From fd93641ed08977b13d36fa38946f00fc91b5607d Mon Sep 17 00:00:00 2001 From: EngyNasr Date: Wed, 3 Jul 2024 15:02:01 +0200 Subject: [PATCH] Adding a Microbiome Workflow PathoGFAIR --- .../microbiome/PathoGFAIR/.dockstore.yml | 15 + workflows/microbiome/PathoGFAIR/CHANGELOG.md | 5 + .../PathoGFAIR/PathoGFAIR-tests.yml | 25 + workflows/microbiome/PathoGFAIR/PathoGFAIR.ga | 8516 +++++++++++++++++ workflows/microbiome/PathoGFAIR/README.md | 14 + .../test-data/heatmap_table.tabular | 149 + workflows/microbiome/README.md | 2 + 7 files changed, 8726 insertions(+) create mode 100644 workflows/microbiome/PathoGFAIR/.dockstore.yml create mode 100644 workflows/microbiome/PathoGFAIR/CHANGELOG.md create mode 100644 workflows/microbiome/PathoGFAIR/PathoGFAIR-tests.yml create mode 100644 workflows/microbiome/PathoGFAIR/PathoGFAIR.ga create mode 100644 workflows/microbiome/PathoGFAIR/README.md create mode 100644 workflows/microbiome/PathoGFAIR/test-data/heatmap_table.tabular diff --git a/workflows/microbiome/PathoGFAIR/.dockstore.yml b/workflows/microbiome/PathoGFAIR/.dockstore.yml new file mode 100644 index 0000000000..1511bdae70 --- /dev/null +++ b/workflows/microbiome/PathoGFAIR/.dockstore.yml @@ -0,0 +1,15 @@ +version: 1.2 +workflows: +- name: main + subclass: Galaxy + publish: true + primaryDescriptorPath: /PathoGFAIR.ga + testParameterFiles: + - /PathoGFAIR-tests.yml + authors: + - name: Engy Nasr + orcid: 0000-0001-9047-4215 + - name: "Bérénice Batut" + orcid: 0000-0001-9852-1987 + - name: Paul Zierep + orcid: 0000-0003-2982-388X diff --git a/workflows/microbiome/PathoGFAIR/CHANGELOG.md b/workflows/microbiome/PathoGFAIR/CHANGELOG.md new file mode 100644 index 0000000000..a8cf9f29a4 --- /dev/null +++ b/workflows/microbiome/PathoGFAIR/CHANGELOG.md @@ -0,0 +1,5 @@ +# Changelog + +## [0.1] 2024-07-03 + +First release. diff --git a/workflows/microbiome/PathoGFAIR/PathoGFAIR-tests.yml b/workflows/microbiome/PathoGFAIR/PathoGFAIR-tests.yml new file mode 100644 index 0000000000..c3426734f5 --- /dev/null +++ b/workflows/microbiome/PathoGFAIR/PathoGFAIR-tests.yml @@ -0,0 +1,25 @@ +- doc: Test outline for PathoGFAIR + job: + reference_genome_of_tested_pathogen_strain: + class: File + location: https://zenodo.org/record/12190648/files/reference_genome_of_tested_strain.fasta.gz + filetype: fasta.gz + collection_of_all_samples: + class: Collection + collection_type: list + elements: + - class: File + identifier: collection_of_all_samples_Spike3bBarcode10 + location: https://zenodo.org/record/12190648/files/collection_of_all_samples_Spike3bBarcode10.fastq.gz + filetype: fastqsanger.gz + - class: File + identifier: collection_of_all_samples_Spike3bBarcode12 + location: https://zenodo.org/record/12190648/files/collection_of_all_samples_Spike3bBarcode12.fastq.gz + filetype: fastqsanger.gz + samples_profile: map-pb + kraken_database: k2_minusb_20210517 + host_reference_genome: apiMel3 + outputs: + heatmap_table: + attributes: {} + path: test-data/heatmap_table.tabular diff --git a/workflows/microbiome/PathoGFAIR/PathoGFAIR.ga b/workflows/microbiome/PathoGFAIR/PathoGFAIR.ga new file mode 100644 index 0000000000..cf1bb1c5af --- /dev/null +++ b/workflows/microbiome/PathoGFAIR/PathoGFAIR.ga @@ -0,0 +1,8516 @@ +{ + "a_galaxy_workflow": "true", + "annotation": "5 workflows in 1: Nanopore Pre-processing, Taxonomy Profiling and Visualisation with krona, Gene-based Pathogen Identification, Allele-based Pathogen Identification, and Pathogen Detection PathoGFAIR Samples Aggregation and Visualisation", + "comments": [], + "creator": [ + { + "class": "Person", + "identifier": "0000-0001-9047-4215", + "name": "Engy Nasr" + }, + { + "class": "Person", + "identifier": "0000-0001-9852-1987", + "name": "Bérénice Batut" + }, + { + "class": "Person", + "identifier": "0000-0003-2982-388X", + "name": "Paul Zierep" + } + ], + "format-version": "0.1", + "license": "MIT", + "release": "0.1", + "name": "PathoGFAIR", + "report": { + "markdown": "# PathoGFAIR Workflow\nBelow are the results for the PathoGFAIR Workflow\n\nThis workflow was run on:\n\n```galaxy\ngenerate_time()\n```\n\nWith Galaxy version:\n\n```galaxy\ngenerate_galaxy_version()\n```\n\n## Workflow Inputs\n- A collection of all sample reads (all in the same sequence file format, e.g.: Fastq, Fastq.gz, Fastqsanger, etc.)\n- Reference Genome to the main pathogen of question to the samples\n- Reference Genome to the host, where the samples are coming from, Human, Chicken, Cow, etc. \n- (Optional) Samples Profile, based on the lab preparation of the samples during sequencing, there should be a sample profile better than the other, to be chosen as an optional input to Minimap2. e.g. PacBio/Oxford Nanopore\n\n## Workflow Output: \n\n### Taxonomy profiling Krona Pie Chart, performed in the Taxonomy Profiling and Visualization with Krona workflow\n\n```galaxy\nhistory_dataset_display(output=\"krona_pie_chart\")\n```\n\n### Bar-plot for the number of QC reads before host sequences removal and number of found host QC reads per sample, performed in the Nanopore - Preprocessing workflow\n\n\n### Barplot for the total number of removed host sequences per sample, performed in the Nanopore - Preprocessing workflow\n\n \n### Barplot for the Mapping mean depth of coverage per sample, performed in the Allele-based Pathogen Identification workflow\n\n\n### Barplot for the Mapping breadth of coverage percentage per sample, performed in the Allele-based Pathogen Identification workflow\n\n\n### Barplot for the total number of complex variants and SNPs identified per sample, performed in the Allele-based Pathogen Identification workflow\n\n\n\n### Clustered heatmap for all identified Virulence Factor (VF) genes per sample, performed in the Gene-based Pathogen Identification workflow\n\n```galaxy\nhistory_dataset_as_image(output=\"heatmap_png\")\n```\n\n### Phylogenetic tree of all identified Virulence Factor (VF) genes per sample, performed in the Gene-based Pathogen Identification workflow\n\n```galaxy\nhistory_dataset_as_image(output=\"all_samples_phylogenetic_tree_based_vfs\")\n```\n\n### Phylogenetic tree of all Antimicrobial resistance (AMR) genes per sample, performed in the Gene-based Pathogen Identification workflow\n\n```galaxy\nhistory_dataset_as_image(output=\"all_samples_phylogenetic_tree_based_vfs\")\n```\n" + }, + "steps": { + "0": { + "annotation": "based on the lab preparation of the samples during sequencing, there should be a sample profile better than the other, to be chosen as an optional input to Minimap2. e.g. PacBio/Oxford Nanopore\n\nFor more details check: https://github.com/lh3/minimap2?tab=readme-ov-file#use-cases", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "based on the lab preparation of the samples during sequencing, there should be a sample profile better than the other, to be chosen as an optional input to Minimap2. e.g. PacBio/Oxford Nanopore\n\nFor more details check: https://github.com/lh3/minimap2?tab=readme-ov-file#use-cases", + "name": "samples_profile" + } + ], + "label": "samples_profile", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 4, + "top": 145.95215999999783 + }, + "tool_id": null, + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": true}", + "tool_version": null, + "type": "parameter_input", + "uuid": "15aa361c-5d92-437b-8d5e-f64b70c8d7c4", + "when": null, + "workflow_outputs": [] + }, + "1": { + "annotation": "Where the samples are coming from, for example, Human, Chicken, Cow, etc. ", + "content_id": null, + "errors": null, + "id": 1, + "input_connections": {}, + "inputs": [ + { + "description": "Where the samples are coming from, for example, Human, Chicken, Cow, etc. ", + "name": "host_reference_genome" + } + ], + "label": "host_reference_genome", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 0, + 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null, + "errors": null, + "id": 3, + "input_connections": {}, + "inputs": [ + { + "description": "Nanopore reads of each sample are all in a single fastq or fastq.gz file", + "name": "collection_of_all_samples" + } + ], + "label": "collection_of_all_samples", + "name": "Input dataset collection", + "outputs": [], + "position": { + "left": 4, + "top": 346.95215999999783 + }, + "tool_id": null, + "tool_state": "{\"optional\": false, \"tag\": null, \"collection_type\": \"list\"}", + "tool_version": null, + "type": "data_collection_input", + "uuid": "4541ed06-a560-4df5-90c7-846279d12925", + "when": null, + "workflow_outputs": [] + }, + "4": { + "annotation": "kraken_database_for_user_to_choose", + "content_id": null, + "errors": null, + "id": 4, + "input_connections": {}, + "inputs": [ + { + "description": "kraken_database_for_user_to_choose", + "name": "kraken_database" + } + ], + "label": "kraken_database", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 284.0000000000001, + "top": 2721.952159999998 + }, + "tool_id": null, + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": false}", + "tool_version": null, + "type": "parameter_input", + "uuid": "edf18172-1512-40ca-9f60-94c756d763d5", + "when": null, + "workflow_outputs": [] + }, + "5": { + "annotation": "", + "id": 5, + "input_connections": { + "collection_of_all_samples": { + "id": 3, + "input_subworkflow_step_id": 2, + "output_name": "output" + }, + "host_reference_genome": { + "id": 1, + "input_subworkflow_step_id": 1, + "output_name": "output" + }, + "samples_profile": { + "id": 0, + "input_subworkflow_step_id": 0, + "output_name": "output" + } + }, + "inputs": [], + "label": null, + "name": "Nanopore Preprocessing", + "outputs": [], + "position": { + "left": 284.0000000000001, + "top": 248.95215999999783 + }, + "subworkflow": { + "a_galaxy_workflow": "true", + "annotation": "", + "comments": [ + { + "child_steps": [ + 14, + 17, + 20 + ], + "color": "green", + "data": { + "title": "Hosts Sequences Identification and Removal (Kraken Technique)" + }, + "id": 6, + "position": [ + 1407.3, + 442.8999938964844 + ], + "size": [ + 709.1, + 300 + ], + "type": "frame" + }, + { + "child_steps": [ + 9, + 10, + 27 + ], + "color": "green", + "data": { + "title": "Samples QC After Trimming" + }, + "id": 5, + "position": [ + 892.1, + 943.5999938964844 + ], + "size": [ + 569.3, + 815 + ], + "type": "frame" + }, + { + "child_steps": [ + 4, + 5, + 7 + ], + "color": "green", + "data": { + "title": "Samples Reads QC" + }, + "id": 4, + "position": [ + 293, + 947.7999938964844 + ], + "size": [ + 520, + 810 + ], + "type": "frame" + }, + { + "child_steps": [ + 2 + ], + "color": "green", + "data": { + "title": "Input Samples Collection" + }, + "id": 3, + "position": [ + 0, + 973.7999938964844 + ], + "size": [ + 240, + 142.2 + ], + "type": "frame" + }, + { + "child_steps": [ + 23, + 8, + 11, + 13, + 19, + 21, + 16, + 22 + ], + "color": "green", + "data": { + "title": "Host Sequences Detection and Removal (Mapping Technique)" + }, + "id": 2, + "position": [ + 886, + 32.399993896484375 + ], + "size": [ + 1772, + 293 + ], + "type": "frame" + }, + { + "child_steps": [ + 3, + 6 + ], + "color": "green", + "data": { + "title": "Trimming to retain samples reads quality" + }, + "id": 1, + "position": [ + 294, + 506.3999938964844 + ], + "size": [ + 498, + 346.8 + ], + "type": "frame" + }, + { + "color": "lime", + "data": { + "text": "In this workflow, we recommend nanopore samples since we are using some tools that are specified for nanopore such as: Minimap2, Nanoplot porechp and fastp.\n\nIn order to switch to illumina please remove the nanoplot step, replace porechop and fastp with cutadapt or trimmomatic, and finally replace Minimap2 with Bowtie2.\n\nThis workflow also take single-end reads to switch to paired-end, you have to check this option in most of the tools used. " + }, + "id": 0, + "position": [ + 295.3, + 262.9999938964844 + ], + "size": [ + 460, + 228 + ], + "type": "markdown" + }, + { + "child_steps": [ + 12, + 18, + 26, + 15, + 24, + 25 + ], + "color": "green", + "data": { + "title": "Creating a table for samples reads count before and after hosts sequences removal and the percentage of found hosts sequences" + }, + "id": 7, + "position": [ + 2025.8999999999999, + 831.0999938964843 + ], + "size": [ + 1403, + 223 + ], + "type": "frame" + } + ], + "creator": [ + { + "class": "Person", + "identifier": "0000-0001-9852-1987", + "name": "B\u00e9r\u00e9nice Batut", + "url": "https://orcid.org/0000-0001-9852-1987" + }, + { + "class": "Person", + "identifier": "0000-0001-9047-4215", + "name": "Engy Nasr", + "url": "https://orcid.org/0000-0001-9047-4215" + }, + { + "class": "Person", + "identifier": "0000-0003-2982-388X", + "name": "Paul Zierep" + } + ], + "format-version": "0.1", + "license": "MIT", + "name": "Nanopore Preprocessing", + "report": { + "markdown": "# Nanopore - Preprocessing Workflow Report\nBelow are the results of the Preprocessing Workflow\n\nThis workflow was run on:\n\n```galaxy\ngenerate_time()\n```\n\nWith Galaxy version:\n\n```galaxy\ngenerate_galaxy_version()\n```\n\n## Workflow Inputs\nA collection of all sample reads (all in the same sequence file format, e.g.: Fastq, Fastq.gz, Fastqsanger, etc.)\n\n## Workflow Outputs\n\n### Multi QC Report of all samples before reads quality retaining\n\n```galaxy\nhistory_dataset_as_image(output=\"multiQC_html_report_before_preprocessing\")\n```\n### Multi QC Report of all samples after reads quality retaining\n\n```galaxy\nhistory_dataset_as_image(output=\"multiQC_html_report_after_preprocessing\")\n```\n\n### Table of the total number of reads and the number of host reads\n\n```galaxy\nhistory_dataset_display(output=\"removed_hosts_percentage_tabular\")\n```\n\n" + }, + "steps": { + "0": { + "annotation": "based on the lab preparation of the samples during sequencing, there should be a sample profile better than the other, to be chosen as an optional input to Minimap2. e.g. PacBio/Oxford Nanpore\n\nFor more details check: https://github.com/lh3/minimap2?tab=readme-ov-file#use-cases", + "content_id": null, + "errors": null, + "id": 0, + "input_connections": {}, + "inputs": [ + { + "description": "based on the lab preparation of the samples during sequencing, there should be a sample profile better than the other, to be chosen as an optional input to Minimap2. e.g. PacBio/Oxford Nanpore\n\nFor more details check: https://github.com/lh3/minimap2?tab=readme-ov-file#use-cases", + "name": "samples_profile" + } + ], + "label": "samples_profile", + "name": "Input parameter", + "outputs": [], + "position": { + "left": 593, + "top": 0 + }, + "tool_id": null, + "tool_state": "{\"restrictOnConnections\": true, \"parameter_type\": \"text\", \"optional\": true}", + "tool_version": null, + "type": "parameter_input", + "uuid": 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Identification workflow, four other tabular files from Nanopore Preprocessing and Nanopore - Allele-based Pathogen Identification workflow, and an optional Metadata tabular file with more sample information:\n\nFrom Gene-based Pathogenic Identification workflow: \n- contigs, FASTA file\n- VFs, Tabular file\n- vfs_of_genes_identified_by_vfdb, Tabular file\n- AMRs, Tabular file\n- amr_identified_by_ncbi, Tabular file\n\nFrom Nanopore - Allele bases Pathogen Identification workflow: \n- number_of_variants_per_sample, Tabular file\n- mapping_mean_depth_per_sample, Tabular file\n- mapping_coverage_percentage_per_sample, Tabular file\n\nFrom Nanopore Preprocessing: \n- removed_hosts_percentage_tabular, Tabular file\n\n## Some of the Workflow Outputs\n\n1- All Samples VFs Heatmap\n\n```galaxy\nhistory_dataset_as_image(output=\"heatmap_png\")\n```\n\n2- All samples phylogenetic tree VFs based\n\n```galaxy\nhistory_dataset_as_image(output=\"all_samples_phylogenetic_tree_based_vfs\")\n```\n\n3- 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+ ], + "uuid": "b6373c3a-53d0-44ce-8bfd-f503239a1db8", + "version": 93 +} diff --git a/workflows/microbiome/PathoGFAIR/README.md b/workflows/microbiome/PathoGFAIR/README.md new file mode 100644 index 0000000000..0257d97427 --- /dev/null +++ b/workflows/microbiome/PathoGFAIR/README.md @@ -0,0 +1,14 @@ +# PathoGFAIR + +This workflow groups 5 different workflows in 1: **Nanopore Preprocessing**, **Taxonomy Profiling and Visualization with