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main.nf
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// NGS580 Target exome analysis for 580 gene panel
import java.nio.file.Files;
import java.text.SimpleDateFormat;
import groovy.json.JsonSlurper;
def jsonSlurper = new JsonSlurper()
def workflowTimestamp = "${workflow.start.format('yyyy-MM-dd-HH-mm-ss')}"
def username = System.getProperty("user.name")
String localhostname = java.net.InetAddress.getLocalHost().getHostName();
Date now = new Date()
SimpleDateFormat timestamp = new SimpleDateFormat("yyyy-MM-dd-HH-mm-ss")
def currentDirPath = new File(System.getProperty("user.dir")).getCanonicalPath()
Process uname_proc = 'uname'.execute()
def uname = "${uname_proc.text.trim()}"
def NXF_PIDFILE = ".nextflow.pid"
if(uname == "Linux"){
// /proc/self only works on Linux
int pid = Integer.parseInt(new File("/proc/self").getCanonicalFile().getName())
File pid_file = new File("${NXF_PIDFILE}")
pid_file.write("${pid}\n")
}
// ~~~~~~~~~~ CONFIGURATION ~~~~~~~~~~ //
// configure pipeline settings
// order of evaluation
// 1. uses CLI passed arg in 'params'
// 2. uses nextflow.config arg in 'params'
// 3. uses values from config.json
// 4. uses default value
// default values; overriden by nextflow.config and CLI
params.configFile = "config.json"
params.reportDir = "report"
params.outputDir = "output"
params.ref_dir = "ref"
params.nxf_completion_log = ".nextflow.completion.log"
params.GIT_CURRENT_BRANCH = "none"
params.GIT_CURRENT_COMMIT = "none"
params.GIT_CURRENT_TAG = "none"
params.GIT_RECENT_TAG = "none"
// default config values
def defaultParams = [:]
defaultParams.runID = "NGS580_run"
defaultParams.workflowLabel = "NGS580"
defaultParams.numTargetSplitLines = 50
defaultParams.targetsBed = "targets/targets.580.bed"
defaultParams.targetsAnnotatedBed = "targets/targets.annotated.580.bed"
defaultParams.projectDir = "${workflow.projectDir}"
defaultParams.samplesheet = "samples.analysis.tsv"
defaultParams.SeraCareSelectedTsv = "data/SeraCare-selected-variants.tsv"
defaultParams.SeraCareErrorRate = 0.02
defaultParams.CNVPool = "ref/CNV-Pool/CNV-Pool.580.cnn"
defaultParams.HapMapBam = "ref/HapMap-Pool/HapMap-pool.bam"
defaultParams.HapMapBai = "ref/HapMap-Pool/HapMap-pool.bam.bai"
// load the JSON config, if present
def externalConfig
def externalConfigFile_obj = new File("${params.configFile}")
if ( externalConfigFile_obj.exists() ) {
log.info("Loading configs from ${params.configFile}")
String externalConfigJSON = externalConfigFile_obj.text
externalConfig = jsonSlurper.parseText(externalConfigJSON)
}
// add and overwrite all values in defaultParams with items from config
if( externalConfig ){
log.info("Updating with configs from ${params.configFile}")
// overwrite existing default params with JSON config values
defaultParams.keySet().each { key ->
if( externalConfig.containsKey(key) ){
defaultParams[key] = externalConfig[key]
}
}
// append the missing JSON configs to default params; doesn't overwrite
externalConfig.keySet().each { key ->
if( ! defaultParams.containsKey(key) ){
defaultParams[key] = externalConfig[key]
}
}
}
// add all the entries to params; wont overwrite existing entries from CLI or nextflow.config
params << defaultParams
// set variables to use throughout the pipeline
def numTargetSplitLines = params.numTargetSplitLines
def HapMapBam = params.HapMapBam
def HapMapBai = params.HapMapBai
def targetsBed = params.targetsBed
def targetsAnnotatedBed = params.targetsAnnotatedBed
def runID = params.runID
def samplesheet = params.samplesheet
def SeraCareSelectedTsv = params.SeraCareSelectedTsv
def SeraCareSelectedTsvFile = new File("${SeraCareSelectedTsv}").getName()
def SeraCareErrorRate = params.SeraCareErrorRate
def CNVPool = params.CNVPool
def projectDir = params.runID
// Enable or disable some pipeline steps here TODO: better config management for this
disable_multiqc = true // for faster testing of the rest of the pipeline
disable_msisensor = true // breaks on very small demo datasets
disable_delly2 = true
disable_eval_pair_vcf = true
disable_pindel = true
disable_varscan2 = true
// load a mapping dict to use for keeping track of the names and suffixes for some files throughout the pipeline
String filemapJSON = new File("filemap.json").text
def filemap = jsonSlurper.parseText(filemapJSON)
// names of some important output files to use throughout the pipeline
def all_annotations_file = filemap.files.all_annotations_file
def all_seracare_annotations_file = filemap.files.all_seracare_annotations_file
def all_HapMapPool_annotations_file = filemap.files.all_HapMapPool_annotations_file
def samplesheet_output_file = filemap.files.samplesheet_output_file
def sample_coverage_file = filemap.files.sample_coverage_file
def interval_coverage_file = filemap.files.interval_coverage_file
def signatures_weights_file = filemap.files.signatures_weights_file
def targets_annotations_file = filemap.files.targets_annotations_file
def tmb_file = filemap.files.tmb_file
def git_json = filemap.files.git_json
def snp_overlap_file = filemap.files.snp_overlap_file
def outputDirPath = new File(params.outputDir).getCanonicalPath()
def reportDirPath = new File(params.reportDir).getCanonicalPath()
// REFERENCE FILES
params.ref_fa = "${params.ref_dir}/iGenomes/Homo_sapiens/UCSC/hg19/Sequence/WholeGenomeFasta/genome.fa"
params.ref_fa_bwa_dir = "${params.ref_dir}/BWA/hg19"
params.ref_fai = "${params.ref_dir}/iGenomes/Homo_sapiens/UCSC/hg19/Sequence/WholeGenomeFasta/genome.fa.fai"
params.ref_dict = "${params.ref_dir}/iGenomes/Homo_sapiens/UCSC/hg19/Sequence/WholeGenomeFasta/genome.dict"
params.ref_chrom_sizes = "${params.ref_dir}/Illumina/hg19/chrom.sizes"
params.microsatellites = "${params.ref_dir}/msisensor/hg19/microsatellites.list"
params.trimmomatic_contaminant_fa = "${params.ref_dir}/contaminants/trimmomatic.fa"
params.gatk_bundle_dir = "${params.ref_dir}/gatk-bundle"
params.gatk_1000G_phase1_indels_hg19_vcf = "${params.gatk_bundle_dir}/1000G_phase1.indels.hg19.vcf"
params.gatk_1000G_phase1_indels_hg19_vcf_idx = "${params.gatk_bundle_dir}/1000G_phase1.indels.hg19.vcf.idx"
params.mills_and_1000G_gold_standard_indels_hg19_vcf = "${params.gatk_bundle_dir}/Mills_and_1000G_gold_standard.indels.hg19.vcf"
params.mills_and_1000G_gold_standard_indels_hg19_vcf_idx = "${params.gatk_bundle_dir}/Mills_and_1000G_gold_standard.indels.hg19.vcf.idx"
params.dbsnp_ref_vcf = "${params.gatk_bundle_dir}/dbsnp_138.hg19.vcf"
params.dbsnp_ref_vcf_idx = "${params.gatk_bundle_dir}/dbsnp_138.hg19.vcf.idx"
params.dbsnp_ref_vcf_gz = "${params.gatk_bundle_dir}/dbsnp_138.hg19.vcf.gz"
params.dbsnp_ref_vcf_gz_tbi = "${params.gatk_bundle_dir}/dbsnp_138.hg19.vcf.gz.tbi"
params.cosmic_ref_vcf = "${params.ref_dir}/hg19/CosmicCodingMuts_v73.hg19.vcf"
params.cosmic_ref_vcf_idx = "${params.ref_dir}/hg19/CosmicCodingMuts_v73.hg19.vcf.idx"
params.common_snp_vcf = "${params.ref_dir}/hg19/common_all_20170710.vcf.gz"
params.common_snp_vcf_tbi = "${params.ref_dir}/hg19/common_all_20170710.vcf.gz.tbi"
// ~~~~~~~~~~ VALIDATION ~~~~~~~~~~ //
// make sure reference data directory exists
def ref_dir = new File("${params.ref_dir}")
if( !ref_dir.exists() ){
log.error "Ref dir does not exist: ${params.ref_dir}"
exit 1
}
// make sure annovar reference databases directory exist
def ANNOVAR_DB_DIR = new File("${params.ANNOVAR_DB_DIR}")
if( !ANNOVAR_DB_DIR.exists() ){
log.error "ANNOVAR database dir does not exist: ${params.ANNOVAR_DB_DIR}"
exit 1
}
// ~~~~~ START WORKFLOW ~~~~~ //
log.info "~~~~~~~ NGS580 Pipeline ~~~~~~~"
if(uname == "Linux"){
// /proc/self only works on Linux
int pid = Integer.parseInt(new File("/proc/self").getCanonicalFile().getName())
log.info "* pid: ${pid}"
}
log.info "* hostname: ${localhostname}"
log.info "* uname: ${uname}"
log.info "* Launch time: ${workflowTimestamp}"
log.info "* Run ID: ${runID}"
log.info "* Samplesheet: ${samplesheet}"
log.info "* Targets: ${targetsBed}"
log.info "* Project dir: ${workflow.projectDir}"
log.info "* Launch dir: ${workflow.launchDir}"
log.info "* Work dir: ${workflow.workDir.toUriString()}"
log.info "* Output dir: ${outputDirPath}"
log.info "* Profile: ${workflow.profile ?: '-'}"
log.info "* Script name: ${workflow.scriptName ?: '-'}"
log.info "* Script ID: ${workflow.scriptId ?: '-'}"
log.info "* Container engine: ${workflow.containerEngine?:'-'}"
log.info "* Workflow session: ${workflow.sessionId}"
log.info "* Nextflow run name: ${workflow.runName}"
log.info "* Nextflow version: ${workflow.nextflow.version}, build ${workflow.nextflow.build} (${workflow.nextflow.timestamp})"
log.info "* Launch command:\n${workflow.commandLine}\n"
// ~~~~~ DATA INPUT ~~~~~ //
// targets .bed file
Channel.fromPath( file(targetsBed) ).set{ targets_bed } // TODO: why is this here? duplicated..
