def _group_by_cnv_method(batches):
"""Group into batches samples with identical CNV/SV approaches.
Allows sharing of background samples across multiple batches,
using all normals from tumor/normal pairs with the same prep method
for background.
"""
CnvGroup = collections.namedtuple(
"CnvGroup", "items, work_dir, access_file, region_file")
out = []
groups = collections.defaultdict(list)
for batch, items in batches.items():
for data in items:
work_dir = utils.safe_makedir(
os.path.join(dd.get_work_dir(data), "structural", "bins",
batch))
cnv_file = get_base_cnv_regions(data,
work_dir,
"transcripts100",
include_gene_names=False)
if cnv_file:
break
assert cnv_file, (
"Did not find coverage regions for batch %s: %s" %
(batch, " ".join([dd.get_sample_name(d) for d in items])))
groups[(cnv_file, dd.get_prep_method(data))].append(
(items, data, work_dir))
for (cnv_file, _), cur_group in groups.items():
group_items = reduce(operator.add, [xs[0] for xs in cur_group])
access_file = tz.get_in(["config", "algorithm", "callable_regions"],
cur_group[0][1])
out.append(
CnvGroup(group_items, cur_group[0][2], access_file, cnv_file))
return out
def _group_by_cnv_method(batches):
"""Group into batches samples with identical CNV/SV approaches.
Allows sharing of background samples across multiple batches,
using all normals from tumor/normal pairs with the same prep method
for background.
"""
CnvGroup = collections.namedtuple("CnvGroup", "items, work_dir, access_file, region_file")
out = []
groups = collections.defaultdict(list)
for batch, items in batches.items():
for data in items:
work_dir = utils.safe_makedir(os.path.join(dd.get_work_dir(data), "structural", "bins", batch))
cnv_file = get_base_cnv_regions(data, work_dir, "transcripts100", include_gene_names=False)
if cnv_file:
break
assert cnv_file, ("Did not find coverage regions for batch %s: %s" %
(batch, " ".join([dd.get_sample_name(d) for d in items])))
groups[(cnv_file, dd.get_prep_method(data))].append((items, data, work_dir))
for (cnv_file, _), cur_group in groups.items():
group_items = reduce(operator.add, [xs[0] for xs in cur_group])
access_file = tz.get_in(["config", "algorithm", "callable_regions"], cur_group[0][1])
out.append(CnvGroup(group_items, cur_group[0][2], access_file, cnv_file))
return out
