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main.nf
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#!/usr/bin/env nextflow
/*
================================================================================
nf-core/sarek
================================================================================
Started March 2016.
Ported to nf-core May 2019.
--------------------------------------------------------------------------------
nf-core/sarek:
An open-source analysis pipeline to detect germline or somatic variants
from whole genome or targeted sequencing
--------------------------------------------------------------------------------
@Homepage
https://nf-co.re/sarek
--------------------------------------------------------------------------------
@Documentation
https://nf-co.re/sarek/docs
--------------------------------------------------------------------------------
*/
log.info Headers.nf_core(workflow, params.monochrome_logs)
////////////////////////////////////////////////////
/* -- PRINT HELP -- */
////////////////////////////////////////////////////
def json_schema = "$projectDir/nextflow_schema.json"
if (params.help) {
def command = "nextflow run nf-core/sarek --input sample.tsv -profile docker"
log.info NfcoreSchema.params_help(workflow, params, json_schema, command)
exit 0
}
////////////////////////////////////////////////////
/* -- VALIDATE PARAMETERS -- */
////////////////////////////////////////////////////
if (params.validate_params) {
NfcoreSchema.validateParameters(params, json_schema, log)
}
////////////////////////////////////////////////////
/* -- Collect configuration parameters -- */
////////////////////////////////////////////////////
// Check if genome exists in the config file
if (params.genomes && !params.genomes.containsKey(params.genome) && !params.igenomes_ignore) {
exit 1, "The provided genome '${params.genome}' is not available in the iGenomes file. Currently the available genomes are ${params.genomes.keySet().join(", ")}"
} else if (params.genomes && !params.genomes.containsKey(params.genome) && params.igenomes_ignore) {
exit 1, "The provided genome '${params.genome}' is not available in the genomes file. Currently the available genomes are ${params.genomes.keySet().join(", ")}"
}
/*
================================================================================
SET UP CONFIGURATION VARIABLES
================================================================================
*/
stepList = defineStepList()
step = params.step ? params.step.toLowerCase().replaceAll('-', '').replaceAll('_', '') : ''
// Handle deprecation
if (step == 'preprocessing') step = 'mapping'
if (step.contains(',')) exit 1, 'You can choose only one step, see --help for more information'
if (!checkParameterExistence(step, stepList)) exit 1, "Unknown step ${step}, see --help for more information"
toolList = defineToolList()
tools = params.tools ? params.tools.split(',').collect{it.trim().toLowerCase().replaceAll('-', '').replaceAll('_', '')} : []
if (step == 'controlfreec') tools = ['controlfreec']
if (!checkParameterList(tools, toolList)) exit 1, 'Unknown tool(s), see --help for more information'
skipQClist = defineSkipQClist()
skipQC = params.skip_qc ? params.skip_qc == 'all' ? skipQClist : params.skip_qc.split(',').collect{it.trim().toLowerCase().replaceAll('-', '').replaceAll('_', '')} : []
if (!checkParameterList(skipQC, skipQClist)) exit 1, 'Unknown QC tool(s), see --help for more information'
annoList = defineAnnoList()
annotate_tools = params.annotate_tools ? params.annotate_tools.split(',').collect{it.trim().toLowerCase().replaceAll('-', '')} : []
if (!checkParameterList(annotate_tools,annoList)) exit 1, 'Unknown tool(s) to annotate, see --help for more information'
// Check parameters
if ((params.ascat_ploidy && !params.ascat_purity) || (!params.ascat_ploidy && params.ascat_purity)) exit 1, 'Please specify both --ascat_purity and --ascat_ploidy, or none of them'
if (params.umi && !(params.read_structure1 && params.read_structure2)) exit 1, 'Please specify both --read_structure1 and --read_structure2, when using --umi'
// Check AWS batch settings
if (workflow.profile.contains('awsbatch')) {
// AWSBatch sanity checking
if (!params.awsqueue || !params.awsregion) exit 1, 'Specify correct --awsqueue and --awsregion parameters on AWSBatch!'
// Check outdir paths to be S3 buckets if running on AWSBatch
// related: https://github.com/nextflow-io/nextflow/issues/813
if (!params.outdir.startsWith('s3:')) exit 1, 'Outdir not on S3 - specify S3 Bucket to run on AWSBatch!'
// Prevent trace files to be stored on S3 since S3 does not support rolling files.
if (params.tracedir.startsWith('s3:')) exit 1, 'Specify a local tracedir or run without trace! S3 cannot be used for tracefiles.'