Channel.fromPath( file(targetsAnnotatedBed) ).set{ targets_annotated_bed }
// reference files
Channel.fromPath( file(targetsBed) ).into { targets_bed;
targets_bed2;
targets_bed3;
targets_bed4;
targets_bed5;
targets_bed6;
targets_bed7;
targets_bed8;
targets_bed9;
targets_bed10;
targets_bed11;
targets_bed12;
targets_bed13;
targets_bed14 }
Channel.fromPath( file(params.ref_fa) ).into { ref_fasta;
ref_fasta2;
ref_fasta3;
ref_fasta4;
ref_fasta5;
ref_fasta6;
ref_fasta7;
ref_fasta8;
ref_fasta9;
ref_fasta10;
ref_fasta11;
ref_fasta12;
ref_fasta13;
ref_fasta14;
ref_fasta15;
ref_fasta16;
ref_fasta17;
ref_fasta18;
ref_fasta19;
ref_fasta20;
ref_fasta21 }
Channel.fromPath( file(params.ref_fai) ).into { ref_fai;
ref_fai2;
ref_fai3;
ref_fai4;
ref_fai5;
ref_fai6;
ref_fai7;
ref_fai8;
ref_fai9;
ref_fai10;
ref_fai11;
ref_fai12;
ref_fai13;
ref_fai14;
ref_fai15;
ref_fai16;
ref_fai17;
ref_fai18;
ref_fai19;
ref_fai20;
ref_fai21 }
Channel.fromPath( file(params.ref_dict) ).into { ref_dict;
ref_dict2;
ref_dict3;
ref_dict4;
ref_dict5;
ref_dict6;
ref_dict7;
ref_dict8;
ref_dict9;
ref_dict10;
ref_dict11;
ref_dict12;
ref_dict13;
ref_dict14;
ref_dict15;
ref_dict16;
ref_dict17;
ref_dict18;
ref_dict19;
ref_dict20;
ref_dict21 }
Channel.fromPath( file(params.ref_chrom_sizes) ).set{ ref_chrom_sizes }
Channel.fromPath( file(params.trimmomatic_contaminant_fa) ).set{ trimmomatic_contaminant_fa }
Channel.fromPath( file(params.ref_fa_bwa_dir) ).set{ ref_fa_bwa_dir }
Channel.fromPath( file(params.gatk_1000G_phase1_indels_hg19_vcf) ).into{ gatk_1000G_phase1_indels_vcf;
gatk_1000G_phase1_indels_vcf2;
gatk_1000G_phase1_indels_vcf3;
gatk_1000G_phase1_indels_vcf4 }
Channel.fromPath( file(params.gatk_1000G_phase1_indels_hg19_vcf_idx) ).into{ gatk_1000G_phase1_indels_vcf_idx;
gatk_1000G_phase1_indels_vcf_idx2;
gatk_1000G_phase1_indels_vcf_idx3;
gatk_1000G_phase1_indels_vcf_idx4 }
Channel.fromPath( file(params.mills_and_1000G_gold_standard_indels_hg19_vcf) ).into{ mills_and_1000G_gold_standard_indels_vcf;
mills_and_1000G_gold_standard_indels_vcf2;
mills_and_1000G_gold_standard_indels_vcf3;
mills_and_1000G_gold_standard_indels_vcf4 }
Channel.fromPath( file(params.mills_and_1000G_gold_standard_indels_hg19_vcf_idx) ).into{ mills_and_1000G_gold_standard_indels_vcf_idx;
mills_and_1000G_gold_standard_indels_vcf_idx2;
mills_and_1000G_gold_standard_indels_vcf_idx3;
mills_and_1000G_gold_standard_indels_vcf_idx4 }
Channel.fromPath( file(params.dbsnp_ref_vcf) ).into{ dbsnp_ref_vcf;
dbsnp_ref_vcf2;
dbsnp_ref_vcf3;
dbsnp_ref_vcf4;
dbsnp_ref_vcf5;
dbsnp_ref_vcf6;
dbsnp_ref_vcf7;
dbsnp_ref_vcf8 }
Channel.fromPath( file(params.dbsnp_ref_vcf_idx) ).into{ dbsnp_ref_vcf_idx;
dbsnp_ref_vcf_idx2;
dbsnp_ref_vcf_idx3;
dbsnp_ref_vcf_idx4;
dbsnp_ref_vcf_idx5;
dbsnp_ref_vcf_idx6;
dbsnp_ref_vcf_idx7;
dbsnp_ref_vcf_idx8 }
Channel.fromPath( file(params.dbsnp_ref_vcf_gz) ).set { dbsnp_ref_vcf_gz }
Channel.fromPath( file(params.dbsnp_ref_vcf_gz_tbi) ).set { dbsnp_ref_vcf_gz_tbi }
Channel.fromPath( file(params.cosmic_ref_vcf) ).into{ cosmic_ref_vcf; cosmic_ref_vcf2 }
Channel.fromPath( file(params.cosmic_ref_vcf_idx) ).into{ cosmic_ref_vcf_idx; cosmic_ref_vcf_idx2 }
Channel.fromPath( file(params.common_snp_vcf) ).set{ common_snp_vcf }
Channel.fromPath( file(params.common_snp_vcf_tbi) ).set{ common_snp_vcf_tbi }
Channel.fromPath( file(params.microsatellites) ).set{ microsatellites }
Channel.fromPath( file(params.ANNOVAR_DB_DIR) ).into { annovar_db_dir;
annovar_db_dir2;
annovar_db_dir3;
annovar_db_dir4 }
// report and output dir
Channel.fromPath("${outputDirPath}").into { analysis_output; analysis_output2 }
// load analysis report files
Channel.fromPath("${reportDirPath}/util").into { report_utils; report_utils2 }
Channel.fromPath("${reportDirPath}/analysis/*")
.set { analysis_report_files_base }
analysis_report_files_base.mix(report_utils).set { analysis_report_files }
// load samples report files
Channel.fromPath("${reportDirPath}/samples/*")
.toList()
.map { items ->
return( [items])
}
.set { samples_report_files }
// read samples from analysis samplesheet
Channel.fromPath( file(samplesheet) )
.splitCsv(header: true, sep: '\t')
.map{row ->
def sampleID = row['Sample']
def reads1 = row['R1'].tokenize( ',' ).collect { file(it) } // comma-sep string into list of files
def reads2 = row['R2'].tokenize( ',' ).collect { file(it) }
return [ sampleID, reads1, reads2 ]
}
.tap { samples_R1_R2; samples_R1_R2_2 } // set of all fastq R1 R2 per sample
.map { sampleID, reads1, reads2 ->
return [ reads1, reads2 ]
}
.flatMap().flatMap()
.set { samples_each_fastq } // emit each fastq file individually, no sampleID
// read sample tumor-normal pairs from analysis sheet
Channel.fromPath( file(samplesheet) )
.splitCsv(header: true, sep: '\t')
.map { row ->
def tumorID = row['Tumor']
def normalID = row['Normal']
return [ tumorID, normalID ]
}
.filter { item ->
item[0] != item[1] // remove Normal samples
}
.tap { samples_pairs_with_NA; samples_pairs_with_NA2 }
.filter { item ->
item[1] != 'NA' // unpaired samples
}
.into { samples_pairs;
samples_pairs2;
samples_pairs3;
samples_pairs4 }
// read sample IDs from analysis sheet
Channel.fromPath( file(samplesheet) )
.splitCsv(header: true, sep: '\t')
.map{row ->
def sampleID = row['Sample']
return(sampleID)
}
.unique()
.into { sampleIDs; sampleIDs2; sampleIDs3 }
// find all the HapMap samples
sampleIDs2.filter {
def is_hapmap = "${it}".toLowerCase().contains("hapmap")
return(is_hapmap)
}.set { hapmap_sample_ids }
// ref HapMap Pool bam and bai
Channel.from([ [file("${HapMapBam}"), file("${HapMapBai}")] ]).filter { items ->
def bam = items[0]
def bai = items[1]
// only run these steps if params were set and files exist
HapMapBam && HapMapBai && bam.exists() && bai.exists()
}.set { hapmap_pool_ch }
// find all the SeraCare samples
sampleIDs3.filter {
def is_seracare = "${it}".toLowerCase().contains("seracare")
return(is_seracare)
}.set { seracare_sample_ids }
Channel.fromPath( "${SeraCareSelectedTsv}").into { seracare_selected_tsv; seracare_selected_tsv2 }
Channel.fromPath("${CNVPool}").set { cnv_pool_ch }
Channel.fromPath( file(samplesheet) ).set { samples_analysis_sheet }
// logging channels
Channel.from("Sample\tProgram\tType\tNote\tFiles").set { failed_samples }
Channel.from("Comparison\tTumor\tNormal\tChunk\tProgram\tProgramType\tNote\tFiles").set { failed_pairs }
// ~~~~~ PIPELINE TASKS ~~~~~ //
// PREPROCESSING
process git {
// get repo information
publishDir "${params.outputDir}", mode: 'copy'
output:
file("${output_file}") into git_json_ch
script:
output_file = "${git_json}"
"""
git.py --dir "${workflow.projectDir}" -o "${output_file}"
"""
}
process copy_samplesheet {
// make a copy of the samplesheet in the output directory
// this ensures the output sheet has the correct name
publishDir "${params.outputDir}", mode: 'copy'
executor "local"
input:
file(input_sheet: "input_samplesheet.tsv") from samples_analysis_sheet
output:
file("${samplesheet_output_file}") into samplesheet_output_file_ch
val("") into done_copy_samplesheet
script:
"""
cp "${input_sheet}" "${samplesheet_output_file}"
"""
}
process print_metadata {
// print the workflow meta data to the output directory
publishDir "${params.outputDir}", mode: 'copy'
executor "local"
input:
val(x) from Channel.from('')
output:
file("${output_file}") into metadata_ch
val("") into done_print_metadata
script:
output_file = "meta.tsv"
"""
printf "Run\tTime\tSession\tWorkflow\tLocation\tSystem\tOutputPath\tUsername\n" > "${output_file}"
printf "${runID}\t${workflowTimestamp}\t${workflow.sessionId}\t${workflow.runName}\t${workflow.projectDir}\t${localhostname}\t${outputDirPath}\t${username}\n" >> "${output_file}"
"""
}
process targets_zip {
input:
file(targets_bed) from targets_bed13
output:
set file("${output_bgz}"), file("${output_index}") into targets_zipped, targets_zipped2
script:
output_bgz = "targets.bed.bgz"
output_index = "targets.bed.bgz.tbi"
"""
sort -V -k1,1 -k2,2 "${targets_bed}" > targets.sorted.bed
bgzip -c targets.sorted.bed > "${output_bgz}"
tabix -p bed "${output_bgz}"
"""
}
process targets_metrics {
// print metrics about the targets
publishDir "${params.outputDir}/metrics/targets", mode: 'copy', pattern: "*.bed"
