sample.wdl

version 1.0

# Copyright (c) 2020 Leiden University Medical Center
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# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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import "structs.wdl" as structs
import "QC/QC.wdl" as qc
import "tasks/centrifuge.wdl" as centrifuge

workflow SampleWorkflow {
    input {
        Sample sample
        Array[File]+ centrifugeIndex
        String outputDirectory = "."
        Boolean runQc = true

        Map[String, String] dockerImages
    }

    meta {allowNestedInputs: true}

    Array[Readgroup] readgroups = sample.readgroups

    scatter (readgroup in readgroups) {
        String readgroupName = "~{sample.id}-~{readgroup.lib_id}-~{readgroup.id}"
        String readgroupIdentifier = readgroup.lib_id + "-" + readgroup.id
        Boolean pairedEnd = defined(readgroup.R2)

        if (runQc) {
            call qc.QC as qualityControl {
                input:
                    read1 = readgroup.R1,
                    read2 = readgroup.R2,
                    readgroupName = readgroupName,
                    outputDir = outputDirectory + "/" + readgroupIdentifier,
                    dockerImages = dockerImages
            }
        }

        File firstSequenceFile = select_first([qualityControl.qcRead1, readgroup.R1])
        if (pairedEnd) {
            File? secondSequenceFile = select_first([qualityControl.qcRead2, readgroup.R2])
        }
        Array[File] qualityReports = select_first([qualityControl.reports, []])
    }

    call centrifuge.Classify as centrifuge {
        input:
            outputPrefix = outputDirectory + "/" + sample.id,
            inputFormat = if (runQc) then "fastq" else "fasta",
            indexFiles = centrifugeIndex,
            read1 = firstSequenceFile,
            read2 = select_all(secondSequenceFile),
            dockerImage = dockerImages["centrifuge"]
    }

    call centrifuge.KReport as kReport {
        input:
            classification = centrifuge.classification,
            outputPrefix = outputDirectory + "/" + sample.id,
            indexFiles = centrifugeIndex,
            dockerImage = dockerImages["centrifuge"]
    }

    call centrifuge.KTimportTaxonomy as krona {
        input:
            inputFile = centrifuge.classification,
            outputPrefix = outputDirectory + "/" + sample.id,
            dockerImage = dockerImages["krona"]
    }

    output {
        Array[File] workflowReports = flatten(qualityReports)
        File centrifugeClassification = centrifuge.classification
        File centrifugeReport = centrifuge.report
        File centrifugeKReport = kReport.KrakenReport
        File kronaPlot = krona.kronaPlot
    }

    parameter_meta {
        # inputs
        sample: {description: "The sample data.", category: "required"}
        centrifugeIndex: {description: "The files of the index for the reference genomes.", category: "required"}
        outputDirectory: {description: "The directory to which the outputs will be written.", category: "common"}
        runQc: {description: "Run the QC pipeline when the input is fastq.", category: "common"}
        dockerImages: {description: "The docker image used for this workflow. Changing this may result in errors which the developers may choose not to address.", category: "advanced"}

        # outputs
        workflowReports: {description: "The qc workflow file(s)."}
        centrifugeClassification: {description: "File(s) with the classification results."}
        centrifugeReport: {description: "File(s) with a classification summary."}
        centrifugeKReport: {description: "File(s) with kraken style report(s)."}
        kronaPlot: {description: "Krona taxonomy plot file(s)."}
    }
}