Home | BioWDL: gatk-preprocess

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This workflow performs preprocessing steps required for variantcalling based on the GATK Best Practices. This workflow can be used for both DNA data and RNA-seq data.

This workflow is part of BioWDL developed by the SASC team.

Usage

This workflow can be run using Cromwell:

java -jar cromwell-<version>.jar run -i inputs.json gatk-preprocess.wdl

Inputs

Inputs are provided through a JSON file. The minimally required inputs are described below and a template containing all possible inputs can be generated using Womtool as described in the WOMtool documentation. See this page for some additional general notes and information about pipeline inputs.

{
  "GatkPreprocess.reference": {
    "fasta": "A path to a reference fasta",
    "fai": "The path to the index associated with the reference fasta",
    "dict": "The path to the dict file associated with the reference fasta"
  },
  "GatkPreprocess.basePath": "The base bath (prefix) for the output. The final output will be <basePath>.bam or <basePath>.bqsr",
  "GatkPreprocess.dbsnpVCF": {
    "file": "A path to a dbSNP VCF file",
    "index": "The path to the index (.tbi) file associated with the dbSNP VCF"
  },
  "GatkPreprocess.bamFile": {
    "file": "The path to an input BAM file",
    "index":"The path to the index for the input BAM file"
  }
}

Some additional inputs that may be of interest are:

{
  "GatkPreprocess.scatterSize": "The size of scatter regions (see explanation of scattering below), defaults to 10,000,000",
  "GatkPreprocess.outputRecalibratedBam": "Whether or not a recalibrated BAM file should be outputted, defaults to false",
  "GatkPreprocess.splitSplicedReads": "Whether or not SplitNCigarReads should be executed (recommended for RNA-seq data), defaults to false",
  "GatkPreprocess.scatterList.regions": "A bed file for which preprocessing will be performed"
}

Example

{
  "GatkPreprocess.reference": {
    "fasta": "/home/user/genomes/human/GRCh38.fasta",
    "fai": "/home/user/genomes/human/GRCh38.fasta.fai",
    "dict": "/home/user/genomes/human/GRCh38.dict"
  },
  "GatkPreprocess.basePath": "/home/user/mapping/results/s1_preprocessed",
  "GatkPreprocess.dbsnpVCF": {
    "file": "/home/user/genomes/human/dbsnp/dbsnp-151.vcf.gz",
    "index": "/home/user/genomes/human/dbsnp/dbsnp-151.vcf.gz.tbi"
  },
  "GatkPreprocess.bamFile": {
    "file": "/home/user/mapping/results/s1.bam",
    "index":"/home/user/mapping/results/s1.bai"
  },
  "GatkPreprocess.splitSplicedReads": true,
  "GatkPreprocess.outputRecalibratedBam": true
}

Dependency requirements and tool versions

Included in the repository is an environment.yml file. This file includes all the tool version on which the workflow was tested. You can use conda and this file to create an environment with all the correct tools.

Output

This workflow will produce a BQSR report named according to the basePath input (basePath + ‘.bqsr’). If one of the splitSplicedReads or outputRecalibratedBam inputs is set to true, a new BAM file (basePath + ‘.bam’) will be produced as well.

Scattering

This pipeline performs scattering to speed up analysis on grid computing clusters. This is done by splitting the reference genome into regions of roughly equal size (see the scatterSize input). Each of these regions will be analyzed in separate jobs, allowing them to be processed in parallel.

Contact

For any question about running this workflow and feature requests, please use the github issue tracker or contact the SASC team directly at: sasc@lumc.nl.