publishDir "${params.outputDir}", mode: 'copy', pattern: "*${targets_metrics}"
executor "local"
input:
file(targets) from targets_bed9
output:
file("${targets_metrics}") into targets_metrics_ch
script:
targets_sorted = "targets.sorted.bed"
targets_merged = "targets.merged.bed"
targets_metrics = "targets.metrics.tsv"
"""
num_targets="\$(cat "${targets}" | wc -l)"
targets_md5="\$(python -c "import hashlib; print(hashlib.md5(open('${targets}', 'rb').read()).hexdigest())")"
# check if there are strands in the targets
if [ "\$(bed.py "${targets}" hasStrands)" == "True" ]; then
sort -k 1,1 -k2,2n "${targets}" > "${targets_sorted}"
bedtools merge -s -i "${targets_sorted}" > "${targets_merged}"
else
sort -k 1,1 -k2,2n "${targets}" > "${targets_sorted}"
bedtools merge -i "${targets_sorted}" > "${targets_merged}"
fi
num_merged_targets="\$(cat "${targets_merged}" | wc -l)"
targets_coverage_bp="\$(bed.py "${targets}" breadthOfCoverage)"
targets_coverage_Mbp="\$(python -c "print( \${targets_coverage_bp} / float((10**6)) )")"
targets_filename="\$(python -c "import os; print(os.path.basename(os.path.realpath('${targets}')))")"
printf 'Targets File\tNumber of Targets\tNumber of Merged Targets\tBreadth Of Coverage (Mbp)\tBreadth Of Coverage (bp)\tmd5\n' > "${targets_metrics}"
printf "\${targets_filename}\t\${num_targets}\t\${num_merged_targets}\t\${targets_coverage_Mbp}\t\${targets_coverage_bp}\t\${targets_md5}\n" >> "${targets_metrics}"
"""
}
target_ANNOVAR_BUILD_VERSION = "hg19"
target_ANNOVAR_PROTOCOL = "refGene"
target_ANNOVAR_OPERATION = "g"
process annotate_targets {
// annotate the target.bed regions
input:
set file(targets_bed), file(annovar_db_dir) from targets_bed11.combine(annovar_db_dir4)
output:
file("${output_file}") into annotated_targets
script:
prefix = "targets"
interval_tmp = "${prefix}.intervals.tmp"
remainder_tsv = "${prefix}.remainder.tsv"
avinput_file = "${prefix}.avinput"
annovar_output_txt = "${prefix}.${target_ANNOVAR_BUILD_VERSION}_multianno.txt"
output_file = "${targets_annotations_file}"
"""
# convert table to ANNOVAR format for annotation; http://annovar.openbioinformatics.org/en/latest/user-guide/input/
# add '0' cols for ref and alt
cut -f1-3 "${targets_bed}" > "${avinput_file}"
sed -e 's|\$|\t0|' -i "${avinput_file}"
sed -e 's|\$|\t0|' -i "${avinput_file}"
# annotate
table_annovar.pl "${avinput_file}" "${annovar_db_dir}" \
--buildver "${target_ANNOVAR_BUILD_VERSION}" \
--remove \
--protocol "${target_ANNOVAR_PROTOCOL}" \
--operation "${target_ANNOVAR_OPERATION}" \
--nastring . \
--outfile "${prefix}"
mv "${annovar_output_txt}" "${output_file}"
"""
}
process fastq_merge {
// merge multiple R1 and R2 fastq files (e.g. split by lane) into a single fastq each
input:
set val(sampleID), file(fastq_r1: "*"), file(fastq_r2: "*") from samples_R1_R2
output:
set val(sampleID), file("${merged_fastq_R1}"), file("${merged_fastq_R2}") into samples_fastq_merged
file("${num_reads_R1}")
file("${num_reads_R2}")
file("${num_reads}")
val(sampleID) into done_fastq_merge
script:
prefix = "${sampleID}"
merged_fastq_R1 = "${prefix}_R1.fastq.gz"
merged_fastq_R2 = "${prefix}_R2.fastq.gz"
num_reads = "${prefix}.reads.txt"
num_reads_R1 = "${prefix}_R1.reads.txt"
num_reads_R2 = "${prefix}_R2.reads.txt"
"""
cat ${fastq_r1} > "${merged_fastq_R1}"
cat ${fastq_r2} > "${merged_fastq_R2}"
# get the number of reads
zcat "${merged_fastq_R1}" | awk '{s++}END{print s/4}' > "${num_reads}"
cp "${num_reads}" "${num_reads_R1}"
zcat "${merged_fastq_R2}" | awk '{s++}END{print s/4}' > "${num_reads_R2}"
"""
}
process trimmomatic {
// trim low quality bases from reads
publishDir "${params.outputDir}/reads/trimmed", mode: 'copy', pattern: "*${fastq_R1_trimmed}"
publishDir "${params.outputDir}/reads/trimmed", mode: 'copy', pattern: "*${fastq_R2_trimmed}"
publishDir "${params.outputDir}/reads/stats", mode: 'copy', pattern: "*.txt"
input:
set val(sampleID), file(read1), file(read2), file(trimmomatic_contaminant_fa) from samples_fastq_merged.combine(trimmomatic_contaminant_fa)
output:
set val(sampleID), file("${fastq_R1_trimmed}"), file("${fastq_R2_trimmed}") into samples_fastq_trimmed, samples_fastq_trimmed2
