def constructor(self): self.input("bam", BamBai) self.input("intervals", Bed) self.input("sample_name", String) self.input("header_lines", File) self.input("reference", FastaWithDict) # vardict options self.input("allele_freq_threshold", Float, default=0.05) self.input("min_mapping_qual", Int(optional=True)) self.input("filter", String(optional=True)) self.input("no_sv_call", Boolean(optional=True)) self.step( "vardict", VarDictGermline_1_6_0( intervals=self.intervals, bam=self.bam, reference=self.reference, sampleName=self.sample_name, var2vcfSampleName=self.sample_name, alleleFreqThreshold=self.allele_freq_threshold, var2vcfAlleleFreqThreshold=self.allele_freq_threshold, vcfFormat=True, chromColumn=1, regStartCol=2, geneEndCol=3, threads=4, minMappingQual=self.min_mapping_qual, filter=self.filter, noStructuralVariants=self.no_sv_call, ), ) self.step( "annotate", BcfToolsAnnotate_1_5(vcf=self.vardict.out, headerLines=self.header_lines), ) self.step("compressvcf", BGZipLatest(file=self.annotate.out, stdout=True)) self.step("tabixvcf", TabixLatest(inp=self.compressvcf.out)) self.step( "splitnormalisevcf", SplitMultiAllele(vcf=self.annotate.out, reference=self.reference), ) self.step("trim", TrimIUPAC_0_0_5(vcf=self.splitnormalisevcf.out)) self.step( "filterpass", VcfToolsvcftoolsLatest( vcf=self.trim.out, removeFileteredAll=True, recode=True, recodeINFOAll=True, ), ) self.output("variants", source=self.tabixvcf.out) self.output("out", source=self.filterpass.out)
def constructor(self): self.input("normal_bam", BamBai) self.input("tumor_bam", BamBai) self.input("normal_name", String) self.input("tumor_name", String) self.input("intervals", Bed) self.input("header_lines", File) self.input("reference", FastaWithDict) # vardict options self.input("allele_freq_threshold", Float(), 0.05) self.input("minMappingQual", Int(optional=True)) self.input("filter", String(optional=True)) self.step( "vardict", VarDictSomatic_1_6_0( normalBam=self.normal_bam, tumorBam=self.tumor_bam, intervals=self.intervals, reference=self.reference, normalName=self.normal_name, tumorName=self.tumor_name, alleleFreqThreshold=self.allele_freq_threshold, vcfFormat=True, chromColumn=1, regStartCol=2, geneEndCol=3, threads=4, minMappingQual=self.minMappingQual, filter=self.filter, ), ) self.step( "annotate", BcfToolsAnnotate_1_5(vcf=self.vardict.out, headerLines=self.header_lines), ) self.step("compressvcf", BGZipLatest(file=self.annotate.out, stdout=True)) self.step("tabixvcf", TabixLatest(inp=self.compressvcf.out)) self.step( "splitnormalisevcf", SplitMultiAllele(vcf=self.annotate.out, reference=self.reference), ) self.step("trim", TrimIUPAC_0_0_5(vcf=self.splitnormalisevcf.out)) self.step("filterpass", FilterVardictSomaticVcf(vcf=self.trim.out)) self.output("variants", source=self.tabixvcf.out) self.output("out", source=self.filterpass.out)
def constructor(self): self.input("bam", BamBai) self.input("intervals", Bed) self.input("sample_name", String) self.input("allele_freq_threshold", Float, default=0.5) self.input("header_lines", File) self.input("reference", FastaWithDict) self.step( "vardict", VarDictGermline_1_6_0( intervals=self.intervals, bam=self.bam, reference=self.reference, sampleName=self.sample_name, var2vcfSampleName=self.sample_name, alleleFreqThreshold=self.allele_freq_threshold, var2vcfAlleleFreqThreshold=self.allele_freq_threshold, chromNamesAreNumbers=True, vcfFormat=True, chromColumn=1, regStartCol=2, geneEndCol=3, ), ) self.step( "annotate", BcfToolsAnnotate_1_5(file=self.vardict.out, headerLines=self.header_lines), ) self.step( "split_multi_allele", SplitMultiAllele(vcf=self.annotate.out, reference=self.reference), ) self.step("trim", TrimIUPAC_0_0_5(vcf=self.split_multi_allele.out)) self.output("vardict_variants", source=self.vardict.out) self.output("out", source=self.trim.out)