}
// MultiQC
// Stage config files
ch_multiqc_config = file("$projectDir/assets/multiqc_config.yaml", checkIfExists: true)
ch_multiqc_custom_config = params.multiqc_config ? Channel.fromPath(params.multiqc_config, checkIfExists: true) : Channel.empty()
ch_output_docs = file("$projectDir/docs/output.md", checkIfExists: true)
ch_output_docs_images = file("$projectDir/docs/images/", checkIfExists: true)
// Handle input
tsvPath = null
if (params.input && (hasExtension(params.input, "tsv") || hasExtension(params.input, "vcf") || hasExtension(params.input, "vcf.gz"))) tsvPath = params.input
if (params.input && (hasExtension(params.input, "vcf") || hasExtension(params.input, "vcf.gz"))) step = "annotate"
save_bam_mapped = params.skip_markduplicates ? true : params.save_bam_mapped ? true : false
// If no input file specified, trying to get TSV files corresponding to step in the TSV directory
// only for steps preparerecalibration, recalibrate, variantcalling and controlfreec
if (!params.input && params.sentieon) {
switch (step) {
case 'mapping': break
case 'recalibrate': tsvPath = "${params.outdir}/Preprocessing/TSV/sentieon_deduped.tsv"; break
case 'variantcalling': tsvPath = "${params.outdir}/Preprocessing/TSV/sentieon_recalibrated.tsv"; break
case 'annotate': break
default: exit 1, "Unknown step ${step}"
}
} else if (!params.input && !params.sentieon && !params.skip_markduplicates) {
switch (step) {
case 'mapping': break
case 'preparerecalibration': tsvPath = "${params.outdir}/Preprocessing/TSV/duplicates_marked_no_table.tsv"; break
case 'recalibrate': tsvPath = "${params.outdir}/Preprocessing/TSV/duplicates_marked.tsv"; break
case 'variantcalling': tsvPath = "${params.outdir}/Preprocessing/TSV/recalibrated.tsv"; break
case 'controlfreec': tsvPath = "${params.outdir}/Preprocessing/TSV/recalibrated.tsv"; break
case 'annotate': break
default: exit 1, "Unknown step ${step}"
}
} else if (!params.input && !params.sentieon && params.skip_markduplicates) {
switch (step) {
case 'mapping': break
case 'preparerecalibration': tsvPath = "${params.outdir}/Preprocessing/TSV/mapped.tsv"; break
case 'recalibrate': tsvPath = "${params.outdir}/Preprocessing/TSV/mapped_no_duplicates_marked.tsv"; break
case 'variantcalling': tsvPath = "${params.outdir}/Preprocessing/TSV/recalibrated.tsv"; break
case 'controlfreec': tsvPath = "${params.outdir}/Preprocessing/TSV/recalibrated.tsv"; break
case 'annotate': break
default: exit 1, "Unknown step ${step}"
}
}
inputSample = Channel.empty()
if (tsvPath) {
tsvFile = file(tsvPath)
switch (step) {
case 'mapping': inputSample = extractFastq(tsvFile); break
case 'preparerecalibration': inputSample = extractBam(tsvFile); break
case 'recalibrate': inputSample = extractRecal(tsvFile); break
case 'variantcalling': inputSample = extractBam(tsvFile); break
case 'controlfreec': inputSample = extractBam(tsvFile); break
case 'annotate': break
default: exit 1, "Unknown step ${step}"
}
} else if (params.input && !hasExtension(params.input, "tsv")) {
log.info "No TSV file"
if (step != 'mapping') exit 1, 'No step other than "mapping" supports a directory as an input'
log.info "Reading ${params.input} directory"
log.warn "[nf-core/sarek] in ${params.input} directory, all fastqs are assuming to be from the same sample, which is assumed to be a germline one"
inputSample = extractFastqFromDir(params.input)
(inputSample, fastqTMP) = inputSample.into(2)
fastqTMP.toList().subscribe onNext: {
if (it.size() == 0) exit 1, "No FASTQ files found in --input directory '${params.input}'"
}
tsvFile = params.input // used in the reports
} else if (tsvPath && step == 'annotate') {
log.info "Annotating ${tsvPath}"
} else if (step == 'annotate') {
log.info "Trying automatic annotation on files in the VariantCalling/ directory"
} else exit 1, 'No sample were defined, see --help'
(genderMap, statusMap, inputSample) = extractInfos(inputSample)
/*
================================================================================
CHECKING REFERENCES
================================================================================
*/
// Initialize each params in params.genomes, catch the command line first if it was defined
// params.fasta has to be the first one
params.fasta = params.genome && !('annotate' in step) ? params.genomes[params.genome].fasta ?: null : null
// The rest can be sorted
params.ac_loci = params.genome && 'ascat' in tools ? params.genomes[params.genome].ac_loci ?: null : null
params.ac_loci_gc = params.genome && 'ascat' in tools ? params.genomes[params.genome].ac_loci_gc ?: null : null
params.bwa = params.genome && params.fasta && 'mapping' in step ? params.genomes[params.genome].bwa ?: null : null
params.chr_dir = params.genome && 'controlfreec' in tools ? params.genomes[params.genome].chr_dir ?: null : null
params.chr_length = params.genome && 'controlfreec' in tools ? params.genomes[params.genome].chr_length ?: null : null
params.dbsnp = params.genome && ('mapping' in step || 'preparerecalibration' in step || 'controlfreec' in tools || 'haplotypecaller' in tools || 'mutect2' in tools || params.sentieon) ? params.genomes[params.genome].dbsnp ?: null : null
params.dbsnp_index = params.genome && params.dbsnp ? params.genomes[params.genome].dbsnp_index ?: null : null
params.dict = params.genome && params.fasta ? params.genomes[params.genome].dict ?: null : null
params.fasta_fai = params.genome && params.fasta ? params.genomes[params.genome].fasta_fai ?: null : null
params.germline_resource = params.genome && 'mutect2' in tools ? params.genomes[params.genome].germline_resource ?: null : null
params.germline_resource_index = params.genome && params.germline_resource ? params.genomes[params.genome].germline_resource_index ?: null : null
params.intervals = params.genome && !('annotate' in step) ? params.genomes[params.genome].intervals ?: null : null
params.known_indels = params.genome && ('mapping' in step || 'preparerecalibration' in step) ? params.genomes[params.genome].known_indels ?: null : null
params.known_indels_index = params.genome && params.known_indels ? params.genomes[params.genome].known_indels_index ?: null : null
params.mappability = params.genome && 'controlfreec' in tools ? params.genomes[params.genome].mappability ?: null : null
params.snpeff_db = params.genome && ('snpeff' in tools || 'merge' in tools) ? params.genomes[params.genome].snpeff_db ?: null : null
params.species = params.genome && ('vep' in tools || 'merge' in tools) ? params.genomes[params.genome].species ?: null : null
params.vep_cache_version = params.genome && ('vep' in tools || 'merge' in tools) ? params.genomes[params.genome].vep_cache_version ?: null : null
params.vep_genome = params.genome && ('vep' in tools || 'merge' in tools) ? params.genomes[params.genome].vep_genome ?: null : null
// Initialize channels with files based on params
ch_ac_loci = params.ac_loci && 'ascat' in tools ? Channel.value(file(params.ac_loci)) : "null"
ch_ac_loci_gc = params.ac_loci_gc && 'ascat' in tools ? Channel.value(file(params.ac_loci_gc)) : "null"
ch_chr_dir = params.chr_dir && 'controlfreec' in tools ? Channel.value(file(params.chr_dir)) : "null"
ch_chr_length = params.chr_length && 'controlfreec' in tools ? Channel.value(file(params.chr_length)) : "null"
ch_dbsnp = params.dbsnp && ('mapping' in step || 'preparerecalibration' in step || 'controlfreec' in tools || 'haplotypecaller' in tools || 'mutect2' in tools || params.sentieon) ? Channel.value(file(params.dbsnp)) : "null"
ch_fasta = params.fasta && !('annotate' in step) ? Channel.value(file(params.fasta)) : "null"
ch_fai = params.fasta_fai && !('annotate' in step) ? Channel.value(file(params.fasta_fai)) : "null"
ch_germline_resource = params.germline_resource && 'mutect2' in tools ? Channel.value(file(params.germline_resource)) : "null"
ch_intervals = params.intervals && !params.no_intervals && !('annotate' in step) ? Channel.value(file(params.intervals)) : "null"
ch_known_indels = params.known_indels && ('mapping' in step || 'preparerecalibration' in step) ? Channel.value(file(params.known_indels)) : "null"
ch_mappability = params.mappability && 'controlfreec' in tools ? Channel.value(file(params.mappability)) : "null"
// Initialize channels with values based on params
ch_snpeff_cache = params.snpeff_cache ? Channel.value(file(params.snpeff_cache)) : "null"
ch_snpeff_db = params.snpeff_db ? Channel.value(params.snpeff_db) : "null"
ch_vep_cache_version = params.vep_cache_version ? Channel.value(params.vep_cache_version) : "null"
ch_vep_cache = params.vep_cache ? Channel.value(file(params.vep_cache)) : "null"
// Optional files, not defined within the params.genomes[params.genome] scope
ch_cadd_indels = params.cadd_indels ? Channel.value(file(params.cadd_indels)) : "null"
ch_cadd_indels_tbi = params.cadd_indels_tbi ? Channel.value(file(params.cadd_indels_tbi)) : "null"
ch_cadd_wg_snvs = params.cadd_wg_snvs ? Channel.value(file(params.cadd_wg_snvs)) : "null"
ch_cadd_wg_snvs_tbi = params.cadd_wg_snvs_tbi ? Channel.value(file(params.cadd_wg_snvs_tbi)) : "null"
ch_pon = params.pon ? Channel.value(file(params.pon)) : "null"
ch_target_bed = params.target_bed ? Channel.value(file(params.target_bed)) : "null"
// Optional values, not defined within the params.genomes[params.genome] scope
ch_read_structure1 = params.read_structure1 ? Channel.value(params.read_structure1) : "null"
ch_read_structure2 = params.read_structure2 ? Channel.value(params.read_structure2) : "null"
////////////////////////////////////////////////////
/* -- PRINT PARAMETER SUMMARY -- */
////////////////////////////////////////////////////
log.info NfcoreSchema.params_summary_log(workflow, params, json_schema)
// Header log info
def summary = [:]
if (workflow.revision) summary['Pipeline Release'] = workflow.revision
summary['Run Name'] = workflow.runName
summary['Max Resources'] = "$params.max_memory memory, $params.max_cpus cpus, $params.max_time time per job"
if (workflow.containerEngine) summary['Container'] = "$workflow.containerEngine - $workflow.container"
summary['Output dir'] = params.outdir
summary['Launch dir'] = workflow.launchDir
summary['Working dir'] = workflow.workDir
summary['Script dir'] = workflow.projectDir
summary['User'] = workflow.userName
if (workflow.profile.contains('awsbatch')) {
summary['AWS Region'] = params.awsregion
summary['AWS Queue'] = params.awsqueue
summary['AWS CLI'] = params.awscli
}
summary['Input'] = params.input
summary['Step'] = step
summary['Genome'] = params.genome
if (params.no_intervals && step != 'annotate') summary['Intervals'] = 'Do not use'
summary['Nucleotides/s'] = params.nucleotides_per_second
if (params.sentieon) summary['Sention'] = "Using Sentieon for Preprocessing and/or Variant Calling"
if (params.skip_qc) summary['QC tools skipped'] = skipQC.join(', ')
if (params.target_bed) summary['Target BED'] = params.target_bed
if (params.tools) summary['Tools'] = tools.join(', ')
if (params.trim_fastq || params.split_fastq) summary['Modify fastqs (trim/split)'] = ""
if (params.trim_fastq) {
summary['Fastq trim'] = "Fastq trim selected"
summary['Trim R1'] = "${params.clip_r1} bp"
summary['Trim R2'] = "${params.clip_r2} bp"
summary["Trim 3' R1"] = "${params.three_prime_clip_r1} bp"
summary["Trim 3' R2"] = "${params.three_prime_clip_r2} bp"
summary['NextSeq Trim'] = "${params.trim_nextseq} bp"
summary['Saved Trimmed Fastq'] = params.save_trimmed ? 'Yes' : 'No'
}
if (params.split_fastq) summary['Reads in fastq'] = params.split_fastq