file("${num_reads_trim}")
file("${num_reads_trim_R1}")
file("${num_reads_trim_R2}")
file("${num_reads_unpaired_R1}")
file("${num_reads_unpaired_R2}")
val(sampleID) into done_trimmomatic
script:
prefix = "${sampleID}"
fastq_R1_trimmed = "${prefix}_R1.trim.fastq.gz"
fastq_R2_trimmed = "${prefix}_R2.trim.fastq.gz"
fastq_R1_unpaired = "${prefix}_R1.unpaired.fastq.gz"
fastq_R2_unpaired = "${prefix}_R2.unpaired.fastq.gz"
num_reads_trim = "${prefix}.trim.reads.txt"
num_reads_trim_R1 = "${prefix}_R1.trim.reads.txt"
num_reads_trim_R2 = "${prefix}_R2.trim.reads.txt"
num_reads_unpaired_R1 = "${prefix}_R1.unpaired.reads.txt"
num_reads_unpaired_R2 = "${prefix}_R2.unpaired.reads.txt"
"""
trimmomatic.sh PE -threads \${NSLOTS:-\${NTHREADS:-1}} \
"${read1}" "${read2}" \
"${fastq_R1_trimmed}" "${fastq_R1_unpaired}" \
"${fastq_R2_trimmed}" "${fastq_R2_unpaired}" \
ILLUMINACLIP:${trimmomatic_contaminant_fa}:2:30:10:1:true TRAILING:5 SLIDINGWINDOW:4:15 MINLEN:35
# get the number of reads
zcat "${fastq_R1_trimmed}" | awk '{s++}END{print s/4}' > "${num_reads_trim}"
cp "${num_reads_trim}" "${num_reads_trim_R1}"
zcat "${fastq_R2_trimmed}" | awk '{s++}END{print s/4}' > "${num_reads_trim_R2}"
zcat "${fastq_R1_unpaired}" | awk '{s++}END{print s/4}' > "${num_reads_unpaired_R1}"
zcat "${fastq_R2_unpaired}" | awk '{s++}END{print s/4}' > "${num_reads_unpaired_R2}"
"""
}
process fastqc {
// quality control checking with FastQC
publishDir "${params.outputDir}/qc/fastqc", mode: 'copy'
input:
set val(sampleID), file(fastq_R1), file(fastq_R2) from samples_fastq_trimmed2
output:
file(output_R1_html)
file(output_R1_zip)
file(output_R2_html)
file(output_R2_zip)
val(sampleID) into done_fastqc_trim
script:
output_R1_html = "${fastq_R1}".replaceFirst(/.fastq.gz$/, "_fastqc.html")
output_R1_zip = "${fastq_R1}".replaceFirst(/.fastq.gz$/, "_fastqc.zip")
output_R2_html = "${fastq_R2}".replaceFirst(/.fastq.gz$/, "_fastqc.html")
output_R2_zip = "${fastq_R2}".replaceFirst(/.fastq.gz$/, "_fastqc.zip")
"""
fastqc -o . "${fastq_R1}"
fastqc -o . "${fastq_R2}"
"""
}
process alignment {
// first pass alignment with BWA
publishDir "${params.outputDir}/alignments/raw", mode: 'copy'
input:
set val(sampleID), file(fastq_R1_trim), file(fastq_R2_trim), file(ref_fa_bwa_dir) from samples_fastq_trimmed.combine(ref_fa_bwa_dir)
output:
set val(sampleID), file("${bam_file}") into samples_bam, samples_bam2, samples_bam3, samples_bam4
val(sampleID) into done_alignment
script:
prefix = "${sampleID}"
bam_file = "${prefix}.bam"
"""
bwa mem \
-M -v 1 \
-t \${NSLOTS:-\${NTHREADS:-1}} \
-R '@RG\\tID:${sampleID}\\tSM:${sampleID}\\tLB:${sampleID}\\tPL:ILLUMINA' \
"${ref_fa_bwa_dir}/genome.fa" \
"${fastq_R1_trim}" "${fastq_R2_trim}" | \
sambamba view \
--sam-input \
--nthreads=\${NSLOTS:-\${NTHREADS:-1}} \
--filter='mapping_quality>=10' \
--format=bam \
--compression-level=0 \
/dev/stdin | \
sambamba sort \
--nthreads=\${NSLOTS:-\${NTHREADS:-1}} \
--out="${bam_file}" /dev/stdin
"""
}
process samtools_flagstat {
// alignment stats
publishDir "${params.outputDir}/alignments/stats", mode: 'copy'
input:
set val(sampleID), file(sample_bam) from samples_bam
output:
set val(sampleID), file("${flagstat}") into flagstats
val(sampleID) into done_sambamba_flagstat
script:
prefix = "${sampleID}"
flagstat = "${prefix}.flagstat.txt"
"""
samtools flagstat "${sample_bam}" > "${flagstat}"
"""
}
process samtools_flagstat_table {
// convert flagstat output to a flat table
publishDir "${params.outputDir}/alignments/stats", mode: 'copy'
input:
set val(sampleID), file(flagstat) from flagstats
output:
file("${output_file}") into sambamba_flagstat_tables
val(sampleID) into done_sambamba_flagstat_table
script:
prefix = "${sampleID}"
output_file = "${prefix}.flagstat.tsv"
"""
flagstat2table.R "${flagstat}" tmp.tsv
paste-col.py -i tmp.tsv --header "Sample" -v "${sampleID}" > "${output_file}"
"""
}
sambamba_flagstat_tables.collectFile(name: ".flagstat.tsv", keepHeader: true).set { sambamba_flagstat_table_collected }
process update_samtools_flagstat_table {
// add labels to the table to output
