def create_peaktable(samples):
"""create a table of peak counts per sample to use with differential peak calling
"""
data = dd.get_data_from_sample(samples[0])
peakcounts = []
out_dir = os.path.join(dd.get_work_dir(data), "consensus")
out_file = os.path.join(out_dir, "consensus-counts.tsv")
if dd.get_chip_method(data) == "chip":
for data in dd.sample_data_iterator(samples):
peakcounts.append(tz.get_in(("peak_counts"), data))
elif dd.get_chip_method(data) == "atac":
for data in dd.sample_data_iterator(samples):
if bam.is_paired(dd.get_work_bam(data)):
peakcounts.append(tz.get_in(("peak_counts", "NF"), data))
else:
logger.info(f"Creating peak table from full BAM file because "
f"{dd.get_work_bam(data)} is single-ended.")
peakcounts.append(tz.get_in(("peak_counts", "full"), data))
combined_peaks = count.combine_count_files(peakcounts,
out_file,
ext=".counts")
new_data = []
for data in dd.sample_data_iterator(samples):
data = tz.assoc_in(data, ("peak_counts", "peaktable"), combined_peaks)
new_data.append(data)
new_samples = dd.get_samples_from_datalist(new_data)
return new_samples
def create_peaktable(samples):
"""create a table of peak counts per sample to use with differential peak calling
"""
data = dd.get_data_from_sample(samples[0])
peakcounts = []
out_dir = os.path.join(dd.get_work_dir(data), "consensus")
out_file = os.path.join(out_dir, "consensus-counts.tsv")
if dd.get_chip_method(data) == "chip":
for data in dd.sample_data_iterator(samples):
peakcounts.append(tz.get_in(("peak_counts"), data))
elif dd.get_chip_method(data) == "atac":
for data in dd.sample_data_iterator(samples):
peakcounts.append(tz.get_in(("peak_counts", "NF"), data))
combined_peaks = count.combine_count_files(peakcounts,
out_file,
ext=".counts")
new_data = []
for data in dd.sample_data_iterator(samples):
data = tz.assoc_in(data, ("peak_counts", "peaktable"), combined_peaks)
new_data.append(data)
new_samples = dd.get_samples_from_datalist(new_data)
return new_samples