summary['MarkDuplicates'] = "Options"
summary['Java options'] = params.markdup_java_options
summary['GATK Spark'] = params.use_gatk_spark ? 'Yes' : 'No'
summary['Save BAMs mapped'] = params.save_bam_mapped ? 'Yes' : 'No'
summary['Skip MarkDuplicates'] = params.skip_markduplicates ? 'Yes' : 'No'
if ('ascat' in tools) {
summary['ASCAT'] = "Options"
if (params.ascat_purity) summary['purity'] = params.ascat_purity
if (params.ascat_ploidy) summary['ploidy'] = params.ascat_ploidy
}
if ('controlfreec' in tools) {
summary['Control-FREEC'] = "Options"
if (params.cf_coeff) summary['coefficientOfVariation'] = params.cf_coeff
if (params.cf_contamination) summary['contamination'] = params.cf_contamination
if (params.cf_contamination_adjustment) summary['contaminationAdjustment'] = params.cf_contamination_adjustment
if (params.cf_ploidy) summary['ploidy'] = params.cf_ploidy
if (params.cf_window) summary['window'] = params.cf_window
}
if ('haplotypecaller' in tools) summary['GVCF'] = params.generate_gvcf ? 'Yes' : 'No'
if ('strelka' in tools && 'manta' in tools) summary['Strelka BP'] = params.no_strelka_bp ? 'No' : 'Yes'
if (params.pon && ('mutect2' in tools || (params.sentieon && 'tnscope' in tools))) summary['Panel of normals'] = params.pon
if (params.annotate_tools) summary['Tools to annotate'] = annotate_tools.join(', ')
if (params.annotation_cache) {
summary['Annotation cache'] = "Enabled"
if (params.snpeff_cache) summary['snpEff cache'] = params.snpeff_cache
if (params.vep_cache) summary['VEP cache'] = params.vep_cache
}
if (params.cadd_cache) {
summary['CADD cache'] = "Enabled"
if (params.cadd_indels) summary['CADD indels'] = params.cadd_indels
if (params.cadd_wg_snvs) summary['CADD wg snvs'] = params.cadd_wg_snvs
}
if (params.genesplicer) summary['genesplicer'] = "Enabled"
if (params.igenomes_base && !params.igenomes_ignore) summary['AWS iGenomes base'] = params.igenomes_base
if (params.igenomes_ignore) summary['AWS iGenomes'] = "Do not use"
if (params.genomes_base && !params.igenomes_ignore) summary['Genomes base'] = params.genomes_base
summary['Save Reference'] = params.save_reference ? 'Yes' : 'No'
if (params.ac_loci) summary['Loci'] = params.ac_loci
if (params.ac_loci_gc) summary['Loci GC'] = params.ac_loci_gc
if (params.bwa) summary['BWA indexes'] = params.bwa
if (params.chr_dir) summary['Chromosomes'] = params.chr_dir
if (params.chr_length) summary['Chromosomes length'] = params.chr_length
if (params.dbsnp) summary['dbsnp'] = params.dbsnp
if (params.dbsnp_index) summary['dbsnpIndex'] = params.dbsnp_index
if (params.dict) summary['dict'] = params.dict
if (params.fasta) summary['fasta reference'] = params.fasta
if (params.fasta_fai) summary['fasta index'] = params.fasta_fai
if (params.germline_resource) summary['germline resource'] = params.germline_resource
if (params.germline_resource_index) summary['germline resource index'] = params.germline_resource_index
if (params.intervals) summary['intervals'] = params.intervals
if (params.known_indels) summary['known indels'] = params.known_indels
if (params.known_indels_index) summary['known indels index'] = params.known_indels_index
if (params.mappability) summary['Mappability'] = params.mappability
if (params.snpeff_cache) summary['snpEff cache'] = params.snpeff_cache
if (params.snpeff_db) summary['snpEff DB'] = params.snpeff_db
if (params.species) summary['species'] = params.species
if (params.vep_cache) summary['VEP cache'] = params.vep_cache
if (params.vep_cache_version) summary['VEP cache version'] = params.vep_cache_version
summary['Output dir'] = params.outdir
summary['Publish dir mode'] = params.publish_dir_mode
if (params.sequencing_center) summary['Sequenced by'] = params.sequencing_center
summary['Launch dir'] = workflow.launchDir
summary['Working dir'] = workflow.workDir
summary['Script dir'] = workflow.projectDir
summary['User'] = workflow.userName
if (params.multiqc_config) summary['MultiQC config'] = params.multiqc_config
summary['Config Profile'] = workflow.profile
if (params.config_profile_description) summary['Config Description'] = params.config_profile_description
if (params.config_profile_contact) summary['Config Contact'] = params.config_profile_contact
if (params.config_profile_url) summary['Config URL'] = params.config_profile_url
summary['Config Files'] = workflow.configFiles.join(', ')
if (workflow.profile.contains('awsbatch')) {
summary['AWS Region'] = params.awsregion
summary['AWS Queue'] = params.awsqueue
summary['AWS CLI'] = params.awscli
}
if (params.email || params.email_on_fail) {
summary['E-mail Address'] = params.email
summary['E-mail on failure'] = params.email_on_fail
summary['MultiQC maxsize'] = params.max_multiqc_email_size
}
log.info summary.collect { k,v -> "${k.padRight(18)}: $v" }.join("\n")
log.info "-\033[2m--------------------------------------------------\033[0m-"
if ('mutect2' in tools && !(params.pon)) log.warn "[nf-core/sarek] Mutect2 was requested, but as no panel of normals were given, results will not be optimal"
if ('mutect2' in tools && !(params.germline_resource)) log.warn "[nf-core/sarek] Mutect2 was requested, but as no germline resource was given, results will not be optimal"
if (params.sentieon) log.warn "[nf-core/sarek] Sentieon will be used, only works if Sentieon is available where nf-core/sarek is run"
// Check the hostnames against configured profiles
checkHostname()
Channel.from(summary.collect{ [it.key, it.value] })
.map { k,v -> "<dt>$k</dt><dd><samp>${v ?: '<span style=\"color:#999999;\">N/A</a>'}</samp></dd>" }
.reduce { a, b -> return [a, b].join("\n ") }
.map { x -> """
id: 'sarek-summary'
description: " - this information is collected when the pipeline is started."