publishDir "${params.outputDir}", mode: 'copy'
input:
file(table) from sambamba_flagstat_table_collected
output:
file("${output_file}") into samtools_flagstat_table_ch
val('') into done_samtools_flagstat_table_update
script:
output_file = "flagstat.tsv"
"""
paste-col.py -i "${table}" --header "Run" -v "${runID}" | \
paste-col.py --header "Time" -v "${workflowTimestamp}" | \
paste-col.py --header "Session" -v "${workflow.sessionId}" | \
paste-col.py --header "Workflow" -v "${workflow.runName}" | \
paste-col.py --header "Location" -v "${workflow.projectDir}" | \
paste-col.py --header "System" -v "${localhostname}" | \
paste-col.py --header "GitBranch" -v "${params.GIT_CURRENT_BRANCH}" | \
paste-col.py --header "GitTag" -v "${params.GIT_CURRENT_TAG}" > \
"${output_file}"
"""
}
process sambamba_dedup {
// deduplicate alignments
publishDir "${params.outputDir}/alignments/deduplicated", mode: 'copy'
input:
set val(sampleID), file(sample_bam) from samples_bam2
output:
set val(sampleID), file("${bam_file}") into samples_dd_bam, samples_dd_bam2
set val(sampleID), file("${bam_file}"), file("${bai_file}") into samples_dd_bam3, samples_dd_bam4, samples_dd_bam5
set val(sampleID), file("${log_file}") into sambamba_dedup_logs
val(sampleID) into done_sambamba_dedup
script:
prefix = "${sampleID}"
bam_file = "${prefix}.dd.bam"
bai_file = "${prefix}.dd.bam.bai"
log_file = "${prefix}.dd.log"
"""
sambamba markdup \
--remove-duplicates \
--nthreads \${NSLOTS:-\${NTHREADS:-1}} \
--hash-table-size 525000 \
--overflow-list-size 525000 \
"${sample_bam}" "${bam_file}"
# make a copy of the .command.err Nextflow log file for parsing
cat .command.err > "${log_file}"
samtools index "${bam_file}"
"""
}
process sambamba_dedup_log_table {
// convert the dedup stats the a flat table
publishDir "${params.outputDir}/alignment-stats", mode: 'copy'
input:
set val(sampleID), file(log_file) from sambamba_dedup_logs
output:
file("${output_file}") into sambamba_dedup_log_tables
val(sampleID) into done_sambamba_dedup_log_table
script:
prefix = "${sampleID}"
output_file = "${prefix}.dd.tsv"
"""
dedup-log2table.R "${log_file}" tmp.tsv
paste-col.py -i tmp.tsv --header "Sample" -v "${sampleID}" > "${output_file}"
"""
}
sambamba_dedup_log_tables.collectFile(name: ".reads.dedup.tsv", keepHeader: true).set { sambamba_dedup_log_tables_collected }
process update_sambamba_dedup_log_table{
// add labels to the table to output
publishDir "${params.outputDir}", mode: 'copy'
input:
file(table) from sambamba_dedup_log_tables_collected
output:
file("${output_file}") into sambamba_dedup_log_table_ch
val('') into done_update_sambamba_dedup_log_table
script:
output_file = "reads.dedup.tsv"
"""
paste-col.py -i "${table}" --header "Run" -v "${runID}" | \
paste-col.py --header "Time" -v "${workflowTimestamp}" | \
paste-col.py --header "Session" -v "${workflow.sessionId}" | \
paste-col.py --header "Workflow" -v "${workflow.runName}" | \
paste-col.py --header "Location" -v "${workflow.projectDir}" | \
paste-col.py --header "System" -v "${localhostname}" | \
paste-col.py --header "GitBranch" -v "${params.GIT_CURRENT_BRANCH}" | \
paste-col.py --header "GitTag" -v "${params.GIT_CURRENT_TAG}" > \
"${output_file}"
"""
}
process samtools_dedup_flagstat {
// dedup alignment stats
publishDir "${params.outputDir}/alignment-stats", mode: 'copy'
input:
set val(sampleID), file(sample_bam) from samples_dd_bam2
output:
set val(sampleID), file("${flagstat}") into dedup_flagstats
val(sampleID) into done_sambamba_dedup_flagstat
script:
prefix = "${sampleID}"
flagstat = "${prefix}.dd.flagstat.txt"
"""
samtools flagstat "${sample_bam}" > "${flagstat}"
"""
}
process samtools_dedup_flagstat_table {
// convert dedup stats to a flat table
publishDir "${params.outputDir}/alignment-stats", mode: 'copy'
input:
set val(sampleID), file(flagstat) from dedup_flagstats
output:
file("${output_file}") into sambamba_dedup_flagstat_tables
val(sampleID) into done_sambamba_dedup_flagstat_table
script:
prefix = "${sampleID}"
output_file = "${prefix}.dd.flagstat.tsv"
"""
flagstat2table.R "${flagstat}" tmp.tsv
