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)