germline.wdl

version 1.0

# Copyright (c) 2018 Leiden University Medical Center
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import "sample.wdl" as sampleWf
import "structural-variantcalling/structural-variantcalling.wdl" as structuralVariantCalling
import "gatk-variantcalling/single-sample-variantcalling.wdl" as variantCallingWorkflow
import "gatk-variantcalling/jointgenotyping.wdl" as jgwf
import "gatk-variantcalling/calculate-regions.wdl" as calcRegions
import "structs.wdl" as structs
import "tasks/biowdl.wdl" as biowdl
import "tasks/bwa.wdl" as bwa
import "tasks/common.wdl" as common
import "tasks/multiqc.wdl" as multiqc
import "tasks/chunked-scatter.wdl" as chunkedScatter
import "tasks/samtools.wdl" as samtools

workflow Germline {
    input {
        File sampleConfigFile
        String outputDir = "."
        File referenceFasta
        File? referenceFastaFai
        File? referenceFastaDict
        File dbsnpVCF
        File? dbsnpVCFIndex
        Boolean jointgenotyping = true
        Boolean singleSampleGvcf = false
        String platform = "illumina"
        Boolean useBwaKit = false
        Int scatterSizeMillions = 1000
        Boolean runSVcalling = false
        Boolean umiDeduplication = false
        Boolean collectUmiStats = false

        BwaIndex? bwaIndex
        BwaIndex? bwaMem2Index
        File? regions
        File? XNonParRegions
        File? YNonParRegions
        String? adapterForward
        String? adapterReverse
        Int? scatterSize

        Int bwaThreads = 4
        File dockerImagesFile
    }

    meta {
        WDL_AID: {
            exclude: ["DONOTDEFINE"]
        }
        allowNestedInputs: true
    }

    Boolean mergeVcfs = !jointgenotyping || singleSampleGvcf

    if (!defined(referenceFastaFai) || !defined(referenceFastaDict)) {
        call samtools.DictAndFaidx as fidx {
            input:
                inputFile = referenceFasta
        }
    }
    File refFasta = select_first([fidx.outputFasta, referenceFasta])
    File refFastaDict = select_first([fidx.outputFastaDict, referenceFastaDict])
    File refFastaFai = select_first([fidx.outputFastaFai, referenceFastaFai])

    if (!defined(dbsnpVCFIndex)) {
        call samtools.Tabix as tabix {
            input:
                inputFile = dbsnpVCF,
                type = "vcf"
        }
    }
    File dbsnpVcf = select_first([tabix.indexedFile, dbsnpVCF])
    File dbsnpVcfIndex = select_first([tabix.index, dbsnpVCFIndex])

    if (!defined(bwaIndex) && !defined(bwaMem2Index)) {
        call bwa.Index as bwaIndexTask {
            input:
                fasta = refFasta
        }
    }
    BwaIndex? bwidx = if defined(bwaIndex) then bwaIndex else bwaIndexTask.index

    # Parse docker Tags configuration and sample sheet.
    call common.YamlToJson as convertDockerImagesFile {
        input:
            yaml = dockerImagesFile,
            outputJson = "dockerImages.json"
    }

    Map[String, String] dockerImages = read_json(convertDockerImagesFile.json)

    call biowdl.InputConverter as convertSampleConfig {
        input:
            samplesheet = sampleConfigFile,
            dockerImage = dockerImages["biowdl-input-converter"]
    }

    SampleConfig sampleConfig = read_json(convertSampleConfig.json)

    call calcRegions.CalculateRegions as calculateRegions {
        input:
            referenceFasta = refFasta,
            referenceFastaFai = refFastaFai,
            referenceFastaDict = refFastaDict,
            XNonParRegions = XNonParRegions,
            YNonParRegions = YNonParRegions,
            regions = regions,
            scatterSize = scatterSize,
            scatterSizeMillions = scatterSizeMillions,
            dockerImages = dockerImages
    }

    call chunkedScatter.ScatterRegions as scatterList {
        input:
            inputFile = select_first([regions, refFastaFai]),
            scatterSize = scatterSize,
            scatterSizeMillions = scatterSizeMillions,
            dockerImage = dockerImages["chunked-scatter"]
    }

