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223,400 | bcbio/bcbio-nextgen | bcbio/install.py | _datatarget_defaults | def _datatarget_defaults(args, default_args):
"""Set data installation targets, handling defaults.
Sets variation, rnaseq, smallrna as default targets if we're not
isolated to a single method.
Provides back compatibility for toolplus specifications.
"""
default_data = default_args.get("datatar... | python | def _datatarget_defaults(args, default_args):
"""Set data installation targets, handling defaults.
Sets variation, rnaseq, smallrna as default targets if we're not
isolated to a single method.
Provides back compatibility for toolplus specifications.
"""
default_data = default_args.get("datatar... | [
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Sets variation, rnaseq, smallrna as default targets if we're not
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223,401 | bcbio/bcbio-nextgen | bcbio/cwl/workflow.py | _merge_wf_inputs | def _merge_wf_inputs(new, out, wf_outputs, to_ignore, parallel, nested_inputs):
"""Merge inputs for a sub-workflow, adding any not present inputs in out.
Skips inputs that are internally generated or generated and ignored, keeping
only as inputs those that we do not generate internally.
"""
interna... | python | def _merge_wf_inputs(new, out, wf_outputs, to_ignore, parallel, nested_inputs):
"""Merge inputs for a sub-workflow, adding any not present inputs in out.
Skips inputs that are internally generated or generated and ignored, keeping
only as inputs those that we do not generate internally.
"""
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223,402 | bcbio/bcbio-nextgen | bcbio/cwl/workflow.py | _merge_wf_outputs | def _merge_wf_outputs(new, cur, parallel):
"""Merge outputs for a sub-workflow, replacing variables changed in later steps.
ignore_ids are those used internally in a sub-workflow but not exposed to subsequent steps
"""
new_ids = set([])
out = []
for v in new:
outv = {}
outv["sou... | python | def _merge_wf_outputs(new, cur, parallel):
"""Merge outputs for a sub-workflow, replacing variables changed in later steps.
ignore_ids are those used internally in a sub-workflow but not exposed to subsequent steps
"""
new_ids = set([])
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223,403 | bcbio/bcbio-nextgen | bcbio/cwl/workflow.py | _extract_from_subworkflow | def _extract_from_subworkflow(vs, step):
"""Remove internal variable names when moving from sub-workflow to main.
"""
substep_ids = set([x.name for x in step.workflow])
out = []
for var in vs:
internal = False
parts = var["id"].split("/")
if len(parts) > 1:
if par... | python | def _extract_from_subworkflow(vs, step):
"""Remove internal variable names when moving from sub-workflow to main.
"""
substep_ids = set([x.name for x in step.workflow])
out = []
for var in vs:
internal = False
parts = var["id"].split("/")
if len(parts) > 1:
if par... | [
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223,404 | bcbio/bcbio-nextgen | bcbio/cwl/workflow.py | is_cwl_record | def is_cwl_record(d):
"""Check if an input is a CWL record, from any level of nesting.
"""
if isinstance(d, dict):
if d.get("type") == "record":
return d
else:
recs = list(filter(lambda x: x is not None, [is_cwl_record(v) for v in d.values()]))
return recs... | python | def is_cwl_record(d):
"""Check if an input is a CWL record, from any level of nesting.
"""
if isinstance(d, dict):
if d.get("type") == "record":
return d
else:
recs = list(filter(lambda x: x is not None, [is_cwl_record(v) for v in d.values()]))
return recs... | [
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223,405 | bcbio/bcbio-nextgen | bcbio/cwl/workflow.py | _get_step_inputs | def _get_step_inputs(step, file_vs, std_vs, parallel_ids, wf=None):
"""Retrieve inputs for a step from existing variables.
Potentially nests inputs to deal with merging split variables. If
we split previously and are merging now, then we only nest those
coming from the split process.
"""
inputs... | python | def _get_step_inputs(step, file_vs, std_vs, parallel_ids, wf=None):
"""Retrieve inputs for a step from existing variables.
Potentially nests inputs to deal with merging split variables. If
we split previously and are merging now, then we only nest those
coming from the split process.
"""
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223,406 | bcbio/bcbio-nextgen | bcbio/cwl/workflow.py | _nest_variable | def _nest_variable(v, check_records=False):
"""Nest a variable when moving from scattered back to consolidated.
check_records -- avoid re-nesting a record input if it comes from a previous
step and is already nested, don't need to re-array.
"""
if (check_records and is_cwl_record(v) and len(v["id"]... | python | def _nest_variable(v, check_records=False):
"""Nest a variable when moving from scattered back to consolidated.
check_records -- avoid re-nesting a record input if it comes from a previous
step and is already nested, don't need to re-array.
