running in the background Nextflow handles job submissions and supervises the running jobs. The Nextflow process must run until the pipeline is finished. diff --git a/main.nf b/main.nf index 4877381..09a0cfa 100644 --- a/main.nf +++ b/main.nf @@ -54,7 +54,7 @@ workflow WF_WISPS { // // WORKFLOW: Run pipeline // - + WISPS ( ch_samplesheet, params.mode, diff --git a/modules/local/run_boltz/Dockerfile b/modules/local/run_boltz/Dockerfile index 256cf36..9ebd9e4 100644 --- a/modules/local/run_boltz/Dockerfile +++ b/modules/local/run_boltz/Dockerfile @@ -23,4 +23,4 @@ RUN pip install --no-cache-dir \ cuequivariance_torch==0.8.1 \ triton==3.3.0 -CMD ["boltz"] \ No newline at end of file +CMD ["boltz"] diff --git a/workflows/wisps.nf b/workflows/wisps.nf index 7ccfc6b..a9d247e 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -333,7 +333,7 @@ workflow WISPS { .flatten() .map{[["id": it.baseName.split("_model_0")[0].split("confidence_")[1], "model": "boltz"], it]} .set{ch_boltz_confidence} - + RUN_BOLTZ.out.affinity .map{it[1]} .flatten() From 6a341057613881dc20b7b142faa4c279c0b26c1b Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Fri, 24 Apr 2026 11:51:44 +1000 Subject: [PATCH 60/70] cleaning --- .nf-core.yml | 1 + 1 file changed, 1 insertion(+) create mode 100644 .nf-core.yml diff --git a/.nf-core.yml b/.nf-core.yml new file mode 100644 index 0000000..3805dc8 --- /dev/null +++ b/.nf-core.yml @@ -0,0 +1 @@ +repository_type: pipeline From b948ab05ead6a5e00f96161f52a1fb2cbd3ee1ce Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Sat, 25 Apr 2026 20:08:10 +1000 Subject: [PATCH 61/70] fixing docs --- LICENSE | 2 +- README.md | 4 ++- docs/images/nf-core-wisps_logo_dark.png | Bin 26192 -> 0 bytes docs/images/nf-core-wisps_logo_light.png | Bin 22628 -> 0 bytes docs/usage.md | 44 +++++++++++++++++++++-- nextflow.config | 2 +- 6 files changed, 46 insertions(+), 6 deletions(-) delete mode 100644 docs/images/nf-core-wisps_logo_dark.png delete mode 100644 docs/images/nf-core-wisps_logo_light.png diff --git a/LICENSE b/LICENSE index 8dd95ca..b46bd78 100644 --- a/LICENSE +++ b/LICENSE @@ -1,6 +1,6 @@ MIT License -Copyright (c) Ziad Al-Bkhetan and Thomas Liftin +Copyright (c) Ziad Al-Bkhetan and Thomas Litfin Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal diff --git a/README.md b/README.md index 788048a..8aec9c1 100644 --- a/README.md +++ b/README.md @@ -11,6 +11,8 @@ - Compute confidence and interface metrics, including IPSAE. - Aggregate run metrics and QC summaries in [`MultiQC`](http://multiqc.info/). +![Workflow Diagram](docs/images/wf.jpg) + ## Usage > [!NOTE] @@ -82,7 +84,7 @@ For more details about the output files and reports, please refer to the ## Credits -Australian-Structural-Biology-Computing/wisps was originally written by [Ziad Al-Bkhetan](https://github.com/ziadbkh) and [Thomas Liftin](https://github.com/tlitfin/). +Australian-Structural-Biology-Computing/wisps was originally written by [Ziad Al-Bkhetan](https://github.com/ziadbkh) and [Thomas Litfin](https://github.com/tlitfin/). 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Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row as shown in the examples below. + +```bash +--input '[path to samplesheet file]' +``` -- Use `molecule_type|sequence` for non-protein entities (for example `dna|ATCG`, `rna|AUGC`, `ccd|ATP`, `smiles|...