def find_mutation_files(
input_files, combined_maf=False, max_peptide_length=31):
"""
Collect all .vcf/.maf file paths in the `input_filenames` list.
Returns a dictionary mapping patient IDs to DataFrames containing basic
variant information (chr, pos, ref, alt). The patient IDs will be each
filename without its extension, unless the argument combined_maf is True.
In this case, patient IDs are derived from the tumor barcode column in
each MAF file.
"""
mutation_files = OrderedDict()
for path in input_filenames:
_, filename = split(path)
base, ext = splitext(filename)
if ext in MUTATION_FILE_EXTENSIONS:
if ext.endswith('maf') and combined_maf:
maf_df = load_maf(path)
file_patients = {}
for barcode, group_df in (
maf_df.groupby(['Tumor_Sample_Barcode'])):
vcf_df = maf_to_vcf(group_df)
patient_id = get_patient_id(barcode)
file_patients[patient_id] = vcf_df
else:
patient_id = get_patient_id(base)
vcf_df = load_variants(path)
file_patients = {patient_id: vcf_df}
for patient_id, vcf_df in file_patients.iteritems():
patient_id = "-".join(patient_id.split("-")[:3])
if patient_id in mutation_files:
logging.warning(
"Already processed patient %s before file %s",
patient_id,
path)
else:
mutation_files[patient_id] = vcf_df
if args.debug_patient_id:
patient_id = args.debug_patient_id
mutation_files = {patient_id: mutation_files[patient_id]}
return mutation_files
def find_mutation_files(input_files,
combined_maf=False,
max_peptide_length=31):
"""
Collect all .vcf/.maf file paths in the `input_filenames` list.
Returns a dictionary mapping patient IDs to DataFrames containing basic
variant information (chr, pos, ref, alt). The patient IDs will be each
filename without its extension, unless the argument combined_maf is True.
In this case, patient IDs are derived from the tumor barcode column in
each MAF file.
"""
mutation_files = OrderedDict()
for path in input_filenames:
_, filename = split(path)
base, ext = splitext(filename)
if ext in MUTATION_FILE_EXTENSIONS:
if ext.endswith('maf') and combined_maf:
maf_df = load_maf(path)
file_patients = {}
for barcode, group_df in (maf_df.groupby(
['Tumor_Sample_Barcode'])):
vcf_df = maf_to_vcf(group_df)
patient_id = get_patient_id(barcode)
file_patients[patient_id] = vcf_df
else:
patient_id = get_patient_id(base)
vcf_df = load_variants(path)
file_patients = {patient_id: vcf_df}
for patient_id, vcf_df in file_patients.iteritems():
patient_id = "-".join(patient_id.split("-")[:3])
if patient_id in mutation_files:
logging.warning(
"Already processed patient %s before file %s",
patient_id, path)
else:
mutation_files[patient_id] = vcf_df
if args.debug_patient_id:
patient_id = args.debug_patient_id
mutation_files = {patient_id: mutation_files[patient_id]}
return mutation_files
def load_variants(input_filename):
"""
Read the input file into a DataFrame containing (at least)
the basic columns of a VCF:
- chr
- pos
- ref
- alt
"""
# VCF and MAF files give us the raw mutations in genomic coordinates
if input_filename.endswith(".vcf"):
vcf_df = load_vcf(input_filename)
elif input_filename.endswith(".maf"):
maf_df = load_maf(input_filename)
vcf_df = maf_to_vcf(maf_df)
elif input_filename.endswith("tab"):
tab_df = pd.read_csv(input_filename, sep='\t', header=0)
vcf_df = tab_to_vcf(tab_df)
else:
assert False, "Unrecognized file type %s" % input_filename
return vcf_df
def load_variants(input_filename):
"""
Read the input file into a DataFrame containing (at least)
the basic columns of a VCF:
- chr
- pos
- ref
- alt
"""
# VCF and MAF files give us the raw mutations in genomic coordinates
if input_filename.endswith(".vcf"):
vcf_df = load_vcf(input_filename)
elif input_filename.endswith(".maf"):
maf_df = load_maf(input_filename)
vcf_df = maf_to_vcf(maf_df)
elif input_filename.endswith("tab"):
tab_df = pd.read_csv(input_filename, sep='\t', header=0)
vcf_df = tab_to_vcf(tab_df)
else:
assert False, "Unrecognized file type %s" % input_filename
return vcf_df