"""
if (check_records and is_cwl_record(v) and len(v["id"]... | [
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223,407 | bcbio/bcbio-nextgen | bcbio/cwl/workflow.py | _clean_output | def _clean_output(v):
"""Remove output specific variables to allow variables to be inputs to next steps.
"""
out = copy.deepcopy(v)
outb = out.pop("outputBinding", {})
if "secondaryFiles" in outb:
out["secondaryFiles"] = outb["secondaryFiles"]
return out | python | def _clean_output(v):
"""Remove output specific variables to allow variables to be inputs to next steps.
"""
out = copy.deepcopy(v)
outb = out.pop("outputBinding", {})
if "secondaryFiles" in outb:
out["secondaryFiles"] = outb["secondaryFiles"]
return out | [
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223,408 | bcbio/bcbio-nextgen | bcbio/cwl/workflow.py | _get_variable | def _get_variable(vid, variables):
"""Retrieve an input variable from our existing pool of options.
"""
if isinstance(vid, six.string_types):
vid = get_base_id(vid)
else:
vid = _get_string_vid(vid)
for v in variables:
if vid == get_base_id(v["id"]):
return copy.de... | python | def _get_variable(vid, variables):
"""Retrieve an input variable from our existing pool of options.
"""
if isinstance(vid, six.string_types):
vid = get_base_id(vid)
else:
vid = _get_string_vid(vid)
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if vid == get_base_id(v["id"]):
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223,409 | bcbio/bcbio-nextgen | bcbio/cwl/workflow.py | _handle_special_inputs | def _handle_special_inputs(inputs, variables):
"""Adjust input variables based on special cases.
This case handles inputs where we are optional or can have flexible choices.
XXX Need to better expose this at a top level definition.
"""
from bcbio import structural
optional = [["config", "algor... | python | def _handle_special_inputs(inputs, variables):
"""Adjust input variables based on special cases.
This case handles inputs where we are optional or can have flexible choices.
XXX Need to better expose this at a top level definition.
"""
from bcbio import structural
optional = [["config", "algor... | [
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223,410 | bcbio/bcbio-nextgen | bcbio/cwl/workflow.py | _create_record | def _create_record(name, field_defs, step_name, inputs, unlist, file_vs, std_vs, parallel):
"""Create an output record by rearranging inputs.
Batching processes create records that reformat the inputs for
parallelization.
"""
if field_defs:
fields = []
inherit = []
inherit_a... | python | def _create_record(name, field_defs, step_name, inputs, unlist, file_vs, std_vs, parallel):
"""Create an output record by rearranging inputs.
Batching processes create records that reformat the inputs for
parallelization.
"""
if field_defs:
fields = []
inherit = []
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223,411 | bcbio/bcbio-nextgen | bcbio/cwl/workflow.py | _infer_record_outputs | def _infer_record_outputs(inputs, unlist, file_vs, std_vs, parallel, to_include=None,
exclude=None):
"""Infer the outputs of a record from the original inputs
"""
fields = []
unlist = set([_get_string_vid(x) for x in unlist])
input_vids = set([_get_string_vid(v) for v in _h... | python | def _infer_record_outputs(inputs, unlist, file_vs, std_vs, parallel, to_include=None,
exclude=None):
"""Infer the outputs of a record from the original inputs
"""
fields = []
unlist = set([_get_string_vid(x) for x in unlist])
input_vids = set([_get_string_vid(v) for v in _h... | [
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223,412 | bcbio/bcbio-nextgen | bcbio/cwl/workflow.py | _create_variable | def _create_variable(orig_v, step, variables):
"""Create a new output variable, potentially over-writing existing or creating new.
"""
# get current variable, and convert to be the output of our process step
try:
v = _get_variable(orig_v["id"], variables)
except ValueError:
v = copy.... | python | def _create_variable(orig_v, step, variables):
"""Create a new output variable, potentially over-writing existing or creating new.
"""
# get current variable, and convert to be the output of our process step
try:
v = _get_variable(orig_v["id"], variables)
except ValueError:
v = copy.... | [
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223,413 | bcbio/bcbio-nextgen | bcbio/cwl/workflow.py | _merge_variables | def _merge_variables(new, cur):
"""Add any new variables to the world representation in cur.
Replaces any variables adjusted by previous steps.
"""
new_added = set([])
out = []
for cur_var in cur:
updated = False
for new_var in new:
if get_base_id(new_var["id"]) == g... | python | def _merge_variables(new, cur):
"""Add any new variables to the world representation in cur.
Replaces any variables adjusted by previous steps.
