def finalize_sv(samples, config):
"""Combine results from multiple sv callers into a single ordered 'sv' key.
"""
by_bam = collections.OrderedDict()
for x in samples:
batch = dd.get_batch(x) or [dd.get_sample_name(x)]
try:
by_bam[x["align_bam"], tuple(batch)].append(x)
except KeyError:
by_bam[x["align_bam"], tuple(batch)] = [x]
by_batch = collections.OrderedDict()
lead_batches = {}
for grouped_calls in by_bam.values():
def orig_svcaller_order(x):
orig_callers = tz.get_in(["config", "algorithm", "svcaller_orig"],
x)
cur_caller = tz.get_in(["config", "algorithm", "svcaller"], x)
return orig_callers.index(cur_caller)
sorted_svcalls = sorted([x for x in grouped_calls if "sv" in x],
key=orig_svcaller_order)
final = grouped_calls[0]
if len(sorted_svcalls) > 0:
final["sv"] = reduce(operator.add,
[x["sv"] for x in sorted_svcalls])
final["config"]["algorithm"]["svcaller"] = final["config"][
"algorithm"].pop("svcaller_orig")
batch = dd.get_batch(final) or dd.get_sample_name(final)
batches = batch if isinstance(batch, (list, tuple)) else [batch]
if len(batches) > 1:
lead_batches[(dd.get_sample_name(final),
dd.get_phenotype(final) == "germline")] = batches[0]
for batch in batches:
try:
by_batch[batch].append(final)
except KeyError:
by_batch[batch] = [final]
out = []
for batch, items in by_batch.items():
if any("svplots" in dd.get_tools_on(d) for d in items):
items = plot.by_regions(items)
for data in items:
if lead_batches.get(
(dd.get_sample_name(data),
dd.get_phenotype(data) == "germline")) in [batch, None]:
out.append([data])
return out
def finalize_sv(samples, config, initial_only=False):
"""Combine results from multiple sv callers into a single ordered 'sv' key.
Handles ensemble calling and plotting of results.
"""
by_bam = collections.OrderedDict()
for x in samples:
try:
by_bam[x["align_bam"]].append(x)
except KeyError:
by_bam[x["align_bam"]] = [x]
by_batch = collections.OrderedDict()
lead_batches = {}
for grouped_calls in by_bam.values():
def orig_svcaller_order(x):
return _get_svcallers(x).index(x["config"]["algorithm"]["svcaller_active"])
sorted_svcalls = sorted([x for x in grouped_calls if "sv" in x], key=orig_svcaller_order)
final = grouped_calls[0]
if len(sorted_svcalls) > 0:
final_calls = reduce(operator.add, [x["sv"] for x in sorted_svcalls])
if not initial_only:
for caller in (c for c in _get_svcallers(final) if c in _ENSEMBLE_CALLERS):
final_calls = _ENSEMBLE_CALLERS[caller](final_calls, final)
final_calls = ensemble.summarize(final_calls, final, grouped_calls)
final_calls = validate.evaluate(final, final_calls)
final["sv"] = final_calls
del final["config"]["algorithm"]["svcaller_active"]
batch = dd.get_batch(final) or dd.get_sample_name(final)
batches = batch if isinstance(batch, (list, tuple)) else [batch]
lead_batches[dd.get_sample_name(final)] = batches[0]
for batch in batches:
try:
by_batch[batch].append(final)
except KeyError:
by_batch[batch] = [final]
out = []
for batch, items in by_batch.items():
if any("svplots" in dd.get_tools_on(d) for d in items):
plot_items = plot.by_regions(items)
else:
plot_items = items
for data in plot_items:
if lead_batches[dd.get_sample_name(data)] == batch:
out.append([data])
return out
def finalize_sv(samples, config, initial_only=False):
"""Combine results from multiple sv callers into a single ordered 'sv' key.
Handles ensemble calling and plotting of results.
"""
by_bam = collections.OrderedDict()
for x in samples:
try:
by_bam[x["align_bam"]].append(x)
except KeyError:
by_bam[x["align_bam"]] = [x]
by_batch = collections.OrderedDict()
lead_batches = {}
for grouped_calls in by_bam.values():
def orig_svcaller_order(x):
return _get_svcallers(x).index(x["config"]["algorithm"]["svcaller_active"])
sorted_svcalls = sorted([x for x in grouped_calls if "sv" in x],
key=orig_svcaller_order)
final = grouped_calls[0]
if len(sorted_svcalls) > 0:
final_calls = reduce(operator.add, [x["sv"] for x in sorted_svcalls])
if not initial_only:
for caller in (c for c in _get_svcallers(final) if c in _ENSEMBLE_CALLERS):
final_calls = _ENSEMBLE_CALLERS[caller](final_calls, final)
final_calls = ensemble.summarize(final_calls, final, grouped_calls)
final_calls = validate.evaluate(final, final_calls)
final["sv"] = final_calls
del final["config"]["algorithm"]["svcaller_active"]
batch = dd.get_batch(final) or dd.get_sample_name(final)
batches = batch if isinstance(batch, (list, tuple)) else [batch]
lead_batches[dd.get_sample_name(final)] = batches[0]
for batch in batches:
try:
by_batch[batch].append(final)
except KeyError:
by_batch[batch] = [final]
out = []
for batch, items in by_batch.items():
if any("svplots" in dd.get_tools_on(d) for d in items):
plot_items = plot.by_regions(items)
else:
plot_items = items
for data in plot_items:
if lead_batches[dd.get_sample_name(data)] == batch:
out.append([data])
return out
def finalize_sv(samples, config):
"""Combine results from multiple sv callers into a single ordered 'sv' key.