`; optional copies like `ccd|ATP|2`). -- If SMILES contains aromatic bonds, replace `:` with `;` as required by ColabFold parsing. +### Full samplesheet + +An example of the sample sheet used for the pipeline is shown below: + +```csv title="samplesheet.csv" +id,sequence,group,type +S1,S1.fasta,A,protein +S2,Sample2.fasta,B,protein +S3,S3.fasta,A,rna +``` + +| Column | Description | +| ---------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `id` | The `id` identifiers have to be unique in the sample sheet and **must not** have an underscore or hyphen (`_`, `-`). | +| `sequence` | Full path to FASTA file for sample sequence. File has to have the extension ".fasta", or ".fa" | +| `type` | The sequence type, can be either `protein`, `rna`, `smiles`. It is an optional column; by default, it will be considered as `protein`. | +| `group` | It is a way to group samples together to create custom interactions. It is an optional column and **must not** have a hyphen (`-`). If not provided, the interactions will be `all-all`, which means all samples against all samples, or you can use `group.a-group.b` to only consider the samples from `group.a` against samples from `group.b`. | + +A sequence file can contain multiple entities but if the entities are different types, they must adhere to the colabfold standard described below. + +An [example samplesheet](../assets/samplesheet.csv) has been provided with the pipeline. + +## Creating Interactions from sample sheet + +The interactions generated from the sample sheet are controlled with `--mode`. There are three supported modes: + +1. `--mode all-all` (default): the workflow generates all unique sample pairs (order-independent) across the full sample sheet. This mode does not require the `group` column. You can limit pair generation with `--interaction_neighbours `. The default is `0` (no limit). For any positive `n`, only pairs within `n` neighbours in the sample sheet order are kept. For example, with `--interaction_neighbours 2`, each sample is paired with up to 2 samples before and 2 samples after it. + +2. Group-based mode (for example, `--mode A-A,A-B`): interactions are generated only for the requested group combinations from the `group` column (comma-separated, no spaces). With groups `A` and `B`, `--mode A-A,A-B` will include all `A-A` pairs plus all `A-B` pairs. + +3. `--mode manual`: no interaction pairing is generated from the sample sheet. Instead, each FASTA record is treated as one interaction input directly. In this mode, provide interaction FASTA entries in the required ColabFold format: + - One FASTA record per interaction (`>interaction_id` then one sequence line). + - Use `:` to separate entities/chains in a complex. + - Use `molecule_type|sequence` for non-protein entities (for example `dna|ATCG`, `rna|AUGC`, `ccd|ATP`, `smiles|...`; optional copies like `ccd|ATP|2`). + - If SMILES contains aromatic bonds, replace `:` with `;` as required by ColabFold parsing. Reference: ColabFold input format examples in the official repository README: . + ## Running the pipeline You will need to create a samplesheet with information about the samples you would like to analyse before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row as shown in the examples below. diff --git a/nextflow.config b/nextflow.config index 8023e1d..b7760a0 100644 --- a/nextflow.config +++ b/nextflow.config @@ -242,7 +242,7 @@ dag { manifest { name = 'Australian-Structural-Biology-Computing/wisps' - author = """Ziad Al-Bkhetan and Thomas Liftin""" + author = """Ziad Al-Bkhetan and Thomas Litfin""" homePage = 'https://github.com/Australian-Structural-Biology-Computing/wisps' description = """Workflow for Interaction Screening by predicting Structure""" mainScript = 'main.nf' From 8c769ffcf6527cda1290daba7428ebfb00b9f584 Mon Sep 17 00:00:00 2001 From: Ziad Al-Bkhetan Date: Sat, 25 Apr 2026 20:12:14 +1000 Subject: [PATCH 62/70] Add wf diagram --- docs/wf.jpg | Bin 0 -> 66698 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 docs/wf.jpg diff --git a/docs/wf.jpg b/docs/wf.jpg new file mode 100644 index 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z_ZqD4Arzi&J$-%bV3G4165j8xbfaxj^n7|*%-R*swtD3Y!iQ{sb%}q|0{KTQR;0&v zZvT2FF*|0q`!rN6Yvw>(N&VcGolk(|f!t-^C%v$@3kq3@Rj&+|73^QxDK5KK2K)@v zMrVXBSRY#bouh_Dkn0V=^l^MUlsF%d4|$>{C~|e>AaW{_8FH zA7O$ycD>0+#%~!TwnP|`k=LsT)1OFy;K-qoHDP={aGDmidei77s0DL z*ZOFah&Y>3o3X<}E;dLIkv=8K6}>ABS=vM8W-lwa8b-&xF`ORll;Ym*&kvhcg|R}M ze*m7)k0=3(g{GDYz2Xh`eOyQ z!pg5@TJ%57l7ip)RkA{o(4lDSn(T9ar^z=O;Ups)?