"""
new_added = set([])
out = []
for cur_var in cur:
updated = False
for new_var in new:
if get_base_id(new_var["id"]) == g... | [
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223,414 | bcbio/bcbio-nextgen | bcbio/pipeline/disambiguate/__init__.py | split | def split(*items):
"""Split samples into all possible genomes for alignment.
"""
out = []
for data in [x[0] for x in items]:
dis_orgs = data["config"]["algorithm"].get("disambiguate")
if dis_orgs:
if not data.get("disambiguate", None):
data["disambiguate"] = {... | python | def split(*items):
"""Split samples into all possible genomes for alignment.
"""
out = []
for data in [x[0] for x in items]:
dis_orgs = data["config"]["algorithm"].get("disambiguate")
if dis_orgs:
if not data.get("disambiguate", None):
data["disambiguate"] = {... | [
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223,415 | bcbio/bcbio-nextgen | bcbio/pipeline/disambiguate/__init__.py | resolve | def resolve(items, run_parallel):
"""Combine aligned and split samples into final set of disambiguated reads.
"""
out = []
to_process = collections.defaultdict(list)
for data in [x[0] for x in items]:
if "disambiguate" in data:
split_part = tuple([int(x) for x in data["align_spli... | python | def resolve(items, run_parallel):
"""Combine aligned and split samples into final set of disambiguated reads.
"""
out = []
to_process = collections.defaultdict(list)
for data in [x[0] for x in items]:
if "disambiguate" in data:
split_part = tuple([int(x) for x in data["align_spli... | [
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223,416 | bcbio/bcbio-nextgen | bcbio/pipeline/disambiguate/__init__.py | merge_extras | def merge_extras(items, config):
"""Merge extra disambiguated reads into a final BAM file.
"""
final = {}
for extra_name in items[0]["disambiguate"].keys():
in_files = []
for data in items:
in_files.append(data["disambiguate"][extra_name])
out_file = "%s-allmerged%s" ... | python | def merge_extras(items, config):
"""Merge extra disambiguated reads into a final BAM file.
"""
final = {}
for extra_name in items[0]["disambiguate"].keys():
in_files = []
for data in items:
in_files.append(data["disambiguate"][extra_name])
out_file = "%s-allmerged%s" ... | [
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223,417 | bcbio/bcbio-nextgen | bcbio/pipeline/disambiguate/__init__.py | _merge_summary | def _merge_summary(in_files, out_file, data):
"""Create one big summary file for disambiguation from multiple splits.
"""
if not utils.file_exists(out_file):
with file_transaction(data, out_file) as tx_out_file:
with open(tx_out_file, "w") as out_handle:
for i, in_file in... | python | def _merge_summary(in_files, out_file, data):
"""Create one big summary file for disambiguation from multiple splits.
"""
if not utils.file_exists(out_file):
with file_transaction(data, out_file) as tx_out_file:
with open(tx_out_file, "w") as out_handle:
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223,418 | bcbio/bcbio-nextgen | bcbio/pipeline/disambiguate/__init__.py | _run_python | def _run_python(work_bam_a, work_bam_b, out_dir, aligner, prefix, items):
"""Run python version of disambiguation
"""
Args = collections.namedtuple("Args", "A B output_dir intermediate_dir "
"no_sort prefix aligner")
args = Args(work_bam_a, work_bam_b, out_dir, out_di... | python | def _run_python(work_bam_a, work_bam_b, out_dir, aligner, prefix, items):
"""Run python version of disambiguation
"""
Args = collections.namedtuple("Args", "A B output_dir intermediate_dir "
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args = Args(work_bam_a, work_bam_b, out_dir, out_di... | [
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223,419 | bcbio/bcbio-nextgen | bcbio/cwl/main.py | run | def run(args):
"""Run a CWL preparation pipeline.
"""
dirs, config, run_info_yaml = run_info.prep_system(args.sample_config, args.systemconfig)
integrations = args.integrations if hasattr(args, "integrations") else {}
world = run_info.organize(dirs, config, run_info_yaml, is_cwl=True, integrations=i... | python | def run(args):
"""Run a CWL preparation pipeline.
"""
dirs, config, run_info_yaml = run_info.prep_system(args.sample_config, args.systemconfig)
integrations = args.integrations if hasattr(args, "integrations") else {}
world = run_info.organize(dirs, config, run_info_yaml, is_cwl=True, integrations=i... | [
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223,420 | bcbio/bcbio-nextgen | bcbio/variation/coverage.py | assign_interval | def assign_interval(data):
"""Identify coverage based on percent of genome covered and relation to targets.
Classifies coverage into 3 categories:
- genome: Full genome coverage
- regional: Regional coverage, like exome capture, with off-target reads
- amplicon: Amplication based regional cov... | python | def assign_interval(data):
"""Identify coverage based on percent of genome covered and relation to targets.
