BioWDL: germline-DNA

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This repository contains two workflows. The first is a pipeline for germline variant calling and the second is a somatic variant calling pipeline.
These pipelines can be used to process DNA data (WES or WGS), starting with FastQ files. They will perform quality control (using FastQC and MultiQC), adapter clipping (using cutadapt), mapping (using BWA mem or bwakit) and variant calling (based on the GATK Best Practice for germline calling, and using a variety of callers for somatic calling). Optionally, the somatic workflow can also perform CNV calling.

These pipelines are part of BioWDL developed by the SASC team at Leiden University Medical Center.

Usage

You can run these pipelines using Cromwell:

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

Use germline.wdl to perform germline variant calling and somatic.wdl for somatic variant calling.

Inputs

Inputs are provided through a JSON file. The minimally required inputs are described below, but additional inputs are available. A template containing all possible inputs can be generated using Womtool as described in the WOMtool documentation. For overviews of all available inputs, see the following pages:

• germline
• somatic

Replace <pipeline> with either Germline or Somatic.

{
  "<pipeline>.bwaIndex": {
    "fastaFile": "A path to the fasta file from the bwa index",
    "indexFiles": "A list containing the other bwa index files"
  },
  "<pipeline>.dbsnpVCF": "A path to a dbSNP VCF file",
  "<pipeline>.dbsnpVCFIndex": "The path to the index (.tbi) file associated with the dbSNP VCF",
  "<pipeline>.sampleConfigFile": "A sample configuration file (see below)",
  "<pipeline>.outputDir": "The path to the output directory",
  "<pipeline>.referenceFasta": "A path to a reference fasta",
  "<pipeline>.referenceFastaFai": "The path to the index associated with the reference fasta",
  "<pipeline>.referenceFastaDict": "The path to the dict file associated with the reference fasta",
  "<pipeline>.dockerImagesFile": "A file listing the used docker images."
}

Specific inputs for the germline pipeline are:

{
  "Germline.XNonParRegions": "(Optional) A BED file that lists all the non-PAR regions on the X chromosome.",
  "Germline.YNonParRegions": "(Optional) A BED file that lists all the non-PAR regions on the Y chromosome.",
  "Germline.jointgenotyping": "Whether to call a multisample VCF using JointGenotyping or not.",
  "Germline.singleSampleGvcf": "Whether to create a GVCF file for each sample."
}

These region files are required in order to have gender-aware variantcalling, were the non-PAR region of the X and Y chromosome is called with ploidy 1 for males and the Y chromosome is not called for females.

For samples with unknown gender the non-PAR regions of X will be called with ploidy 2 and the non-PAR regions of Y will be called with ploidy 1 to ensure no variants are missed, regardless of the gender.

Specific inputs for the somatic pipeline are:

{
  "Somatic.preprocessedIntervals": "The preprocessed intervals to be used for CNV calling.",
  "Somatic.performCnvCalling": "Whether or not CNV calling should be performed.",
  "Somatic.CnvPanelOfNormals": "A Panel of normals to be used for CNV calling."
}

There are also the booleans runStrelka, runVardict, runMutect2 and runManta which can turn somatic variant callers on or off (default: all are on).

The panel of normals and preprocessed intervals will be generated on the fly if not provided in the inputs. All samples for which no control is given in the samplesheet will be used to generate the panel of normals.

Some additional inputs which may be of interest are:

{
  "<pipeline>.platform":
    "The sequencing platform used. Default: illumina",
  "<pipeline>.scatterSize": "The size of the scattered regions in bases for the GATK subworkflows. Scattering is used to speed up certain processes. The genome will be seperated into multiple chunks (scatters) which will be processed in their own job, allowing for parallel processing. Higher values will result in a lower number of jobs. The optimal value here will depend on the available resources.",
  "<pipeline>.regions":
    "Bed file with regions used for variantcalling",
  "<pipeline>.adapterForward":
    "The adapters to be cut from the forward reads. Default: Illumina Universal Adapter",
  "<pipeline>.adapterReverse":
    "The adapters to be cut from the reverse reads (if paired-end reads are used). Default: Illumina Universal Adapter.",
  "<pipeline>.useBwaKit":
    "Whether bwakit should be used instead of plain BWA mem, this will required an '.alt' file to be present in the index."
}

Sample configuration

Verification

All samplesheet formats can be verified using biowdl-input-converter. It can be installed with pip install biowdl-input-converter or conda install biowdl-input-converter (from the bioconda channel). Python 3.7 or higher is required.

With biowdl-input-converter --validate samplesheet.csv The file “samplesheet.csv” will be checked. Also the presence of all files in the samplesheet will be checked to ensure no typos were made. For more information check out the biowdl-input-converter readthedocs page.

CSV Format

The sample configuration can be given as a csv file with the following columns: sample, library, readgroup, R1, R1_md5, R2, R2_md5.

The easiest way to create a samplesheet is to use a spreadsheet program such as LibreOffice Calc or Microsoft Excel, and create a table:

NOTE: R1_md5, R2 and R2_md5 are optional do not have to be filled. And additional fields may be added (eg. for documentation purposes), these will be ignored by the pipeline.

Or with control information:

NOTE: The control only needs one field per sample to be filled. Although filling more columns is possible if you like to be explicit.

After creating the table in a spreadsheet program it can be saved in csv format.