section_name: 'nf-core/sarek Workflow Summary'
section_href: 'https://github.com/nf-core/sarek'
plot_type: 'html'
data: |
<dl class=\"dl-horizontal\">
$x
</dl>
""".stripIndent() }
.set { ch_workflow_summary }
// Parse software version numbers
process get_software_versions {
publishDir "${params.outdir}/pipeline_info", mode: params.publish_dir_mode,
saveAs: { filename ->
if (filename.indexOf('.csv') > 0) filename
else null
}
output:
file 'software_versions_mqc.yaml' into ch_software_versions_yaml
file 'software_versions.csv'
when: !('versions' in skipQC)
script:
aligner = params.aligner == "bwa-mem2" ? "bwa-mem2" : "bwa"
"""
alleleCounter --version &> v_allelecount.txt 2>&1 || true
bcftools --version &> v_bcftools.txt 2>&1 || true
${aligner} version &> v_bwa.txt 2>&1 || true
cnvkit.py version &> v_cnvkit.txt 2>&1 || true
configManta.py --version &> v_manta.txt 2>&1 || true
configureStrelkaGermlineWorkflow.py --version &> v_strelka.txt 2>&1 || true
echo "${workflow.manifest.version}" &> v_pipeline.txt 2>&1 || true
echo "${workflow.nextflow.version}" &> v_nextflow.txt 2>&1 || true
snpEff -version &> v_snpeff.txt 2>&1 || true
fastqc --version &> v_fastqc.txt 2>&1 || true
freebayes --version &> v_freebayes.txt 2>&1 || true
freec &> v_controlfreec.txt 2>&1 || true
gatk ApplyBQSR --help &> v_gatk.txt 2>&1 || true
msisensor &> v_msisensor.txt 2>&1 || true
multiqc --version &> v_multiqc.txt 2>&1 || true
qualimap --version &> v_qualimap.txt 2>&1 || true
R --version &> v_r.txt 2>&1 || true
R -e "library(ASCAT); help(package='ASCAT')" &> v_ascat.txt 2>&1 || true
samtools --version &> v_samtools.txt 2>&1 || true
tiddit &> v_tiddit.txt 2>&1 || true
trim_galore -v &> v_trim_galore.txt 2>&1 || true
vcftools --version &> v_vcftools.txt 2>&1 || true
vep --help &> v_vep.txt 2>&1 || true
scrape_software_versions.py &> software_versions_mqc.yaml
"""
}
ch_software_versions_yaml = ch_software_versions_yaml.dump(tag:'SOFTWARE VERSIONS')
/*
================================================================================
BUILDING INDEXES
================================================================================
*/
// And then initialize channels based on params or indexes that were just built
process BuildBWAindexes {
tag "${fasta}"
publishDir params.outdir, mode: params.publish_dir_mode,
saveAs: {params.save_reference ? "reference_genome/BWAIndex/${it}" : null }
input:
file(fasta) from ch_fasta
output:
file("${fasta}.*") into bwa_built
when: !(params.bwa) && params.fasta && 'mapping' in step
script:
aligner = params.aligner == "bwa-mem2" ? "bwa-mem2" : "bwa"
"""
${aligner} index ${fasta}
"""
}
ch_bwa = params.bwa ? Channel.value(file(params.bwa)) : bwa_built
process BuildDict {
tag "${fasta}"
publishDir params.outdir, mode: params.publish_dir_mode,
saveAs: {params.save_reference ? "reference_genome/${it}" : null }
input:
file(fasta) from ch_fasta
output:
file("${fasta.baseName}.dict") into dictBuilt
when: !(params.dict) && params.fasta && !('annotate' in step) && !('controlfreec' in step)
script:
"""
gatk --java-options "-Xmx${task.memory.toGiga()}g" \
CreateSequenceDictionary \
--REFERENCE ${fasta} \
--OUTPUT ${fasta.baseName}.dict
"""
}
ch_dict = params.dict ? Channel.value(file(params.dict)) : dictBuilt
process BuildFastaFai {
tag "${fasta}"
publishDir params.outdir, mode: params.publish_dir_mode,
saveAs: {params.save_reference ? "reference_genome/${it}" : null }
input:
file(fasta) from ch_fasta
output:
file("${fasta}.fai") into fai_built
when: !(params.fasta_fai) && params.fasta && !('annotate' in step)
script:
"""
samtools faidx ${fasta}
"""
}
ch_fai = params.fasta_fai ? Channel.value(file(params.fasta_fai)) : fai_built
process BuildDbsnpIndex {
tag "${dbsnp}"
publishDir params.outdir, mode: params.publish_dir_mode,
saveAs: {params.save_reference ? "reference_genome/${it}" : null }
input:
file(dbsnp) from ch_dbsnp
output:
file("${dbsnp}.tbi") into dbsnp_tbi
when: !(params.dbsnp_index) && params.dbsnp && ('mapping' in step || 'preparerecalibration' in step || 'controlfreec' in tools || 'haplotypecaller' in tools || 'mutect2' in tools || 'tnscope' in tools)
script:
"""
tabix -p vcf ${dbsnp}
"""
}
ch_dbsnp_tbi = params.dbsnp ? params.dbsnp_index ? Channel.value(file(params.dbsnp_index)) : dbsnp_tbi : "null"
process BuildGermlineResourceIndex {
tag "${germlineResource}"
publishDir params.outdir, mode: params.publish_dir_mode,
saveAs: {params.save_reference ? "reference_genome/${it}" : null }
input:
file(germlineResource) from ch_germline_resource
output:
file("${germlineResource}.tbi") into germline_resource_tbi
when: !(params.germline_resource_index) && params.germline_resource && 'mutect2' in tools
script:
"""
tabix -p vcf ${germlineResource}
"""
}
ch_germline_resource_tbi = params.germline_resource ? params.germline_resource_index ? Channel.value(file(params.germline_resource_index)) : germline_resource_tbi : "null"
process BuildKnownIndelsIndex {
tag "${knownIndels}"
publishDir params.outdir, mode: params.publish_dir_mode,
saveAs: {params.save_reference ? "reference_genome/${it}" : null }
input:
each file(knownIndels) from ch_known_indels
output:
file("${knownIndels}.tbi") into known_indels_tbi
when: !(params.known_indels_index) && params.known_indels && ('mapping' in step || 'preparerecalibration' in step)
script:
"""
tabix -p vcf ${knownIndels}
"""
}
ch_known_indels_tbi = params.known_indels ? params.known_indels_index ? Channel.value(file(params.known_indels_index)) : known_indels_tbi.collect() : "null"
process BuildPonIndex {
tag "${pon}"
publishDir params.outdir, mode: params.publish_dir_mode,
saveAs: {params.save_reference ? "reference_genome/${it}" : null }
input:
file(pon) from ch_pon
output:
file("${pon}.tbi") into pon_tbi
when: !(params.pon_index) && params.pon && ('tnscope' in tools || 'mutect2' in tools)
script:
"""
tabix -p vcf ${pon}
"""
}
ch_pon_tbi = params.pon ? params.pon_index ? Channel.value(file(params.pon_index)) : pon_tbi : "null"
process BuildIntervals {
tag "${fastaFai}"
publishDir params.outdir, mode: params.publish_dir_mode,
saveAs: {params.save_reference ? "reference_genome/${it}" : null }
input:
file(fastaFai) from ch_fai
output:
file("${fastaFai.baseName}.bed") into intervalBuilt
when: !(params.intervals) && !('annotate' in step) && !('controlfreec' in step)
script:
"""
awk -v FS='\t' -v OFS='\t' '{ print \$1, \"0\", \$2 }' ${fastaFai} > ${fastaFai.baseName}.bed
"""
}
ch_intervals = params.no_intervals ? "null" : params.intervals && !('annotate' in step) ? Channel.value(file(params.intervals)) : intervalBuilt
/*
================================================================================
PREPROCESSING
================================================================================
*/
// STEP 0: CREATING INTERVALS FOR PARALLELIZATION (PREPROCESSING AND VARIANT CALLING)
process CreateIntervalBeds {
tag "${intervals}"
input:
file(intervals) from ch_intervals
output:
file '*.bed' into bedIntervals mode flatten
when: (!params.no_intervals) && step != 'annotate'
script:
// If the interval file is BED format, the fifth column is interpreted to
// contain runtime estimates, which is then used to combine short-running jobs
if (hasExtension(intervals, "bed"))
"""
awk -vFS="\t" '{
t = \$5 # runtime estimate
if (t == "") {
# no runtime estimate in this row, assume default value
t = (\$3 - \$2) / ${params.nucleotides_per_second}
}
if (name == "" || (chunk > 600 && (chunk + t) > longest * 1.05)) {
# start a new chunk
name = sprintf("%s_%d-%d.bed", \$1, \$2+1, \$3)
chunk = 0
longest = 0
}
if (t > longest)
longest = t
chunk += t
print \$0 > name
}' ${intervals}
"""
else if (hasExtension(intervals, "interval_list"))
"""
grep -v '^@' ${intervals} | awk -vFS="\t" '{
name = sprintf("%s_%d-%d", \$1, \$2, \$3);
printf("%s\\t%d\\t%d\\n", \$1, \$2-1, \$3) > name ".bed"
}'
"""
else
"""
awk -vFS="[:-]" '{
name = sprintf("%s_%d-%d", \$1, \$2, \$3);
printf("%s\\t%d\\t%d\\n", \$1, \$2-1, \$3) > name ".bed"
}' ${intervals}
"""
}
bedIntervals = bedIntervals
.map { intervalFile ->
def duration = 0.0
for (line in intervalFile.readLines()) {
final fields = line.split('\t')
if (fields.size() >= 5) duration += fields[4].toFloat()
else {
start = fields[1].toInteger()
end = fields[2].toInteger()
duration += (end - start) / params.nucleotides_per_second
}
}
[duration, intervalFile]
}.toSortedList({ a, b -> b[0] <=> a[0] })
.flatten().collate(2)
.map{duration, intervalFile -> intervalFile}
bedIntervals = bedIntervals.dump(tag:'bedintervals')
if (params.no_intervals && step != 'annotate') {
file("${params.outdir}/no_intervals.bed").text = "no_intervals\n"
bedIntervals = Channel.from(file("${params.outdir}/no_intervals.bed"))
}