Classifies coverage into 3 categories:
- genome: Full genome coverage
- regional: Regional coverage, like exome capture, with off-target reads
- amplicon: Amplication based regional cov... | [
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223,421 | bcbio/bcbio-nextgen | bcbio/variation/coverage.py | calculate | def calculate(bam_file, data, sv_bed):
"""Calculate coverage in parallel using mosdepth.
Removes duplicates and secondary reads from the counts:
if ( b->core.flag & (BAM_FUNMAP | BAM_FSECONDARY | BAM_FQCFAIL | BAM_FDUP) ) continue;
"""
params = {"min": dd.get_coverage_depth_min(data)}
variant_r... | python | def calculate(bam_file, data, sv_bed):
"""Calculate coverage in parallel using mosdepth.
Removes duplicates and secondary reads from the counts:
if ( b->core.flag & (BAM_FUNMAP | BAM_FSECONDARY | BAM_FQCFAIL | BAM_FDUP) ) continue;
"""
params = {"min": dd.get_coverage_depth_min(data)}
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223,422 | bcbio/bcbio-nextgen | bcbio/variation/coverage.py | _create_genome_regions | def _create_genome_regions(data):
"""Create whole genome contigs we want to process, only non-alts.
Skips problem contigs like HLAs for downstream analysis.
"""
work_dir = utils.safe_makedir(os.path.join(dd.get_work_dir(data), "coverage", dd.get_sample_name(data)))
variant_regions = os.path.join(wo... | python | def _create_genome_regions(data):
"""Create whole genome contigs we want to process, only non-alts.
Skips problem contigs like HLAs for downstream analysis.
"""
work_dir = utils.safe_makedir(os.path.join(dd.get_work_dir(data), "coverage", dd.get_sample_name(data)))
variant_regions = os.path.join(wo... | [
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223,423 | bcbio/bcbio-nextgen | bcbio/variation/coverage.py | _subset_to_variant_regions | def _subset_to_variant_regions(callable_file, variant_regions, data):
"""Subset output callable file to only variant regions of interest.
"""
out_file = "%s-vrsubset.bed" % utils.splitext_plus(callable_file)[0]
if not utils.file_uptodate(out_file, callable_file):
with file_transaction(data, out_... | python | def _subset_to_variant_regions(callable_file, variant_regions, data):
"""Subset output callable file to only variant regions of interest.
"""
out_file = "%s-vrsubset.bed" % utils.splitext_plus(callable_file)[0]
if not utils.file_uptodate(out_file, callable_file):
with file_transaction(data, out_... | [
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223,424 | bcbio/bcbio-nextgen | bcbio/variation/coverage.py | _average_genome_coverage | def _average_genome_coverage(data, bam_file):
"""Quickly calculate average coverage for whole genome files using indices.
Includes all reads, with duplicates. Uses sampling of 10M reads.
"""
total = sum([c.size for c in ref.file_contigs(dd.get_ref_file(data), data["config"])])
read_counts = sum(x.a... | python | def _average_genome_coverage(data, bam_file):
"""Quickly calculate average coverage for whole genome files using indices.
Includes all reads, with duplicates. Uses sampling of 10M reads.
"""
total = sum([c.size for c in ref.file_contigs(dd.get_ref_file(data), data["config"])])
read_counts = sum(x.a... | [
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223,425 | bcbio/bcbio-nextgen | bcbio/variation/coverage.py | regions_coverage | def regions_coverage(bed_file, target_name, data):
"""Generate coverage over regions of interest using mosdepth.
"""
ready_bed = tz.get_in(["depth", target_name, "regions"], data)
if ready_bed:
return ready_bed
else:
return run_mosdepth(data, target_name, bed_file).regions | python | def regions_coverage(bed_file, target_name, data):
"""Generate coverage over regions of interest using mosdepth.
"""
ready_bed = tz.get_in(["depth", target_name, "regions"], data)
if ready_bed:
return ready_bed
else:
return run_mosdepth(data, target_name, bed_file).regions | [
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223,426 | bcbio/bcbio-nextgen | bcbio/variation/coverage.py | coverage_region_detailed_stats | def coverage_region_detailed_stats(target_name, bed_file, data, out_dir):
"""
Calculate coverage at different completeness cutoff
for region in coverage option.
"""
if bed_file and utils.file_exists(bed_file):
ready_depth = tz.get_in(["depth", target_name], data)
if ready_depth:
... | python | def coverage_region_detailed_stats(target_name, bed_file, data, out_dir):
"""
Calculate coverage at different completeness cutoff
for region in coverage option.
"""
if bed_file and utils.file_exists(bed_file):
ready_depth = tz.get_in(["depth", target_name], data)
if ready_depth:
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223,427 | bcbio/bcbio-nextgen | bcbio/heterogeneity/loh.py | get_coords | def get_coords(data):
"""Retrieve coordinates of genes of interest for prioritization.
Can read from CIViC input data or a supplied BED file of chrom, start, end
and gene information.
"""
for category, vtypes in [("LOH", {"LOSS", "HETEROZYGOSITY"}),
("amplification", {"... | python | def get_coords(data):
"""Retrieve coordinates of genes of interest for prioritization.
Can read from CIViC input data or a supplied BED file of chrom, start, end
and gene information.
"""
for category, vtypes in [("LOH", {"LOSS", "HETEROZYGOSITY"}),
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223,428 | bcbio/bcbio-nextgen | bcbio/heterogeneity/loh.py | _civic_regions | def _civic_regions(civic_file, variant_types=None, diseases=None, drugs=None):
"""Retrieve gene regions and names filtered by variant_types and diseases.
"""
if isinstance(diseases, six.string_types):
diseases = [diseases]
with utils.open_gzipsafe(civic_file) as in_handle:
reader = csv.r... | python | def _civic_regions(civic_file, variant_types=None, diseases=None, drugs=None):
"""Retrieve gene regions and names filtered by variant_types and diseases.
"""
if isinstance(diseases, six.string_types):
diseases = [diseases]
with utils.open_gzipsafe(civic_file) as in_handle:
reader = csv.r... | [
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223,429 | bcbio/bcbio-nextgen | bcbio/heterogeneity/loh.py | summary_status | def summary_status(call, data):
"""Retrieve status in regions of interest, along with heterogeneity metrics.
Provides output with overall purity and ploidy, along with region
specific calls.
"""
out_file = None
if call.get("vrn_file") and os.path.exists(call.get("vrn_file")):
out_file =... | python | def summary_status(call, data):
"""Retrieve status in regions of interest, along with heterogeneity metrics.
Provides output with overall purity and ploidy, along with region
specific calls.
"""
out_file = None
if call.get("vrn_file") and os.path.exists(call.get("vrn_file")):
out_file =... | [
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223,430 | bcbio/bcbio-nextgen | bcbio/heterogeneity/loh.py | _check_copy_number_changes | def _check_copy_number_changes(svtype, cn, minor_cn, data):
"""Check if copy number changes match the expected svtype.
"""
if svtype == "LOH" and minor_cn == 0:
return svtype
elif svtype == "amplification" and cn > dd.get_ploidy(data):
return svtype
else:
return "std" | python | def _check_copy_number_changes(svtype, cn, minor_cn, data):
"""Check if copy number changes match the expected svtype.
"""
if svtype == "LOH" and minor_cn == 0:
return svtype
elif svtype == "amplification" and cn > dd.get_ploidy(data):
return svtype
else:
return "std" | [
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223,431 | bcbio/bcbio-nextgen | bcbio/heterogeneity/loh.py | _titancna_summary | def _titancna_summary(call, data):
"""Summarize purity, ploidy and LOH for TitanCNA.
"""
out = {}
for svtype, coords in get_coords(data):
cur_calls = {k: collections.defaultdict(int) for k in coords.keys()}
with open(call["subclones"]) as in_handle:
header = in_handle.readlin... | python | def _titancna_summary(call, data):
"""Summarize purity, ploidy and LOH for TitanCNA.
"""
out = {}
for svtype, coords in get_coords(data):
cur_calls = {k: collections.defaultdict(int) for k in coords.keys()}
with open(call["subclones"]) as in_handle:
header = in_handle.readlin... | [
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223,432 | bcbio/bcbio-nextgen | bcbio/heterogeneity/loh.py | _purecn_summary | def _purecn_summary(call, data):
"""Summarize purity, ploidy and LOH for PureCN.
"""
out = {}
for svtype, coords in get_coords(data):
cur_calls = {k: collections.defaultdict(int) for k in coords.keys()}
with open(call["loh"]) as in_handle:
in_handle.readline() # header
... | python | def _purecn_summary(call, data):
"""Summarize purity, ploidy and LOH for PureCN.
"""
out = {}
for svtype, coords in get_coords(data):
cur_calls = {k: collections.defaultdict(int) for k in coords.keys()}
with open(call["loh"]) as in_handle:
in_handle.readline() # header
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223,433 | bcbio/bcbio-nextgen | scripts/utils/plink_to_vcf.py | fix_vcf_line | def fix_vcf_line(parts, ref_base):
"""Orient VCF allele calls with respect to reference base.
Handles cases with ref and variant swaps. strand complements.
"""
swap = {"1/1": "0/0", "0/1": "0/1", "0/0": "1/1", "./.": "./."}
complements = {"G": "C", "A": "T", "C": "G", "T": "A", "N": "N"}
varinf... | python | def fix_vcf_line(parts, ref_base):
"""Orient VCF allele calls with respect to reference base.
Handles cases with ref and variant swaps. strand complements.
"""
swap = {"1/1": "0/0", "0/1": "0/1", "0/0": "1/1", "./.": "./."}
complements = {"G": "C", "A": "T", "C": "G", "T": "A", "N": "N"}
varinf... | [
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223,434 | bcbio/bcbio-nextgen | scripts/utils/plink_to_vcf.py | fix_nonref_positions | def fix_nonref_positions(in_file, ref_file):
"""Fix Genotyping VCF positions where the bases are all variants.
The plink/pseq output does not handle these correctly, and
has all reference/variant bases reversed.
"""
ignore_chrs = ["."]
ref2bit = twobit.TwoBitFile(open(ref_file))
out_file = ... | python | def fix_nonref_positions(in_file, ref_file):
"""Fix Genotyping VCF positions where the bases are all variants.
The plink/pseq output does not handle these correctly, and
has all reference/variant bases reversed.
"""
ignore_chrs = ["."]
ref2bit = twobit.TwoBitFile(open(ref_file))
out_file = ... | [
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223,435 | bcbio/bcbio-nextgen | bcbio/structural/cn_mops.py | run | def run(items, background=None):
"""Detect copy number variations from batched set of samples using cn.mops.
"""
if not background: background = []
names = [tz.get_in(["rgnames", "sample"], x) for x in items + background]
work_bams = [x["align_bam"] for x in items + background]
if len(items + ba... | python | def run(items, background=None):
"""Detect copy number variations from batched set of samples using cn.mops.
"""
if not background: background = []
names = [tz.get_in(["rgnames", "sample"], x) for x in items + background]
work_bams = [x["align_bam"] for x in items + background]
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223,436 | bcbio/bcbio-nextgen | bcbio/structural/cn_mops.py | _combine_out_files | def _combine_out_files(chr_files, work_dir, data):
"""Concatenate all CNV calls into a single file.
"""
out_file = "%s.bed" % sshared.outname_from_inputs(chr_files)
if not utils.file_exists(out_file):
with file_transaction(data, out_file) as tx_out_file:
with open(tx_out_file, "w") a... | python | def _combine_out_files(chr_files, work_dir, data):
"""Concatenate all CNV calls into a single file.
"""
out_file = "%s.bed" % sshared.outname_from_inputs(chr_files)
if not utils.file_exists(out_file):
with file_transaction(data, out_file) as tx_out_file:
with open(tx_out_file, "w") a... | [
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223,437 | bcbio/bcbio-nextgen | bcbio/structural/cn_mops.py | _prep_sample_cnvs | def _prep_sample_cnvs(cnv_file, data):
"""Convert a multiple sample CNV file into a single BED file for a sample.
Handles matching and fixing names where R converts numerical IDs (1234) into
strings by adding an X (X1234), and converts other characters into '.'s.
http://stat.ethz.ch/R-manual/R-devel/li... | python | def _prep_sample_cnvs(cnv_file, data):
"""Convert a multiple sample CNV file into a single BED file for a sample.
Handles matching and fixing names where R converts numerical IDs (1234) into
strings by adding an X (X1234), and converts other characters into '.'s.
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223,438 | bcbio/bcbio-nextgen | bcbio/structural/cn_mops.py | _run_on_chrom | def _run_on_chrom(chrom, work_bams, names, work_dir, items):
"""Run cn.mops on work BAMs for a specific chromosome.
"""
local_sitelib = utils.R_sitelib()
batch = sshared.get_cur_batch(items)
ext = "-%s-cnv" % batch if batch else "-cnv"
out_file = os.path.join(work_dir, "%s%s-%s.bed" % (os.path.s... | python | def _run_on_chrom(chrom, work_bams, names, work_dir, items):
"""Run cn.mops on work BAMs for a specific chromosome.
"""
local_sitelib = utils.R_sitelib()
batch = sshared.get_cur_batch(items)
ext = "-%s-cnv" % batch if batch else "-cnv"
out_file = os.path.join(work_dir, "%s%s-%s.bed" % (os.path.s... | [
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223,439 | bcbio/bcbio-nextgen | bcbio/structural/cn_mops.py | _get_regional_bed_file | def _get_regional_bed_file(data):
"""If we are running a non-genome analysis, pull the regional file for analysis.
"""
variant_regions = bedutils.merge_overlaps(tz.get_in(["config", "algorithm", "variant_regions"], data),
data)
is_genome = data["config"]["al... | python | def _get_regional_bed_file(data):
"""If we are running a non-genome analysis, pull the regional file for analysis.