Krona**, **Gene-based Pathogen Identification**, **Nanopore Allele-based Pathogen Identification** and **Pathogen Detection: PathoGFAIR Samples Aggregation and Visualisation**. + +## Input Datasets + +- A collection of all sample reads (all in the same sequence file format, e.g.: Fastq, Fastq.gz, Fastqsanger, etc.) +- Reference Genome to the main pathogen of question to the samples +- Reference Genome to the host, where the samples are coming from, Human, Chicken, Cow, etc. +- (Optional) Samples Profile, based on the lab preparation of the samples during sequencing, there should be a sample profile better than the other, to be chosen as an optional input to Minimap2. e.g. PacBio/Oxford Nanopore + +## Output Datasets + +All outputs of the previously mentioned workflows that forms PathoGFAIR. diff --git a/workflows/microbiome/PathoGFAIR/test-data/heatmap_table.tabular b/workflows/microbiome/PathoGFAIR/test-data/heatmap_table.tabular new file mode 100644 index 0000000000..2cfe7d41f8 --- /dev/null +++ b/workflows/microbiome/PathoGFAIR/test-data/heatmap_table.tabular @@ -0,0 +1,149 @@ +key collection_of_all_samples_Spike3bBarcode10 collection_of_all_samples_Spike3bBarcode12 +IlpA 0 1 +cheB 0 1 +cheR 0 1 +cheW 0 1 +cheY 0 1 +cheZ 0 1 +chuS 0 1 +chuU 0 1 +csgA 0 1 +csgB 0 1 +csgC 0 1 +csgD 0 1 +csgE 0 1 +csgF 0 1 +csgG 0 1 +entA 0 1 +entB 0 1 +entC 0 1 +entE 0 1 +entF 0 1 +entS 0 1 +farB 0 1 +fcl 0 1 +fepA 0 1 +fepB 0 1 +fepC 0 1 +fepD 0 1 +fepG 0 1 +fes 0 1 +fimC 0 1 +fimD 0 1 +fimF 0 1 +fimH 0 1 +fimI 0 1 +flgB 0 1 +flgC 0 1 +flgD 0 1 +flgF 0 1 +flgG 0 1 +flgH 0 1 +flgI 0 1 +flgJ 0 1 +flhB 0 1 +flhC 0 1 +flhD 0 1 +fliA 1 1 +fliF 1 1 +fliG 1 1 +fliH 1 0 +fliI 1 1 +fliM 1 1 +fliN 1 1 +fliP 1 1 +fliQ 1 1 +fliR 1 1 +fliS 1 1 +galU 0 1 +gmd 0 1 +hcp-2 0 1 +htpB 0 1 +icl 0 1 +icsP/sopA 1 1 +invA 0 1 +invB 0 1 +invC 0 1 +invE 0 1 +invF 0 1 +invG 0 1 +invH 0 1 +invI 0 1 +invJ 0 1 +kdsA 0 1 +lpxB 0 1 +lpxC 0 1 +lpxD 0 1 +luxS 0 1 +mgtB 0 1 +mgtC 0 1 +mig-14 0 2 +motA 0 1 +motB 0 1 +ompA 0 1 +orgA 0 1 +orgB 0 1 +orgC 0 1 +pefA 1 0 +pefB 1 0 +pefC 1 0 +pefD 1 0 +pla 0 1 +prgH 0 1 +prgI 0 1 +prgJ 0 1 +prgK 0 1 +rck 1 0 +rfaD 0 1 +rfaE 0 1 +shuA 0 1 +sicA 0 1 +sicP 0 1 +sifA 1 1 +sifB 0 1 +sipA/sspA 0 1 +sipB/sspB 0 1 +sipC/sspC 0 1 +sipD 0 1 +sodCI 0 1 +sopB/sigD 0 1 +sopD 0 1 +spaO 0 1 +spaP 0 1 +spaQ 0 1 +spaR 0 1 +spaS 0 1 +spiC/ssaB 0 1 +sptP 0 1 +spvB 1 1 +spvC 1 0 +ssaC 0 1 +ssaD 0 1 +ssaE 0 1 +ssaG 0 1 +ssaH 0 1 +ssaI 0 1 +ssaJ 0 1 +ssaK 0 1 +ssaL 0 1 +ssaM 0 1 +ssaN 0 1 +ssaO 0 1 +ssaP 0 1 +ssaV 0 1 +sscA 0 1 +sscB 0 1 +sseA 0 1 +sseB 0 1 +sseC 0 1 +sseD 0 1 +sseE 0 1 +sseF 0 1 +sseG 0 1 +sseJ 0 1 +sseK1 1 0 +sspH2 0 2 +steA 0 1 +steB 0 1 +steC 0 1 +vipB/mglB 0 1 diff --git a/workflows/microbiome/README.md b/workflows/microbiome/README.md index 36e0989ec5..599c164deb 100644 --- a/workflows/microbiome/README.md +++ b/workflows/microbiome/README.md @@ -14,6 +14,8 @@ In this directory, you will find a collection of workflows designed for microbio - **Pathogen Detection: PathoGFAIR Samples Aggregation and Visualisation** +- **PathoGFAIR** + ## Getting Started To learn more about these workflows and to try them with real datasets, please visit our Microbiome tutorials on the Galaxy Training Network (GTN):