+%K)&_l-?sJd UmH2N5@o#tff4TX Date: Sat, 25 Apr 2026 20:13:30 +1000 Subject: [PATCH 63/70] fixing docs --- docs/{ => images}/wf.jpg | Bin 1 file changed, 0 insertions(+), 0 deletions(-) rename docs/{ => images}/wf.jpg (100%) diff --git a/docs/wf.jpg b/docs/images/wf.jpg similarity index 100% rename from docs/wf.jpg rename to docs/images/wf.jpg From 2d25a46d1a95f29487e8e54a2880a49d18d52ef7 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Sat, 25 Apr 2026 20:16:25 +1000 Subject: [PATCH 64/70] cleaning --- docs/usage.md | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/docs/usage.md b/docs/usage.md index b8ef6dc..ae6a0bd 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -22,7 +22,7 @@ S3,S3.fasta,A,rna | Column | Description | | ---------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | `id` | The `id` identifiers have to be unique in the sample sheet and **must not** have an underscore or hyphen (`_`, `-`). | -| `sequence` | Full path to FASTA file for sample sequence. File has to have the extension ".fasta", or ".fa" | +| `sequence` | Full path to FASTA file for sample sequence. File has to have the extension ".fasta", or ".fa" | | `type` | The sequence type, can be either `protein`, `rna`, `smiles`. It is an optional column; by default, it will be considered as `protein`. | | `group` | It is a way to group samples together to create custom interactions. It is an optional column and **must not** have a hyphen (`-`). If not provided, the interactions will be `all-all`, which means all samples against all samples, or you can use `group.a-group.b` to only consider the samples from `group.a` against samples from `group.b`. | @@ -46,7 +46,6 @@ The interactions generated from the sample sheet are controlled with `--mode`. T Reference: ColabFold input format examples in the official repository README: . - ## Running the pipeline You will need to create a samplesheet with information about the samples you would like to analyse before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row as shown in the examples below. From d2074c284cffa628c21eddd668a2b5e39702f434 Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Sat, 25 Apr 2026 20:39:46 +1000 Subject: [PATCH 65/70] update docs --- README.md | 2 +- docs/usage.md | 127 +++++++++++++++++++++++++++++++++++++++++++ nextflow_schema.json | 2 +- 3 files changed, 129 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 8aec9c1..8d8aaf4 100644 --- a/README.md +++ b/README.md @@ -75,7 +75,7 @@ nextflow run Australian-Structural-Biology-Computing/wisps \ > [!WARNING] > Please provide pipeline parameters via the CLI or Nextflow `-params-file` option. Custom config files including those provided by the `-c` Nextflow option can be used to provide any configuration _**except for parameters**_. -For more details and further functionality, please refer to the [usage documentation](docs/usage.md). +For more details and further functionality and pipeline's pparameters, please refer to the [usage documentation](docs/usage.md). ## Pipeline output diff --git a/docs/usage.md b/docs/usage.md index ae6a0bd..52d26ec 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -92,6 +92,133 @@ The interactions generated from the sample sheet are controlled with `--mode`. T Reference: ColabFold input format examples in the official repository README: . +## Pipeline parameters + +### General Help Options + +- `--help` `[boolean, string]` + Show help for top-level parameters. If a parameter is provided, shows detailed help for that parameter. + +- `--help_full` `[boolean]` + Show help for all non-hidden parameters. + +- `--show_hidden` `[boolean]` + Show hidden parameters (must be used with `--help` or `--help_full`). + +--- + +### Input / Output Options + +- `--input` `[string]` + Path to CSV file describing samples. + +- `--outdir` `[string]` + Output directory for results (must be an absolute path in cloud environments). + +- `--mode` `[string]` + Interaction mode: + + - `all-all` + - `group-group` (uses `group` column in samplesheet) + Multiple group-group combinations allowed (comma-separated, no spaces). + **Default:** `all-all` + +- `--tools` `[string]` + Models to run (comma-separated, no spaces): + `alphafold3`, `colabfold`, `boltz` + **Default:** `boltz,colabfold` + +- `--analysis_batch_size` `[integer]` + Number of samples processed in one batch by boltz and Alphafold3. + **Default:** `20` + +- `--colabfold_batch_size` `[integer]` + Number of samples processed in one batch by ColabFold. + **Default:** `20` + +- `--interaction_neighbours` `[integer]` + Local neighbourhood size for all-by-all mode. + **Default:** `0` which means no limit and all samples will be considered. + +- `--pool` `[boolean]` + Enable interaction pooling mode (uses `--mode` group pairs). + **Default:** `false` + +- `--pool_size` `[integer]` + Max total sequence length per pool (required if pooling). + **Default:** `2000` + +- `--mmseqs_gpu` `[boolean]` + Run mmseqs on GPU. + +- `--use_spire_db` `[boolean]` + Use Spire database. + +--- + +## Database Options + +- `--db` `[string]` + Path to reference data and model parameters. + +- `--colabfold_uniref30` `[string]` + UniRef30 database. + +- `--colabfold_envdb` `[string]` + ColabFold environment database. + +- `--colabfold_uniref30_prefix` `[string]` + Default: `colabfold_uniref30/uniref30_2302_db` + +- `--colabfold_envdb_prefix` `[string]` + Default: `colabfold_envdb/colabfold_envdb_202108_db` + +- `--spire_db` `[string]` + Spire database. + +- `--colabfold_alphafold2_params` `[string]` + AlphaFold2 parameters for ColabFold. + +- `--boltz2_aff` `[string]` + Boltz affinity file. + +- `--boltz2_conf` `[string]` + Boltz-2 config file. + +- `--boltz2_mols` `[string]` + Boltz-2 molecule files. + +- `--alphafold3_params` `[string]` + AlphaFold3 parameters. + +--- + +## tools Options + +- `--colabfold_num_recycles` `[integer]` + Number of recycles. + **Default:** `3` + +- `--ipsae_pae_cutoff` `[integer]` + PAE cutoff. + **Default:** `10` + +- `--ipsae_dist_cutoff` `[integer]` + Distance cutoff. + **Default:** `10` + +--- + +## Generic Options + +- `--version` `[boolean]` + Show version and exit. + +- `--publish_dir_mode` `[string]` + Output method: + `symlink`, `rellink`, `link`, `copy`, `copyNoFollow`, `move` + **Default:** `symlink` + ## Running the pipeline The typical command for running the pipeline is as follows: diff --git a/nextflow_schema.json b/nextflow_schema.json index 11aad88..a719280 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -265,7 +265,7 @@ }, "publish_dir_mode": { "type": "string", - "default": "copy", + "default": "symlink", "description": "Method used to save pipeline results to output directory.", "help_text": "The Nextflow `publishDir` option specifies which intermediate files should be saved to the output directory. This option tells the pipeline what method should be used to move these files. See [Nextflow docs](https://www.nextflow.io/docs/latest/process.html#publishdir) for details.", "fa_icon": "fas fa-copy", From d486e9f21c391271aa6fe25df6bb48428ca89d63 Mon Sep 17 00:00:00 2001 From: Ziad Al-Bkhetan Date: Mon, 27 Apr 2026 13:24:42 +1000 Subject: [PATCH 66/70] Update usage.md --- docs/usage.md | 46 ---------------------------------------------- 1 file changed, 46 deletions(-) diff --git a/docs/usage.md b/docs/usage.md index 52d26ec..0e076ec 100644 --- a/docs/usage.md +++ b/docs/usage.md @@ -34,52 +34,6 @@ An [example samplesheet](../assets/samplesheet.csv) has been provided with the p The interactions generated from the sample sheet are controlled with `--mode`. There are three supported modes: -1. `--mode all-all` (default): the workflow generates all unique sample pairs (order-independent) across the full sample sheet. This mode does not require the `group` column. You can limit pair generation with `--interaction_neighbours `. The default is `0` (no limit). For any positive `n`, only pairs within `n` neighbours in the sample sheet order are kept. For example, with `--interaction_neighbours 2`, each sample is paired with up to 2 samples before and 2 samples after it. - -2. Group-based mode (for example, `--mode A-A,A-B`): interactions are generated only for the requested group combinations from the `group` column (comma-separated, no spaces). With groups `A` and `B`, `--mode A-A,A-B` will include all `A-A` pairs plus all `A-B` pairs. - -3. `--mode manual`: no interaction pairing is generated from the sample sheet. Instead, each FASTA record is treated as one interaction input directly. In this mode, provide interaction FASTA entries in the required ColabFold format: - - One FASTA record per interaction (`>interaction_id` then one sequence line). - - Use `:` to separate entities/chains in a complex. - - Use `molecule_type|sequence` for non-protein entities (for example `dna|ATCG`, `rna|AUGC`, `ccd|ATP`, `smiles|...`; optional copies like `ccd|ATP|2`). - - If SMILES contains aromatic bonds, replace `:` with `;` as required by ColabFold parsing. - -Reference: ColabFold input format examples in the official repository README: . - -## Running the pipeline - -You will need to create a samplesheet with information about the samples you would like to analyse before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row as shown in the examples below. - -```bash ---input '[path to samplesheet file]' -``` - -### Full samplesheet - -An example of the sample sheet used for the pipeline is shown below: - -```csv title="samplesheet.csv" -id,sequence,group,type -S1,S1.fasta,A,protein -S2,Sample2.fasta,B,protein -S3,S3.fasta,A,rna -``` - -| Column | Description | -| ---------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `id` | The `id` identifiers have to be unique in the sample sheet and **must not** have an underscore or hyphen (`_`, `-`). | -| `sequence` | Full path to FASTA file for sample sequence. File has to have the extension ".fasta", or ".fa" | -| `type` | The sequence type, can be either `protein`, `rna`, `smiles`. It is an optional column; by default, it will be considered as `protein`. | -| `group` | It is a way to group samples together to create custom interactions. It is an optional column and **must not** have a hyphen (`-`). If not provided, the interactions will be `all-all`, which means all samples against all samples, or you can use `group.a-group.b` to only consider the samples from `group.a` against samples from `group.b`. | - -A sequence file can contain multiple entities but if the entities are different types, they must adhere to the colabfold standard described below. - -An [example samplesheet](../assets/samplesheet.csv) has been provided with the pipeline. - -## Creating Interactions from sample sheet - -The interactions generated from the sample sheet are controlled with `--mode`. There are three supported modes: - 1. `--mode all-all` (default): the workflow generates all unique sample pairs (order-independent) across the full sample sheet. This mode does not require the `group` column. You can limit pair generation with `--interaction_neighbours `. The default is `0` (no limit). For any positive `n`, only pairs within `n` neighbours in the sample sheet order are kept. For example, with `--interaction_neighbours 2`, each sample is paired with itself and the next two samples in the sample sheet. 