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filter germline consented samples in germline mode #870

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12 changes: 12 additions & 0 deletions lib/TempoUtils.groovy
Original file line number Diff line number Diff line change
Expand Up @@ -7,6 +7,18 @@ import nextflow.Channel

class TempoUtils {

static def extractGermlineSamples(tsvFile) {
def allRows = [:]
Channel.from(tsvFile)
.splitCsv(sep: '\t', header: true)
.map { row ->
checkHeader([row.NORMAL_ID], tsvFile)
if(!checkNumberOfItem(row, 1, tsvFile)){System.exit(1)}
if(!checkDuplicates(allRows, row, row, tsvFile)){System.exit(1)}
row.NORMAL_ID
}
}

static def extractPairing(tsvFile) {
def allRows = [:]
Channel.from(tsvFile)
Expand Down
66 changes: 62 additions & 4 deletions pipeline.nf
Original file line number Diff line number Diff line change
Expand Up @@ -90,7 +90,8 @@ if (!(workflow.profile in ['juno', 'awsbatch', 'docker', 'singularity', 'test_si
publishAll = params.publishAll
outDir = file(params.outDir).toAbsolutePath()
outname = params.outname
runGermline = params.germline
runGermline = params.germline != false ? true : params.germline
runGermlineFile = params.germline
runSomatic = params.somatic
runQC = params.QC
runAggregate = params.aggregate
Expand Down Expand Up @@ -768,7 +769,18 @@ if (params.pairing) {
def normalBai = item[4]
return [ idNormal, target, normalBam, normalBai ] }
.unique()
.into{ bams4Haplotypecaller; bamsNormal4Polysolver; bamsForStrelkaGermline; bamsForMantaGermline; bamsForDellyGermline }
//.into{ bams4Haplotypecaller; bamsNormal4Polysolver; bamsForStrelkaGermline; bamsForMantaGermline; bamsForDellyGermline }
.into{bamsNormal4Polysolver; bams4GermlineAnalysis}

if (runGermline != false && file(runGermlineFile.toString()).exists() ){
if (params.watch == false) {
TempoUtils.extractGermlineSamples(file(runGermlineFile)).set{ germlineFilter }
} else {
watchGermline(file(runGermlineFile)).set{ germlineFilter }
}
bams4GermlineAnalysis.combine(germlineFilter, by:[0]).set{bams4GermlineAnalysis}
}
bams4GermlineAnalysis.into{bams4Haplotypecaller; bamsForStrelkaGermline; bamsForMantaGermline; bamsForDellyGermline }


bamsTumor4Combine.combine(bamsNormal4Combine, by: [0,1,2])
Expand Down Expand Up @@ -3281,8 +3293,9 @@ else if(!(runAggregate == false)) {
cohortSomaticAggregateLOHHLA1;
cohortSomaticAggregateMetadata;
cohortGermlineAggregateMaf;
cohortGermlineAggregateSv;
cohortGermlineAggregateSv1;
//cohortGermlineAggregateSv;
//cohortGermlineAggregateSv1;
cohortGermlineAggregateFilter;
cohortQcBamAggregate;
cohortQcBamAggregate1;
cohortQcBamAggregate2;
Expand All @@ -3307,6 +3320,25 @@ else if(!(runAggregate == false)) {
inputSomaticAggregateMetadata = cohortSomaticAggregateMetadata.combine(MetaData4Aggregate, by:[1,2]).groupTuple(by:[2])

if (runGermline){
if ( file(runGermlineFile.toString()).exists() ){
cohortGermlineAggregateFilter
.groupTuple()
.map{cohort, idTumor, idNormal ->
def filterIdTumor = []
def filterIdNormal = []
def intersectLists = idNormal.intersect(germline2List(runGermlineFile))
idTumor.eachWithIndex{ item, index ->
if ( intersectLists.contains(idNormal[index]) ) {
filterIdTumor += item
filterIdNormal += idNormal[index]
}
}
[cohort, filterIdTumor, filterIdNormal]
}.map{ cohort, idTumor, idNormal
-> tuple( groupKey(cohort, idTumor instanceof Collection ? idTumor.size() : 1), idTumor, idNormal)
}.transpose()
.into{cohortGermlineAggregateSv; cohortGermlineAggregateSv1}
} else { cohortGermlineAggregateFilter.into{ cohortGermlineAggregateSv; cohortGermlineAggregateSv1 } }
inputGermlineAggregateMaf = cohortGermlineAggregateMaf.combine(mafFile4AggregateGermline, by:[1,2]).groupTuple(by:[2])
inputGermlineAggregateSv = cohortGermlineAggregateSv.combine(dellyMantaCombined4AggregateGermline, by:[2]).groupTuple(by:[1]).map{[it[1], it[5].unique()]}
inputGermlineAggregateSvTbi = cohortGermlineAggregateSv1.combine(dellyMantaCombinedTbi4AggregateGermline, by:[2]).groupTuple(by:[1]).map{[it[1], it[5].unique()]}
Expand Down Expand Up @@ -4171,3 +4203,29 @@ def watchAggregate(tsvFile) {
.transpose()
.unique()
}

def watchGermline(tsvFile) {
Channel.watchPath(file(tsvFile), 'create, modify')
.splitCsv(sep: '\t', header: true)
.unique()
.map{ row ->
def idNormal = row.NORMAL_ID
if(!TempoUtils.checkNumberOfItem(row, 1, file(tsvFile))){}
idNormal
}
.unique()
}
def germline2List(tsvFile){
def parsedFile = false
def germlineList = []
TempoUtils.extractGermlineSamples(tsvFiles)
.collect()
.subscribe{ row ->
parsedFile = true
germlineList = row
}
while ( ! parsedFile ){
sleep(500)
}
return germlineList
}