Handles ensemble calling and plotting of results.
"""
by_bam = collections.OrderedDict()
for x in samples:
try:
by_bam[x["align_bam"]].append(x)
except KeyError:
by_bam[x["align_bam"]] = [x]
highdepths = filter(
lambda x: x is not None,
list(set([tz.get_in(["config", "algorithm", "highdepth_regions"], x) for x in samples])),
)
by_batch = collections.OrderedDict()
lead_batches = {}
for grouped_calls in by_bam.values():
def orig_svcaller_order(x):
return _get_svcallers(x).index(x["config"]["algorithm"]["svcaller_active"])
sorted_svcalls = sorted([x for x in grouped_calls if "sv" in x], key=orig_svcaller_order)
final = grouped_calls[0]
if len(sorted_svcalls) > 0:
final_calls = reduce(operator.add, [x["sv"] for x in sorted_svcalls])
final_calls = ensemble.summarize(final_calls, final, highdepths)
final_calls = validate.evaluate(final, final_calls)
final["sv"] = final_calls
del final["config"]["algorithm"]["svcaller_active"]
batch = dd.get_batch(final) or dd.get_sample_name(final)
batches = batch if isinstance(batch, (list, tuple)) else [batch]
lead_batches[dd.get_sample_name(final)] = batches[0]
for batch in batches:
try:
by_batch[batch].append(final)
except KeyError:
by_batch[batch] = [final]
out = []
for batch, items in by_batch.items():
plot_items = plot.by_regions(items)
for data in plot_items:
if lead_batches[dd.get_sample_name(data)] == batch:
out.append([data])
return out
def finalize_sv(samples, config):
"""Combine results from multiple sv callers into a single ordered 'sv' key.
"""
by_bam = collections.OrderedDict()
for x in samples:
try:
by_bam[x["align_bam"]].append(x)
except KeyError:
by_bam[x["align_bam"]] = [x]
by_batch = collections.OrderedDict()
lead_batches = {}
for grouped_calls in by_bam.values():
def orig_svcaller_order(x):
return _get_svcallers(x).index(
x["config"]["algorithm"]["svcaller_active"])
sorted_svcalls = sorted([x for x in grouped_calls if "sv" in x],
key=orig_svcaller_order)
final = grouped_calls[0]
if len(sorted_svcalls) > 0:
final["sv"] = reduce(operator.add,
[x["sv"] for x in sorted_svcalls])
del final["config"]["algorithm"]["svcaller_active"]
batch = dd.get_batch(final) or dd.get_sample_name(final)
batches = batch if isinstance(batch, (list, tuple)) else [batch]
lead_batches[dd.get_sample_name(final)] = batches[0]
for batch in batches:
try:
by_batch[batch].append(final)
except KeyError:
by_batch[batch] = [final]
out = []
for batch, items in by_batch.items():
if any("svplots" in dd.get_tools_on(d) for d in items):
plot_items = plot.by_regions(items)
else:
plot_items = items
for data in plot_items:
if lead_batches[dd.get_sample_name(data)] == batch:
out.append([data])
return out
def finalize_sv(samples, config):
"""Combine results from multiple sv callers into a single ordered 'sv' key.
"""
by_bam = collections.OrderedDict()
for x in samples:
batch = dd.get_batch(x) or [dd.get_sample_name(x)]
try:
by_bam[x["align_bam"], tuple(batch)].append(x)
except KeyError:
by_bam[x["align_bam"], tuple(batch)] = [x]
by_batch = collections.OrderedDict()
lead_batches = {}
for grouped_calls in by_bam.values():
def orig_svcaller_order(x):
orig_callers = tz.get_in(["config", "algorithm", "svcaller_orig"], x)
cur_caller = tz.get_in(["config", "algorithm", "svcaller"], x)
return orig_callers.index(cur_caller)
sorted_svcalls = sorted([x for x in grouped_calls if "sv" in x],
key=orig_svcaller_order)
final = grouped_calls[0]
if len(sorted_svcalls) > 0:
final["sv"] = reduce(operator.add, [x["sv"] for x in sorted_svcalls])
final["config"]["algorithm"]["svcaller"] = final["config"]["algorithm"].pop("svcaller_orig")
batch = dd.get_batch(final) or dd.get_sample_name(final)
batches = batch if isinstance(batch, (list, tuple)) else [batch]
lead_batches[dd.get_sample_name(final)] = batches[0]
for batch in batches:
try:
by_batch[batch].append(final)
except KeyError:
by_batch[batch] = [final]
out = []
for batch, items in by_batch.items():
if any("svplots" in dd.get_tools_on(d) for d in items):
plot_items = plot.by_regions(items)
else:
plot_items = items
for data in plot_items:
if lead_batches[dd.get_sample_name(data)] == batch:
out.append([data])
return out