(intBaseRecalibrator, intApplyBQSR, intHaplotypeCaller, intFreebayesSingle, intMpileup, bedIntervalsSingle, bedIntervalsPair) = bedIntervals.into(7)
// PREPARING CHANNELS FOR PREPROCESSING AND QC
inputBam = Channel.create()
inputPairReads = Channel.create()
if (step in ['preparerecalibration', 'recalibrate', 'variantcalling', 'controlfreec', 'annotate']) {
inputBam.close()
inputPairReads.close()
} else inputSample.choice(inputPairReads, inputBam) {hasExtension(it[3], "bam") ? 1 : 0}
(inputBam, inputBamFastQC) = inputBam.into(2)
// Removing inputFile2 which is null in case of uBAM
inputBamFastQC = inputBamFastQC.map {
idPatient, idSample, idRun, inputFile1, inputFile2 ->
[idPatient, idSample, idRun, inputFile1]
}
if (params.split_fastq){
inputPairReads = inputPairReads
// newly splitfastq are named based on split, so the name is easier to catch
.splitFastq(by: params.split_fastq, compress:true, file:"split", pe:true)
.map {idPatient, idSample, idRun, reads1, reads2 ->
// The split fastq read1 is the 4th element (indexed 3) its name is split_3
// The split fastq read2's name is split_4
// It's followed by which split it's acutally based on the mother fastq file
// Index start at 1
// Extracting the index to get a new IdRun
splitIndex = reads1.fileName.toString().minus("split_3.").minus(".gz")
newIdRun = idRun + "_" + splitIndex
// Giving the files a new nice name
newReads1 = file("${idSample}_${newIdRun}_R1.fastq.gz")
newReads2 = file("${idSample}_${newIdRun}_R2.fastq.gz")
[idPatient, idSample, newIdRun, reads1, reads2]}
}
inputPairReads = inputPairReads.dump(tag:'INPUT')
(inputPairReads, inputPairReadsTrimGalore, inputPairReadsFastQC, inputPairReadsUMI) = inputPairReads.into(4)
if (params.umi) inputPairReads.close()
else inputPairReadsUMI.close()
if (params.trim_fastq) inputPairReads.close()
else inputPairReadsTrimGalore.close()
// STEP 0.5: QC ON READS
// TODO: Use only one process for FastQC for FASTQ files and uBAM files
// FASTQ and uBAM files are renamed based on the sample name
process FastQCFQ {
label 'FastQC'
label 'cpus_2'
tag "${idPatient}-${idRun}"
publishDir "${params.outdir}/Reports/${idSample}/FastQC/${idSample}_${idRun}", mode: params.publish_dir_mode
input:
set idPatient, idSample, idRun, file("${idSample}_${idRun}_R1.fastq.gz"), file("${idSample}_${idRun}_R2.fastq.gz") from inputPairReadsFastQC
output:
file("*.{html,zip}") into fastQCFQReport
when: !('fastqc' in skipQC)
script:
"""
fastqc -t 2 -q ${idSample}_${idRun}_R1.fastq.gz ${idSample}_${idRun}_R2.fastq.gz
"""
}
process FastQCBAM {
label 'FastQC'
label 'cpus_2'
tag "${idPatient}-${idRun}"
publishDir "${params.outdir}/Reports/${idSample}/FastQC/${idSample}_${idRun}", mode: params.publish_dir_mode
input:
set idPatient, idSample, idRun, file("${idSample}_${idRun}.bam") from inputBamFastQC
output:
file("*.{html,zip}") into fastQCBAMReport
when: !('fastqc' in skipQC)
script:
"""
fastqc -t 2 -q ${idSample}_${idRun}.bam
"""
}
fastQCReport = fastQCFQReport.mix(fastQCBAMReport)
fastQCReport = fastQCReport.dump(tag:'FastQC')
process TrimGalore {
label 'TrimGalore'
tag "${idPatient}-${idRun}"
publishDir "${params.outdir}/Reports/${idSample}/TrimGalore/${idSample}_${idRun}", mode: params.publish_dir_mode,
saveAs: {filename ->
if (filename.indexOf("_fastqc") > 0) "FastQC/$filename"
else if (filename.indexOf("trimming_report.txt") > 0) "logs/$filename"
else if (params.save_trimmed) filename
else null
}
input:
set idPatient, idSample, idRun, file("${idSample}_${idRun}_R1.fastq.gz"), file("${idSample}_${idRun}_R2.fastq.gz") from inputPairReadsTrimGalore
output:
file("*.{html,zip,txt}") into trimGaloreReport
set idPatient, idSample, idRun, file("${idSample}_${idRun}_R1_val_1.fq.gz"), file("${idSample}_${idRun}_R2_val_2.fq.gz") into outputPairReadsTrimGalore
when: params.trim_fastq
script:
// Calculate number of --cores for TrimGalore based on value of task.cpus
// See: https://github.com/FelixKrueger/TrimGalore/blob/master/Changelog.md#version-060-release-on-1-mar-2019
// See: https://github.com/nf-core/atacseq/pull/65
def cores = 1
if (task.cpus) {
cores = (task.cpus as int) - 4
if (cores < 1) cores = 1
if (cores > 4) cores = 4
}
c_r1 = params.clip_r1 > 0 ? "--clip_r1 ${params.clip_r1}" : ''
c_r2 = params.clip_r2 > 0 ? "--clip_r2 ${params.clip_r2}" : ''
tpc_r1 = params.three_prime_clip_r1 > 0 ? "--three_prime_clip_r1 ${params.three_prime_clip_r1}" : ''