YAML format

The sample configuration can also be a YML file which adheres to the following structure:

samples: # Biological replicates
  - id: <sample>
    control: <sample id for associated control> # Only used in the somatic pipeline
    libraries: # Technical replicates
      - id: <library>
        readgroups: # Sequencing lanes
          - id: <readgroup>
            reads:
              R1: <Path to first-end FastQ file.>
              R1_md5: <Path to MD5 checksum file of first-end FastQ file.>
              R2: <Path to second-end FastQ file.>
              R2_md5: <Path to MD5 checksum file of second-end FastQ file.>

Replace the text between < > with appropriate values. R2 values may be omitted in the case of single-end data. Multiple samples, libraries (per sample) and readgroups (per library) may be given.

The control value on the sample level should specify the control sample associated with this sample. This control sample should be present in the sample configuration as well. This is an optional field which is only used in the somatic-variantcalling pipeline, in which somatic-variantcalling will be performed for the indicated pair.

Example

The following is an example of what an inputs JSON might look like. This example is for the somatic-variantcalling pipeline, however the same values can be used for Germline as long as the starting Somatic. is replaced with Germline..

{
  "Somatic.bwaIndex": {
    "fastaFile": "/home/user/genomes/human/bwa/GRCh38.fasta",
    "indexFiles": [
      "/home/user/genomes/human/bwa/GRCh38.fasta.sa",
      "/home/user/genomes/human/bwa/GRCh38.fasta.amb",
      "/home/user/genomes/human/bwa/GRCh38.fasta.ann",
      "/home/user/genomes/human/bwa/GRCh38.fasta.bwt",
      "/home/user/genomes/human/bwa/GRCh38.fasta.pac"
    ]
  },
  "Somatic.dbsnpVCF": "/home/user/genomes/human/dbsnp/dbsnp-151.vcf.gz",
  "Somatic.dbsnpVCFIndex": "/home/user/genomes/human/dbsnp/dbsnp-151.vcf.gz.tbi",
  "Somatic.sampleConfigFiles": "/home/user/analysis/samples.yml",
  "Somatic.outputDir": "/home/user/analysis/results",
  "Somatic.referenceFasta": "/home/user/genomes/human/GRCh38.fasta",
  "Somatic.referenceFastaFai": "/home/user/genomes/human/GRCh38.fasta.fai",
  "Somatic.referenceFastaDict": "/home/user/genomes/human/GRCh38.dict",
  "Somatic.dockerImages.yml": "dockerImages.yml"
}

And the associated samplesheet might look like this:

Saved as csv format it will look like this.

"sample","library","read","control","R1","R1_md5","R2","R2_md5"
"patient1-case","lib1","lane1","patient1-control","/home/user/data/patient1-case/R1.fq.gz","181a657e3f9c3cde2d3bb14ee7e894a3","/home/user/data/patient1-case/R2.fq.gz","ebe473b62926dcf6b38548851715820e"
"patient1-control","lib1","lane1",,"/home/user/data/patient1-control/lane1_R1.fq.gz","7e79b87d95573b06ff2c5e49508e9dbf","/home/user/data/patient1-control/lane1_R2.fq.gz","dc2776dc3a07c4f468455bae1a8ff872"
"patient1-control","lib1","lane2",,"/home/user/data/patient1-control/lane2_R1.fq.gz","18e9b2fef67f6c69396760c09af8e778","/home/user/data/patient1-control/lane2_R2.fq.gz","72209cc64510827bc3f849bab00dfe7d"

The pipeline also supports tab- and ;-delimited files.

Dependency requirements and tool versions

Biowdl pipelines use docker images to ensure reproducibility. This means that biowdl pipelines will run on any system that has docker installed. Alternatively they can be run with singularity.

For more advanced configuration of docker or singularity please check the cromwell documentation on containers.

Images from biocontainers are preferred for biowdl pipelines. The list of default images for this pipeline can be found in the default for the dockerImages input.

Output

This pipeline will produce a number of directories and files:

• samples: Contains a folder per sample.
  • <sample>: Contains a variety of files, including the BAM files for this library (*.markdup.bam) and a BAM file with additional preprocessing performed used for variant calling (*.bsqr.bam). It also contains a directory per library.
    • CNVcalling: Contains the CNV calling results for this sample and its control sample. Only present if somatic.wdl is used with CNV calling enabled.
    • somatic-variantcalling: Contains somatic variant calling results. Only present if somatic.wdl is used.
    • <library>: This directory contains a directory per readgroup.
      • <readgroup>: Contains QC metrics and preprocessed FastQ files.
• multisample.vcf.gz: A multisample VCF file with the variant calling results. Only present if germline.wdl is used.
• multiqc: Contains the multiQC report.
• PON: A generated panel of normals and the preprocessed intervals. Only present if somatic.wdl is used with CNV calling enabled and no PON or preprocessed intervals were provided in the inputs

Scattering

This pipeline performs scattering to speed up analysis on grid computing clusters. For steps such as variant calling the reference genome is split into regions of roughly equal size (see the scatterSize inputs). Each of these regions will be analyzed in separate jobs, allowing them to be processed in parallel.

Contact

For any questions about running this pipeline and feature request (such as adding additional tools and options), please use the github issue tracker or contact the SASC team directly at: sasc@lumc.nl.