paste-col.py -i tmp.tsv --header "Sample" -v "${sampleID}" > "${output_file}"
"""
}
sambamba_dedup_flagstat_tables.collectFile(name: ".flagstat.dedup.tsv", keepHeader: true).set { sambamba_dedup_flagstat_tables_collected }
process update_samtools_dedup_flagstat_table {
// add labels to the table to output
publishDir "${params.outputDir}", mode: 'copy'
input:
file(table) from sambamba_dedup_flagstat_tables_collected
output:
file("${output_file}") into samtools_dedup_flagstat_table_ch
val('') into done_update_samtools_dedup_flagstat_table
script:
output_file = "flagstat.dedup.tsv"
"""
paste-col.py -i "${table}" --header "Run" -v "${runID}" | \
paste-col.py --header "Time" -v "${workflowTimestamp}" | \
paste-col.py --header "Session" -v "${workflow.sessionId}" | \
paste-col.py --header "Workflow" -v "${workflow.runName}" | \
paste-col.py --header "Location" -v "${workflow.projectDir}" | \
paste-col.py --header "System" -v "${localhostname}" | \
paste-col.py --header "GitBranch" -v "${params.GIT_CURRENT_BRANCH}" | \
paste-col.py --header "GitTag" -v "${params.GIT_CURRENT_TAG}" > \
"${output_file}"
"""
}
// setup downstream Channels
samples_dd_bam.combine(ref_fasta)
.combine(ref_fai)
.combine(ref_dict)
.combine(targets_bed)
.combine(gatk_1000G_phase1_indels_vcf)
.combine(gatk_1000G_phase1_indels_vcf_idx)
.combine(mills_and_1000G_gold_standard_indels_vcf)
.combine(mills_and_1000G_gold_standard_indels_vcf_idx)
.combine(dbsnp_ref_vcf)
.combine(dbsnp_ref_vcf_idx)
.set { samples_dd_bam_ref_gatk }
// MAIN REALIGNMENT AND RECALIBRATION STEP
process gatk_RealignerTargetCreator {
// re-align and recalibrate alignments for later variant calling
publishDir "${params.outputDir}/alignment-stats", pattern: "${intervals_file}", mode: 'copy'
input:
set val(sampleID), file(sample_bam), file(ref_fasta), file(ref_fai), file(ref_dict), file(targets_bed_file), file(gatk_1000G_phase1_indels_vcf), file(gatk_1000G_phase1_indels_vcf_idx), file(mills_and_1000G_gold_standard_indels_vcf), file(mills_and_1000G_gold_standard_indels_vcf_idx), file(dbsnp_ref_vcf), file(dbsnp_ref_vcf_idx) from samples_dd_bam_ref_gatk
output:
set val(sampleID), file("${intervals_file}"), file(sample_bam) into realigned_intervals_tables
val(sampleID) into done_gatk_RealignerTargetCreator
script:
prefix = "${sampleID}"
intervals_file = "${prefix}.RealignerTargetCreator.intervals"
"""
gatk.sh -T RealignerTargetCreator \
-dt NONE \
--logging_level ERROR \
-nt \${NSLOTS:-\${NTHREADS:-1}} \
--reference_sequence "${ref_fasta}" \
-known "${gatk_1000G_phase1_indels_vcf}" \
-known "${mills_and_1000G_gold_standard_indels_vcf}" \
--intervals "${targets_bed_file}" \
--interval_padding 10 \
--input_file "${sample_bam}" \
--out "${intervals_file}"
"""
}
realigned_intervals_tables.combine(ref_fasta6)
.combine(ref_fai6)
.combine(ref_dict6)
.combine(targets_bed5)
.combine(gatk_1000G_phase1_indels_vcf2)
.combine(gatk_1000G_phase1_indels_vcf_idx2)
.combine(mills_and_1000G_gold_standard_indels_vcf2)
.combine(mills_and_1000G_gold_standard_indels_vcf_idx2)
.combine(dbsnp_ref_vcf6)
.combine(dbsnp_ref_vcf_idx6)
.set { realigned_intervals_tables_comb }
process gatk_IndelRealigner {
// re-align and recalibrate alignments for later variant calling
publishDir "${params.outputDir}/alignments/realigned", pattern: "*.dd.ra.bam*", mode: 'copy'
input:
set val(sampleID), file(intervals_file), file(sample_bam), file(ref_fasta), file(ref_fai), file(ref_dict), file(targets_bed_file), file(gatk_1000G_phase1_indels_vcf), file(gatk_1000G_phase1_indels_vcf_idx), file(mills_and_1000G_gold_standard_indels_vcf), file(mills_and_1000G_gold_standard_indels_vcf_idx), file(dbsnp_ref_vcf), file(dbsnp_ref_vcf_idx) from realigned_intervals_tables_comb
output:
set val(sampleID), file("${ra_bam_file}"), file("${ra_bai_file}") into realigned_intervals_bams
val(sampleID) into done_gatk_IndelRealigner
script:
prefix = "${sampleID}"
ra_bam_file = "${prefix}.dd.ra.bam"
ra_bai_file = "${prefix}.dd.ra.bam.bai"
"""
samtools index "${sample_bam}"
gatk.sh -T IndelRealigner \
-dt NONE \
--logging_level ERROR \
--reference_sequence "${ref_fasta}" \
--maxReadsForRealignment 50000 \