    # Running sample subworkflow.
    scatter (sample in sampleConfig.samples) {
        String sampleIds = sample.id
        String sampleDir = outputDir + "/samples/" + sample.id + "/"
        call sampleWf.SampleWorkflow as sampleWorkflow {
            input:
                sampleDir = sampleDir,
                sample = sample,
                referenceFasta = refFasta,
                referenceFastaFai = refFastaFai,
                referenceFastaDict = refFastaDict,
                bwaIndex = bwidx,
                bwaMem2Index = bwaMem2Index,
                dbsnpVCF = dbsnpVcf,
                dbsnpVCFIndex = dbsnpVcfIndex,
                adapterForward = adapterForward,
                adapterReverse = adapterReverse,
                useBwaKit = useBwaKit,
                dockerImages = dockerImages,
                scatters = scatterList.scatters,
                bwaThreads = bwaThreads,
                platform = platform,
                umiDeduplication = umiDeduplication,
                collectUmiStats = collectUmiStats
        }

        call variantCallingWorkflow.SingleSampleCalling as singleSampleCalling {
            input:
                bam = sampleWorkflow.recalibratedBam,
                bamIndex = sampleWorkflow.recalibratedBamIndex,
                gender = select_first([sample.gender, "unknown"]),
                sampleName = sample.id,
                outputDir = sampleDir,
                referenceFasta = refFasta,
                referenceFastaFai = refFastaFai,
                referenceFastaDict = refFastaDict,
                dbsnpVCF = dbsnpVcf,
                dbsnpVCFIndex = dbsnpVcfIndex,
                XNonParRegions = calculateRegions.Xregions,
                YNonParRegions = calculateRegions.Yregions,
                statsRegions = regions,
                autosomalRegionScatters = calculateRegions.autosomalRegionScatters,
                gvcf = jointgenotyping,
                mergeVcf = mergeVcfs,
                dockerImages = dockerImages
        }

        if (runSVcalling && defined(bwaIndex)) {
            call structuralVariantCalling.SVcalling as svCalling {
                input:
                    bamFile = sampleWorkflow.markdupBam,
                    bamIndex = sampleWorkflow.markdupBamIndex,
                    referenceFasta = refFasta,
                    referenceFastaFai = refFastaFai,
                    referenceFastaDict = refFastaDict,
                    bwaIndex = select_first([bwaIndex]),
                    sample = sample.id,
                    outputDir = sampleDir,
                    dockerImages = dockerImages
            }
        }
    }

    if (jointgenotyping) {
        call jgwf.JointGenotyping as JointGenotyping {
            input:
                gvcfFiles = flatten(singleSampleCalling.vcfScatters),
                gvcfFilesIndex = flatten(singleSampleCalling.vcfIndexScatters),
                outputDir = outputDir,
                vcfBasename = "multisample",
                referenceFasta = refFasta,
                referenceFastaFai = refFastaFai,
                referenceFastaDict = refFastaDict,
                sampleIds = sampleIds,
                dbsnpVCF = dbsnpVCF,
                dbsnpVCFIndex = dbsnpVCFIndex,
                regions = regions,
                scatterSize = scatterSize,
                dockerImages = dockerImages
        }
    }

    Array[File] allReports = flatten([
        flatten(sampleWorkflow.reports), flatten(singleSampleCalling.reports),
        select_first([JointGenotyping.reports, []])
    ])

    call multiqc.MultiQC as multiqcTask {
        input:
            reports = allReports,
            outDir = outputDir,
            dockerImage = dockerImages["multiqc"]
    }

    output {
        File dockerImagesList = convertDockerImagesFile.json
        File multiqcReport = multiqcTask.multiqcReport
        Array[File] reports = allReports
        File? multiSampleVcf = JointGenotyping.multisampleVcf
        File? multisampleVcfIndex = JointGenotyping.multisampleVcfIndex
        File? multisampleGVcf = JointGenotyping.multisampleGVcf
        File? multisampleGVcfIndex = JointGenotyping.multisampleGVcfIndex
        Array[File] singleSampleVcfs = if jointgenotyping then [] else select_all(singleSampleCalling.outputVcf)
        Array[File] singleSampleVcfsIndex = if jointgenotyping then [] else select_all(singleSampleCalling.outputVcfIndex)
        Array[File] singleSampleGvcfs = if jointgenotyping then select_all(singleSampleCalling.outputVcf) else []
        Array[File] singleSampleGvcfsIndex = if jointgenotyping then select_all(singleSampleCalling.outputVcfIndex) else []
        Array[File] recalibratedBams = sampleWorkflow.recalibratedBam
        Array[File] recalibratedBamIndexes = sampleWorkflow.recalibratedBamIndex
        Array[File] markdupBams = sampleWorkflow.markdupBam
        Array[File] markdupBamIndexes = sampleWorkflow.markdupBamIndex
        Array[File?] cleverVcfs = svCalling.cleverVcf
        Array[File?] matecleverVcfs = svCalling.mateCleverVcf
        Array[File?] mantaVcfs = svCalling.mantaVcf
        Array[File?] smooveVcfs = svCalling.smooveVcf
        Array[File?] dellyVcfs = svCalling.dellyVcf
        Array[File?] gridssVcfs = svCalling.gridssVcf
        Array[File?] gridssVcfIndexes = svCalling.gridssVcfIndex
        Array[Array[File]?] SVunionVcfs = svCalling.unionVCFs
        Array[Array[File]?] SVisecVcfs = svCalling.isecVCFs
        Array[Array[Array[File]]?] SVmodifiedVcfs = svCalling.modifiedVcfs
    }