"""
variant_regions = bedutils.merge_overlaps(tz.get_in(["config", "algorithm", "variant_regions"], data),
data)
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223,440 | bcbio/bcbio-nextgen | bcbio/structural/cn_mops.py | _population_load_script | def _population_load_script(work_bams, names, chrom, pairmode, items):
"""Prepare BAMs for assessing CNVs in a population.
"""
bed_file = _get_regional_bed_file(items[0])
if bed_file:
return _population_prep_targeted.format(bam_file_str=",".join(work_bams), names_str=",".join(names),
... | python | def _population_load_script(work_bams, names, chrom, pairmode, items):
"""Prepare BAMs for assessing CNVs in a population.
"""
bed_file = _get_regional_bed_file(items[0])
if bed_file:
return _population_prep_targeted.format(bam_file_str=",".join(work_bams), names_str=",".join(names),
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223,441 | bcbio/bcbio-nextgen | bcbio/ngsalign/postalign.py | tobam_cl | def tobam_cl(data, out_file, is_paired=False):
"""Prepare command line for producing de-duplicated sorted output.
- If no deduplication, sort and prepare a BAM file.
- If paired, then use samblaster and prepare discordant outputs.
- If unpaired, use biobambam's bammarkduplicates
"""
do_dedup = ... | python | def tobam_cl(data, out_file, is_paired=False):
"""Prepare command line for producing de-duplicated sorted output.
- If no deduplication, sort and prepare a BAM file.
- If paired, then use samblaster and prepare discordant outputs.
- If unpaired, use biobambam's bammarkduplicates
"""
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223,442 | bcbio/bcbio-nextgen | bcbio/ngsalign/postalign.py | _get_cores_memory | def _get_cores_memory(data, downscale=2):
"""Retrieve cores and memory, using samtools as baseline.
For memory, scaling down because we share with alignment and de-duplication.
"""
resources = config_utils.get_resources("samtools", data["config"])
num_cores = data["config"]["algorithm"].get("num_co... | python | def _get_cores_memory(data, downscale=2):
"""Retrieve cores and memory, using samtools as baseline.
For memory, scaling down because we share with alignment and de-duplication.
"""
resources = config_utils.get_resources("samtools", data["config"])
num_cores = data["config"]["algorithm"].get("num_co... | [
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223,443 | bcbio/bcbio-nextgen | bcbio/ngsalign/postalign.py | sam_to_sortbam_cl | def sam_to_sortbam_cl(data, tx_out_file, name_sort=False):
"""Convert to sorted BAM output.
Set name_sort to True to sort reads by queryname
"""
samtools = config_utils.get_program("samtools", data["config"])
cores, mem = _get_cores_memory(data, downscale=2)
tmp_file = "%s-sorttmp" % utils.spli... | python | def sam_to_sortbam_cl(data, tx_out_file, name_sort=False):
"""Convert to sorted BAM output.
Set name_sort to True to sort reads by queryname
"""
samtools = config_utils.get_program("samtools", data["config"])
cores, mem = _get_cores_memory(data, downscale=2)
tmp_file = "%s-sorttmp" % utils.spli... | [
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223,444 | bcbio/bcbio-nextgen | bcbio/ngsalign/postalign.py | samblaster_dedup_sort | def samblaster_dedup_sort(data, tx_out_file, tx_sr_file, tx_disc_file):
"""Deduplicate and sort with samblaster, produces split read and discordant pair files.
"""
samblaster = config_utils.get_program("samblaster", data["config"])
samtools = config_utils.get_program("samtools", data["config"])
tmp_... | python | def samblaster_dedup_sort(data, tx_out_file, tx_sr_file, tx_disc_file):
"""Deduplicate and sort with samblaster, produces split read and discordant pair files.
"""
samblaster = config_utils.get_program("samblaster", data["config"])
samtools = config_utils.get_program("samtools", data["config"])
tmp_... | [
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223,445 | bcbio/bcbio-nextgen | bcbio/ngsalign/postalign.py | _biobambam_dedup_sort | def _biobambam_dedup_sort(data, tx_out_file):
"""Perform streaming deduplication and sorting with biobambam's bamsormadup
"""
samtools = config_utils.get_program("samtools", data["config"])
cores, mem = _get_cores_memory(data, downscale=2)
tmp_file = "%s-sorttmp" % utils.splitext_plus(tx_out_file)[0... | python | def _biobambam_dedup_sort(data, tx_out_file):
"""Perform streaming deduplication and sorting with biobambam's bamsormadup
"""
samtools = config_utils.get_program("samtools", data["config"])
cores, mem = _get_cores_memory(data, downscale=2)
tmp_file = "%s-sorttmp" % utils.splitext_plus(tx_out_file)[0... | [
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223,446 | bcbio/bcbio-nextgen | bcbio/ngsalign/postalign.py | _sam_to_grouped_umi_cl | def _sam_to_grouped_umi_cl(data, umi_consensus, tx_out_file):
"""Mark duplicates on aligner output and convert to grouped UMIs by position.