2. Group-based mode (for example, `--mode A-A,A-B`): interactions are generated only for the requested group combinations from the `group` column (comma-separated, no spaces). With groups `A` and `B`, `--mode A-A,A-B` will include all `A-A` pairs plus all `A-B` pairs. From efeb6ffe4ee90ae48eb4b517a42572d672c03123 Mon Sep 17 00:00:00 2001 From: Ziad Al-Bkhetan Date: Mon, 27 Apr 2026 13:26:21 +1000 Subject: [PATCH 67/70] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 8d8aaf4..16a935f 100644 --- a/README.md +++ b/README.md @@ -73,9 +73,9 @@ nextflow run Australian-Structural-Biology-Computing/wisps \ ``` > [!WARNING] -> Please provide pipeline parameters via the CLI or Nextflow `-params-file` option. Custom config files including those provided by the `-c` Nextflow option can be used to provide any configuration _**except for parameters**_. +> Please provide pipeline parameters via the CLI or Nextflow `-params-file` option. Custom config files, including those provided by the `-c` Nextflow option can be used to provide any configuration _**except for parameters**_. -For more details and further functionality and pipeline's pparameters, please refer to the [usage documentation](docs/usage.md). +For more details, further functionalities, and pipeline parameters, please refer to the [usage documentation](docs/usage.md). ## Pipeline output From 0168c5860b2fadac7b00837c4d2b500893feab96 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Sun, 10 May 2026 15:31:19 +1000 Subject: [PATCH 68/70] change publishdir to copy and skip colabfold_search duplication --- conf/modules.config | 3 +++ nextflow.config | 2 +- 2 files changed, 4 insertions(+), 1 deletion(-) diff --git a/conf/modules.config b/conf/modules.config index c73e4e9..123c9f8 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -59,6 +59,9 @@ process { ext.args = args } + publishDir = [ + enabled: false + ] } withName: 'RUN_BOLTZ' { diff --git a/nextflow.config b/nextflow.config index b7760a0..e018619 100644 --- a/nextflow.config +++ b/nextflow.config @@ -50,7 +50,7 @@ params { // Boilerplate options outdir = null - publish_dir_mode = 'symlink' + publish_dir_mode = 'copy' email = null email_on_fail = null plaintext_email = false From f8fe606469c97e9721a75eeae7c708fd0a8d2ba6 Mon Sep 17 00:00:00 2001 From: tlitfin Date: Sun, 10 May 2026 15:31:57 +1000 Subject: [PATCH 69/70] fix boltz to check number of required outputs in case of OOM --- modules/local/run_boltz/main.nf | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/modules/local/run_boltz/main.nf b/modules/local/run_boltz/main.nf index 7eb46f3..6cb6418 100644 --- a/modules/local/run_boltz/main.nf +++ b/modules/local/run_boltz/main.nf @@ -40,6 +40,14 @@ process RUN_BOLTZ { boltz predict fasta ${args} --cache ./ + # Fail fast if Boltz silently skipped structures (e.g. OOM). + n_fasta=\$(ls fasta/*.yaml | wc -l) + n_cif=\$(find boltz_results_* -type f -name '*model_0.cif' 2>/dev/null | wc -l) + if [[ "\$n_fasta" -ne "\$n_cif" ]]; then + echo "ERROR: RUN_BOLTZ incomplete batch. yaml files: \$n_fasta, CIF files: \$n_cif" >&2 + exit 1 + fi + cat <<-END_VERSIONS > versions.yml "${task.process}": boltz: $version From 151274b7f65ddefa8ba14d014d5a52e07895de6e Mon Sep 17 00:00:00 2001 From: ziadbkh Date: Fri, 29 May 2026 12:01:49 +1000 Subject: [PATCH 70/70] predictions filteration and output publishing thought workflows --- conf/modules.config | 14 --------- conf/test.config | 11 ++----- main.nf | 72 ++++++++++++++++++++++++++++++++++++++++++-- nextflow.config | 10 +++--- nextflow_schema.json | 6 ++++ workflows/wisps.nf | 38 +++++++++++++++++++++-- 6 files changed, 118 insertions(+), 33 deletions(-) diff --git a/conf/modules.config b/conf/modules.config