def get_paired_bams(align_bams, items):
"""Split aligned bams into tumor / normal pairs if this is a paired analysis.
Allows cases with only tumor BAMs to handle callers that can work without
normal BAMs or with normal VCF panels.
"""
tumor_bam, tumor_name, normal_bam, normal_name, normal_panel, tumor_config, normal_data = (
None, ) * 7
for bamfile, item in zip(align_bams, items):
phenotype = get_paired_phenotype(item)
if phenotype == "normal":
normal_bam = bamfile
normal_name = dd.get_sample_name(item)
normal_data = item
elif phenotype == "tumor":
tumor_bam = bamfile
tumor_name = dd.get_sample_name(item)
tumor_data = item
tumor_config = item["config"]
normal_panel = dd.get_background_variant(item)
if tumor_bam or tumor_name:
return PairedData(tumor_bam, tumor_name, normal_bam, normal_name,
normal_panel, tumor_config, tumor_data, normal_data)
def get_paired_bams(align_bams, items):
"""Split aligned bams into tumor / normal pairs if this is a paired analysis.
Allows cases with only tumor BAMs to handle callers that can work without
normal BAMs or with normal VCF panels.
"""
tumor_bam, tumor_name, normal_bam, normal_name, normal_panel, tumor_config, normal_data = (None,) * 7
for bamfile, item in zip(align_bams, items):
phenotype = get_paired_phenotype(item)
if phenotype == "normal":
normal_bam = bamfile
normal_name = dd.get_sample_name(item)
normal_data = item
elif phenotype == "tumor":
tumor_bam = bamfile
tumor_name = dd.get_sample_name(item)
tumor_data = item
tumor_config = item["config"]
normal_panel = dd.get_background_variant(item)
if tumor_bam or tumor_name:
return PairedData(tumor_bam, tumor_name, normal_bam,
normal_name, normal_panel, tumor_config,
tumor_data, normal_data)