tpc_r2 = params.three_prime_clip_r2 > 0 ? "--three_prime_clip_r2 ${params.three_prime_clip_r2}" : ''
nextseq = params.trim_nextseq > 0 ? "--nextseq ${params.trim_nextseq}" : ''
"""
trim_galore \
--cores ${cores} \
--paired \
--fastqc \
--gzip \
${c_r1} ${c_r2} \
${tpc_r1} ${tpc_r2} \
${nextseq} \
${idSample}_${idRun}_R1.fastq.gz ${idSample}_${idRun}_R2.fastq.gz
mv *val_1_fastqc.html "${idSample}_${idRun}_R1.trimmed_fastqc.html"
mv *val_2_fastqc.html "${idSample}_${idRun}_R2.trimmed_fastqc.html"
mv *val_1_fastqc.zip "${idSample}_${idRun}_R1.trimmed_fastqc.zip"
mv *val_2_fastqc.zip "${idSample}_${idRun}_R2.trimmed_fastqc.zip"
"""
}
/*
================================================================================
UMIs PROCESSING
================================================================================
*/
// UMI - STEP 1 - ANNOTATE
// the process needs to convert fastq to unmapped bam
// and while doing the conversion, tag the bam field RX with the UMI sequence
process UMIFastqToBAM {
publishDir "${params.outdir}/Reports/${idSample}/UMI/${idSample}_${idRun}", mode: params.publish_dir_mode
input:
set idPatient, idSample, idRun, file("${idSample}_${idRun}_R1.fastq.gz"), file("${idSample}_${idRun}_R2.fastq.gz") from inputPairReadsUMI
val read_structure1 from ch_read_structure1
val read_structure2 from ch_read_structure2
output:
tuple val(idPatient), val(idSample), val(idRun), file("${idSample}_umi_converted.bam") into umi_converted_bams_ch
when: params.umi
// tmp folder for fgbio might be solved more elengantly?
script:
"""
mkdir tmp
fgbio --tmp-dir=${PWD}/tmp \
FastqToBam \
-i "${idSample}_${idRun}_R1.fastq.gz" "${idSample}_${idRun}_R2.fastq.gz" \
-o "${idSample}_umi_converted.bam" \
--read-structures ${read_structure1} ${read_structure2} \
--sample ${idSample} \
--library ${idSample}
"""
}
// UMI - STEP 2 - MAP THE BAM FILE
// this is necessary because the UMI groups are created based on
// mapping position + same UMI tag
process UMIMapBamFile {
input:
set idPatient, idSample, idRun, file(convertedBam) from umi_converted_bams_ch
file(bwaIndex) from ch_bwa
file(fasta) from ch_fasta
file(fastaFai) from ch_fai
output:
tuple val(idPatient), val(idSample), val(idRun), file("${idSample}_umi_unsorted.bam") into umi_aligned_bams_ch
when: params.umi
script:
aligner = params.aligner == "bwa-mem2" ? "bwa-mem2" : "bwa"
"""
samtools bam2fq -T RX ${convertedBam} | \
${aligner} mem -p -t ${task.cpus} -C -M -R \"@RG\\tID:${idSample}\\tSM:${idSample}\\tPL:Illumina\" \
${fasta} - | \
samtools view -bS - > ${idSample}_umi_unsorted.bam
"""
}
// UMI - STEP 3 - GROUP READS BY UMIs
// We have chose the Adjacency method, following the nice paper and blog explanation integrated in both
// UMItools and FGBIO
// https://cgatoxford.wordpress.com/2015/08/14/unique-molecular-identifiers-the-problem-the-solution-and-the-proof/
// alternatively we can define this as input for the user to choose from
process GroupReadsByUmi {
publishDir "${params.outdir}/Reports/${idSample}/UMI/${idSample}_${idRun}", mode: params.publish_dir_mode
input:
set idPatient, idSample, idRun, file(alignedBam) from umi_aligned_bams_ch
output:
file("${idSample}_umi_histogram.txt") into umi_histogram_ch
tuple val(idPatient), val(idSample), val(idRun), file("${idSample}_umi-grouped.bam") into umi_grouped_bams_ch
when: params.umi
script:
"""
mkdir tmp
samtools view -h ${alignedBam} | \
samblaster -M --addMateTags | \
samtools view -Sb - >${idSample}_unsorted_tagged.bam
fgbio --tmp-dir=${PWD}/tmp \
GroupReadsByUmi \
-s Adjacency \
-i ${idSample}_unsorted_tagged.bam \
-o ${idSample}_umi-grouped.bam \
-f ${idSample}_umi_histogram.txt
"""
}
// UMI - STEP 4 - CALL MOLECULAR CONSENSUS
// Now that the reads are organised by UMI groups a molecular consensus will be created
// the resulting bam file will be again unmapped and therefore can be fed into the
// existing workflow from the step mapping
process CallMolecularConsensusReads {
publishDir "${params.outdir}/Reports/${idSample}/UMI/${idSample}_${idRun}", mode: params.publish_dir_mode
input:
set idPatient, idSample, idRun, file(groupedBamFile) from umi_grouped_bams_ch
output:
tuple val(idPatient), val(idSample), val(idRun), file("${idSample}_umi-consensus.bam"), val("null") into consensus_bam_ch
when: params.umi
script:
"""
mkdir tmp
fgbio --tmp-dir=${PWD}/tmp \