index 123c9f8..ffbfd47 100644 --- a/conf/modules.config +++ b/conf/modules.config @@ -12,19 +12,8 @@ singularity.runOptions = params.mmseqs_gpu ? '--nv' : '' process { - publishDir = [ - path: { "${params.outdir}/${task.process.tokenize(':')[-1].tokenize('_')[0].toLowerCase()}" }, - mode: params.publish_dir_mode, - saveAs: { filename -> filename.equals('versions.yml') ? null : filename } - ] - withName: 'MULTIQC' { ext.args = { params.multiqc_title ? "--title \"$params.multiqc_title\"" : '' } - publishDir = [ - path: { "${params.outdir}/multiqc" }, - mode: params.publish_dir_mode, - saveAs: { filename -> filename.equals('versions.yml') ? null : filename } - ] } withName: 'MMSEQS_COLABFOLDSEARCH' { @@ -59,9 +48,6 @@ process { ext.args = args } - publishDir = [ - enabled: false - ] } withName: 'RUN_BOLTZ' { diff --git a/conf/test.config b/conf/test.config index 1304a59..32edac8 100644 --- a/conf/test.config +++ b/conf/test.config @@ -10,13 +10,6 @@ ---------------------------------------------------------------------------------------- */ -process { - resourceLimits = [ - cpus: 4, - memory: '15.GB', - time: '1.h' - ] -} params { config_profile_name = 'Test profile' @@ -25,7 +18,7 @@ params { // Input data // TODO nf-core: Specify the paths to your test data on nf-core/test-datasets // TODO nf-core: Give any required params for the test so that command line flags are not needed - input = params.pipelines_testdata_base_path + 'viralrecon/samplesheet/samplesheet_test_illumina_amplicon.csv' - + input = "$projectDir/assets/samplesheet.csv" + outdir = "test-output" } diff --git a/main.nf b/main.nf index 09a0cfa..4ff48dd 100644 --- a/main.nf +++ b/main.nf @@ -77,12 +77,23 @@ workflow WF_WISPS { params.colabfold_batch_size, params.interaction_neighbours, params.pool, - params.pool_size + params.pool_size, + params.iptm_threshold ) ch_versions = ch_versions.mix(WISPS.out.versions) emit: - multiqc_report //= WISPS.out.multiqc_report // channel: /path/to/multiqc_report.html + colabfold_predictions = WISPS.out.colabfold_predictions + boltz_predictions = WISPS.out.boltz_predictions + af3_predictions = WISPS.out.af3_predictions + multiqc_report = WISPS.out.multiqc_report + versions = WISPS.out.versions + collated_versions = WISPS.out.collated_versions + ipsae_report = WISPS.out.ipsae_report + msa_a3m = WISPS.out.msa_a3m + msa_json = WISPS.out.msa_json + msa_yaml = WISPS.out.msa_yaml + msa_csv = WISPS.out.msa_csv } /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ @@ -120,7 +131,64 @@ workflow { params.hook_url, WF_WISPS.out.multiqc_report ) + + publish: + colabfold_predictions = WF_WISPS.out.colabfold_predictions + boltz_predictions = WF_WISPS.out.boltz_predictions + af3_predictions = WF_WISPS.out.af3_predictions + multiqc_report = WF_WISPS.out.multiqc_report // channel: /path/to/multiqc_report.html + //collated_versions = WF_WISPS.out.collated_versions + ipsae_report = WF_WISPS.out.ipsae_report + msa_a3m = WF_WISPS.out.msa_a3m.map{it[1]} + msa_json = WF_WISPS.out.msa_json.ifEmpty([]) + msa_yaml = WF_WISPS.out.msa_yaml.ifEmpty([]) + msa_csv = WF_WISPS.out.msa_csv.ifEmpty([]) } + +output { + colabfold_predictions { + path { sample -> { + sample.pdb >> "colabfold_predictions/pdb/" + sample.confidence >> "colabfold_predictions/confidence/" + } + } + } + boltz_predictions { + path { sample -> { + sample.cif >> "boltz_predictions/cif/${sample.cif.name}" + sample.pae >> "boltz_predictions/pae/${sample.pae.name}" + sample.confidence >> "boltz_predictions/confidence/${sample.confidence.name}" + } + } + } + af3_predictions { + path { sample -> { + sample.cif >> "alphafold3_predictions/cif/${sample.cif.name}" + sample.confidence >> "alphafold3_predictions/confidence/${sample.confidence.name}" + } + } + } + multiqc_report { + path 'multiqc_report.html' + } + ipsae_report { + path "ipsae/" + } + msa_a3m { + path "mmseqs/" + } + msa_json { + path "mmseqs/" + } + msa_yaml { + path 'mmseqs/' + } + msa_csv { + path 'mmseqs/' + } + +} + /* ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ THE END diff --git a/nextflow.config b/nextflow.config index e018619..c717e89 100644 --- a/nextflow.config +++ b/nextflow.config @@ -22,6 +22,7 @@ params { colabfold_num_recycles = 3 tools = "boltz,colabfold" db = null + iptm_threshold = 0.6 ipsae_pae_cutoff = 10 ipsae_dist_cutoff = 10 @@ -73,8 +74,12 @@ params { // Schema validation default options validate_params = true + } +outputDir = params.outdir + + // Load base.config by default for all pipelines includeConfig 'conf/base.config' @@ -265,11 +270,6 @@ validation { showHiddenParameter = "show_hidden" beforeText = """ -\033[2m----------------------------------------------------\033[0m- - \033[0;32m,--.\033[0;30m/\033[0;32m,-.\033[0m -\033[0;34m ___ __ __ __ ___ \033[0;32m/,-._.--~\'\033[0m -\033[0;34m |\\ | |__ __ / ` / \\ |__) |__ \033[0;33m} {\033[0m -\033[0;34m | \\| | \\__, \\__/ | \\ |___ \033[0;32m\\`-._,-`-,\033[0m - \033[0;32m`._,._,\'\033[0m \033[0;35m ${manifest.name} ${manifest.version}\033[0m -\033[2m----------------------------------------------------\033[0m- """ diff --git a/nextflow_schema.json b/nextflow_schema.json index a719280..4eafbfa 100644 --- a/nextflow_schema.json +++ b/nextflow_schema.json @@ -73,6 +73,12 @@ "description": "Maximum total sequence length per interaction pool (required when --pool is set).", "fa_icon": "fas fa-ruler-horizontal" }, + "iptm_threshold": { + "type": "number", + "default": 0, + "description": "Minimum iptm threshold to filter out predictions. Default is 0, and all predicitons will be ppublished in the output directory.", + "fa_icon": "fas fa-microchip" + }, "use_gpu": { "type": "boolean", "description": "Run on CPUs (default) or GPUs for the models", diff --git a/workflows/wisps.nf b/workflows/wisps.nf index a9d247e..0518647 100644 --- a/workflows/wisps.nf +++ b/workflows/wisps.nf @@ -79,6 +79,7 @@ workflow WISPS { interaction_neighbours pool pool_size + iptm_threshold main: ch_multiqc_files = Channel.empty() @@ -275,7 +276,7 @@ workflow WISPS { ], has_protein] } - ch_interaction_in.count().subscribe{print("total final: ${it}")} + //ch_interaction_in.count().subscribe{print("total final: ${it}")} MMSEQS_COLABFOLDSEARCH ( ch_interaction_raw.map{[["id": "all_run"], it]}, @@ -327,7 +328,6 @@ workflow WISPS { ch_mols ) - RUN_BOLTZ.out.confidence .map{it[1]} .flatten() @@ -770,9 +770,41 @@ workflow WISPS { [] ) + + ch_versions = ch_versions.mix(MULTIQC.out.versions) emit: versions = ch_versions - + collated_versions = ch_collated_versions + multiqc_report = MULTIQC.out.report + ipsae_report = IPSAE.out.txt + msa_a3m = MMSEQS_COLABFOLDSEARCH.out.a3m + msa_json = MMSEQS_COLABFOLDSEARCH.out.json + msa_yaml = MMSEQS_COLABFOLDSEARCH.out.yaml + msa_csv = MMSEQS_COLABFOLDSEARCH.out.msa_csv + + colabfold_predictions = ch_colabfold_scores + .join(ch_colabfold_pdb) + .map { ['score': iptm_threshold > 0 ? new groovy.json.JsonSlurper().parseText(it[1].text).iptm : null, + 'pdb': it[2], + 'confidence': it[1]] } + .filter{iptm_threshold == 0 || it.score >= iptm_threshold} + + boltz_predictions = ch_boltz_pae + .join(ch_boltz_cif) + .join(ch_boltz_confidence) + .map { ['confidence': it[3], + 'cif': it[2], + 'pae': it[1], + 'score': iptm_threshold > 0 ? new groovy.json.JsonSlurper().parseText(it[3].text).iptm : null] } + .filter{iptm_threshold == 0 || it.score >= iptm_threshold} + + af3_predictions = ch_alphafold3_confidence + .join(ch_alphafold3_cif) + .map { ['confidence': it[1], + 'cif': it[2], + 'score': iptm_threshold > 0 ? new groovy.json.JsonSlurper().parseText(it[1].text).iptm : null] } + .filter{iptm_threshold == 0 || it.score >= iptm_threshold} } +