vcf_out.write( line_i + '\n' )
line_i = vcf_in.readline().rstrip()
vcf_out.write( line_i + '\n' )
# This line will be #CHROM:
header = line_i.split('\t')
sample_index = header.index(sample) - 9
# This will be the first variant line:
line_i = vcf_in.readline().rstrip()
while line_i:
vcf_i = genome.Vcf_line( line_i )
if vcf_i.filters == 'PASS':
refMQ = float( vcf_i.get_sample_value('refMQ', sample_index) )
altMQ = float( vcf_i.get_sample_value('altMQ', sample_index) )
refBQ = float( vcf_i.get_sample_value('refBQ', sample_index) )
altBQ = float( vcf_i.get_sample_value('altBQ', sample_index) )
refNM = float( vcf_i.get_sample_value('refNM', sample_index) )
altNM = float( vcf_i.get_sample_value('altNM', sample_index) )
fetSB = float( vcf_i.get_sample_value('fetSB', sample_index) )
fetCD = float( vcf_i.get_sample_value('fetCD', sample_index) )
zMQ = float( vcf_i.get_sample_value('zMQ', sample_index) )
zBQ = float( vcf_i.get_sample_value('zBQ', sample_index) )
MQ0 = int( vcf_i.get_sample_value('MQ0', sample_index) )
VAF = float( vcf_i.get_sample_value('VAF', sample_index) )
### It will be a single file, otherwise it goes chr1, chr2, ...., or in the list of files input as ordered:
for chr_i_vcf in right_files:
with genome.open_textfile(chr_i_vcf) as vcf:
line_i = vcf.readline().rstrip()
# Skip headers from now on:
while line_i.startswith('#'):
line_i = vcf.readline().rstrip()
# Doing the work here:
while line_i:
vcf_i = genome.Vcf_line(line_i)
num_samples = len(vcf_i.samples)
if num_samples == 1:
paired = False
elif num_samples == 2:
paired = True
elif num_samples > 2:
sys.stderr.write(
'We found more than 2 sammples in this VCF file. It may be messed up, but I\'ll just assume the first 2 samples mean anything at all'
)
paired = True
elif num_samples == 0:
def catch_up(line_1, line_2, file_1, file_2, output_vcf, id_1, id_2, id_12):
id_1, id_2, id_12 = id_1, id_2, id_12
vcf_1 = genome.Vcf_line(line_1)
vcf_2 = genome.Vcf_line(line_2)
coord_1 = [vcf_1.chromosome, vcf_1.position]
coord_2 = [vcf_2.chromosome, vcf_2.position]
print(coord_1, coord_2)
is_behind = whoisbehind(coord_1, coord_2)
# As long as the coordinates are not the same, and both files are not finished:
while is_behind != 10:
# If 1st VCF is behind:
if is_behind == 0:
item_1 = line_1.rstrip('\n').split('\t')
# Write, unless...
if item_1[idx_filter] != 'PrintEmALL':
#item_1[idx_id] = id_1
id_item = item_1[idx_id].split(';')
id_item.append(id_1)
item_1[idx_id] = ';'.join(id_item)
item_1[idx_id] = re.sub(r'^\.;', '', item_1[idx_id])
line_1 = '\t'.join(item_1)
output_vcf.write(line_1 + '\n')
line_1 = file_1.readline()
vcf_1 = genome.Vcf_line(line_1)
coord_1 = [vcf_1.chromosome, vcf_1.position]
# If 2nd VCF is behind:
elif is_behind == 1:
item_2 = line_2.rstrip('\n').split('\t')
# Write, unless...
#if item_2[idx_filter] != 'PrintEmALL':
#IF
#item_2[idx_id] = id_2
id_item = item_2[idx_id].split(';')
id_item.append(id_2)
item_2[idx_id] = ';'.join(id_item)
item_2[idx_id] = re.sub(r'^\.;', '', item_2[idx_id])
line_2 = '\t'.join(item_2)
output_vcf.write(line_2 + '\n')
## FI
line_2 = file_2.readline()
vcf_2 = genome.Vcf_line(line_2)
coord_2 = [vcf_2.chromosome, vcf_2.position]
is_behind = whoisbehind(coord_1, coord_2)
# Returns the value of the function:
if coord_1[0] == coord_2[0] == '':
result = 42
else:
item_1 = line_1.rstrip('\n').split('\t')
item_2 = line_2.rstrip('\n').split('\t')
#item_1[idx_id] = id_12
id_item = item_1[idx_id].split(';')
id_item.append(id_12)
item_1[idx_id] = ';'.join(id_item)
item_1[idx_id] = re.sub(r'^.;', '', item_1[idx_id])
line_1 = '\t'.join(item_1)
output_vcf.write(line_1 + '\n')
result = (
line_1,
line_2,
)
return result
while strelka_line.startswith('#'):
strelka_line = strelka.readline().rstrip()
# Get through all the headers:
while my_line.startswith('#') or my_line.startswith('track='):
my_line = my_sites.readline().rstrip()
# First line:
outhandle.write(out_header.replace('{', '').replace('}', '') + '\n')
while my_line:
# If VCF, get all the variants with the same coordinate into a list:
if is_vcf:
my_vcf = genome.Vcf_line(my_line)
my_coordinates = [(my_vcf.chromosome, my_vcf.position)]
variants_at_my_coordinate = []
alt_bases = my_vcf.altbase.split(',')
for alt_i in alt_bases:
vcf_i = copy(my_vcf)
vcf_i.altbase = alt_i
variants_at_my_coordinate.append(vcf_i)
# As long as the "coordinate" stays the same, it will keep reading until it's different.
while my_coordinates[0] == (my_vcf.chromosome, my_vcf.position):
my_line = my_sites.readline().rstrip()
my_vcf = genome.Vcf_line(my_line)
'##FORMAT=<ID=SCORE,Number=1,Type=Float,Description="SomaticSeq Probability (either fraction or Phred)">\n'
)
tumor_column = line_in.split('\t').index(tumor)
tumor_idx = tumor_column - 9
(normal_column, normal_idx) = (9, 0) if tumor_idx == 1 else (None, None)
# This is the #CHROM line
vcfout.write(line_in + '\n')
line_in = vcfin.readline().rstrip('\n')
# Move COMBO and NUM_TOOLS from INFO to Tumor Sample, and move QUAL to the Tumor Sample as well
while line_in:
vcf_line_in = genome.Vcf_line(line_in)
# New INFO
new_info = []
for info_item in vcf_line_in.get_info_items():
if not (info_item.startswith('NUM_TOOLS=')
or info_item.startswith(caller_string)):
new_info.append(info_item)
if new_info == []:
new_info_line = '.'
else:
new_info_line = ';'.join(new_info)
# FORMAT:
if somaticseq_trained: