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tutorial_local_conda.md

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Tutorial for general UNIX computers without docker

  1. Git clone this pipeline and move into it.

      $ git clone https://github.com/ENCODE-DCC/chip-seq-pipeline2
  $ cd chip-seq-pipeline2

  2. Download cromwell.

      $ wget https://github.com/broadinstitute/cromwell/releases/download/34/cromwell-34.jar
  $ chmod +rx cromwell-34.jar

  3. Download a SUBSAMPLED paired-end sample of ENCSR936XTK.

      $ wget https://storage.googleapis.com/encode-pipeline-test-samples/encode-chip-seq-pipeline/ENCSR936XTK/ENCSR936XTK_fastq_subsampled.tar
  $ tar xvf ENCSR936XTK_fastq_subsampled.tar

  4. Download pre-built genome database for hg38.

      $ wget https://storage.googleapis.com/encode-pipeline-genome-data/test_genome_database_hg38_chip.tar
  $ tar xvf test_genome_database_hg38_chip.tar

  5. Install Conda

  6. Install Conda dependencies.

      $ bash installers/uninstall_dependencies.sh  # to remove any existing pipeline env
  $ bash installers/install_dependencies.sh

  7. Run a pipeline for the test sample.

      $ source activate encode-chip-seq-pipeline # IMPORTANT!
  $ INPUT=examples/local/ENCSR936XTK_subsampled.json
  $ java -jar -Dconfig.file=backends/backend.conf cromwell-34.jar run chip.wdl -i ${INPUT}

  8. It will take about an hour. You will be able to find all outputs on cromwell-executions/chip/[RANDOM_HASH_STRING]/. See output directory structure for details.

  9. See full specification for input JSON file.