    parameter_meta {
        # inputs
        sampleConfigFile: {description: "The samplesheet, including sample ids, library ids, readgroup ids and fastq file locations.", category: "required"}
        outputDir: {description: "The directory the output should be written to.", category: "common"}
        referenceFasta: {description: "The reference fasta file.", category: "required" }
        referenceFastaFai: {description: "Fasta index (.fai) file of the reference. Will be created automatically if not present.", category: "common"}
        referenceFastaDict: {description: "Sequence dictionary (.dict) file of the reference.", category: "common"}
        dbsnpVCF: {description: "dbsnp VCF file used for checking known sites.", category: "required"}
        dbsnpVCFIndex: {description: "Index (.tbi) file for the dbsnp VCF. Will be created automatically if not present.", category: "common"}
        jointgenotyping: {description: "Whether to perform jointgenotyping (using HaplotypeCaller to call GVCFs and merge them with GenotypeGVCFs) or not.", category: "common"}
        singleSampleGvcf: {description: "Whether to output single-sample gvcfs.", category: "common"}
        platform: {description: "The platform used for sequencing.", category: "advanced"}
        useBwaKit: {description: "Whether or not BWA kit should be used. If false BWA mem will be used.", category: "advanced"}
        scatterSizeMillions:{description: "Same as scatterSize, but is multiplied by 1000000 to get scatterSize. This allows for setting larger values more easily.", category: "advanced"}
        runSVcalling: {description: "Whether or not Structural-variantcalling should be run.", category: "advanced"}
        bwaIndex: {description: "The BWA index files. When these are provided BWA will be used. Will be created automatically if both bwaIndex and bwaMem2Index are not present.", category: "common"}
        bwaMem2Index: {description: "The bwa-mem2 index files. When these are provided bwa-mem2 will be used.", category: "common"}
        regions: {description: "A bed file describing the regions to call variants for.", category: "common"}
        XNonParRegions: {description: "Bed file with the non-PAR regions of X.", category: "common"}
        YNonParRegions: {description: "Bed file with the non-PAR regions of Y.", category: "common"}
        adapterForward: {description: "The adapter to be removed from the reads first or single end reads.", category: "common"}
        adapterReverse: {description: "The adapter to be removed from the reads second end reads.", category: "common"}
        scatterSize: {description: "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.", category: "advanced"}
        bwaThreads: {description: "The amount of threads for the alignment process.", category: "advanced"}
        dockerImagesFile: {description: "A YAML file describing the docker image used for the tasks. The dockerImages.yml provided with the pipeline is recommended.", category: "advanced"}
        umiDeduplication: {description: "Whether or not UMI based deduplication should be performed.", category: "common"}
        collectUmiStats: {description: "Whether or not UMI deduplication stats should be collected. This will potentially cause a massive increase in memory usage of the deduplication step.", category: "advanced"}

        # outputs
        dockerImagesList: {description: "Json file describing the docker images used by the pipeline."}
        multiqcReport: {description: "The MultiQC report based on all reports from the pipeline"}
        reports: {description: "All reports generated by the pipeline."}
        multiSampleVcf: {description: "The multisample VCF."}
        multisampleVcfIndex: {description: "The index for the multisample vcf."}
        multisampleGVcf: {description: "The multisample GVCF."}
        multisampleGVcfIndex: {description: "The index for the multisample GVCF."}
        singleSampleVcfs: {description: "VCFs for all individual samples."}
        singleSampleVcfsIndex: {description: "Indexes for individual sample VCFs."}
        singleSampleGvcfs: {description: "GVCFs for individual samples."}
        singleSampleGvcfsIndex: {description: "Indexes for individual sample GVCFs."}
        recalibratedBams: {description: "Per sample GATK recalibrated BAM files."}
        recalibratedBamIndexes: {description: "Indexes for per sample recalibrated BAM files."}
        markdupBams: {description: "Per sample BAM files with duplicates marked."}
        markdupBamIndexes: {description: "Indexes for per sample duplicates marked BAM files."}
        cleverVcfs: {description: "Per sample VCF files produced by clever."}
        matecleverVcfs: {description: "Per sample VCF files produced by MateClever"}
        mantaVcfs: {description: "Per sample VCF files produced by manta."}
        dellyVcfs: {description: "Per sample VCF files produced by delly."}
        survivorVcfs: {description: "Per sample VCF files produced by survivor."}
        gridssVcfIndexes: {description: "Indixes for per sample VCF files produced by gridss."}
        SVunionVcfs: {description: "Per sample VCF files produced by SVunion."}
        SVisecVcfs: {description: "Per sample VCF files produced by SVisec."}
        SVmodifiedVcfs: {description: "Per sample VCF files produced by SVmodified."}
        smooveVcfs: {description: "Per sample VCF files produced by smoove."}
        gridssVcfs: {description: "per sample VCF files produced by gridss."}
    }
}