Works with either a separate umi_file or UMI embedded in the read names.
"""
tmp_file = "%s-sorttmp" % utils.splitext_plus(tx_out_file)[0]
jvm_opts = _get_fgbi... | python | def _sam_to_grouped_umi_cl(data, umi_consensus, tx_out_file):
"""Mark duplicates on aligner output and convert to grouped UMIs by position.
Works with either a separate umi_file or UMI embedded in the read names.
"""
tmp_file = "%s-sorttmp" % utils.splitext_plus(tx_out_file)[0]
jvm_opts = _get_fgbi... | [
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223,447 | bcbio/bcbio-nextgen | bcbio/ngsalign/postalign.py | umi_consensus | def umi_consensus(data):
"""Convert UMI grouped reads into fastq pair for re-alignment.
"""
align_bam = dd.get_work_bam(data)
umi_method, umi_tag = _check_umi_type(align_bam)
f1_out = "%s-cumi-1.fq.gz" % utils.splitext_plus(align_bam)[0]
f2_out = "%s-cumi-2.fq.gz" % utils.splitext_plus(align_bam... | python | def umi_consensus(data):
"""Convert UMI grouped reads into fastq pair for re-alignment.
"""
align_bam = dd.get_work_bam(data)
umi_method, umi_tag = _check_umi_type(align_bam)
f1_out = "%s-cumi-1.fq.gz" % utils.splitext_plus(align_bam)[0]
f2_out = "%s-cumi-2.fq.gz" % utils.splitext_plus(align_bam... | [
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223,448 | bcbio/bcbio-nextgen | bcbio/ngsalign/postalign.py | _get_fgbio_options | def _get_fgbio_options(data, estimated_defaults, umi_method):
"""Get adjustable, through resources, or default options for fgbio.
"""
group_opts = ["--edits", "--min-map-q"]
cons_opts = ["--min-input-base-quality"]
if umi_method != "paired":
cons_opts += ["--min-reads", "--max-reads"]
fi... | python | def _get_fgbio_options(data, estimated_defaults, umi_method):
"""Get adjustable, through resources, or default options for fgbio.
"""
group_opts = ["--edits", "--min-map-q"]
cons_opts = ["--min-input-base-quality"]
if umi_method != "paired":
cons_opts += ["--min-reads", "--max-reads"]
fi... | [
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223,449 | bcbio/bcbio-nextgen | bcbio/ngsalign/postalign.py | _check_dedup | def _check_dedup(data):
"""Check configuration for de-duplication.
Defaults to no de-duplication for RNA-seq and small RNA, the
back compatible default. Allow overwriting with explicit
`mark_duplicates: true` setting.
Also defaults to false for no alignment inputs.
"""
if dd.get_analysis(da... | python | def _check_dedup(data):
"""Check configuration for de-duplication.
Defaults to no de-duplication for RNA-seq and small RNA, the
back compatible default. Allow overwriting with explicit
`mark_duplicates: true` setting.
Also defaults to false for no alignment inputs.
"""
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223,450 | bcbio/bcbio-nextgen | bcbio/ngsalign/postalign.py | dedup_bam | def dedup_bam(in_bam, data):
"""Perform non-stream based deduplication of BAM input files using biobambam.
"""
if _check_dedup(data):
out_file = os.path.join(utils.safe_makedir(os.path.join(os.getcwd(), "align", dd.get_sample_name(data))),
"%s-dedup%s" % utils.splitex... | python | def dedup_bam(in_bam, data):
"""Perform non-stream based deduplication of BAM input files using biobambam.
"""
if _check_dedup(data):
out_file = os.path.join(utils.safe_makedir(os.path.join(os.getcwd(), "align", dd.get_sample_name(data))),
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223,451 | bcbio/bcbio-nextgen | bcbio/structural/titancna.py | _finalize_sv | def _finalize_sv(solution_file, data):
"""Add output files from TitanCNA calling optional solution.
"""
out = {"variantcaller": "titancna"}
with open(solution_file) as in_handle:
solution = dict(zip(in_handle.readline().strip("\r\n").split("\t"),
in_handle.readline().... | python | def _finalize_sv(solution_file, data):
"""Add output files from TitanCNA calling optional solution.
"""
out = {"variantcaller": "titancna"}
with open(solution_file) as in_handle:
solution = dict(zip(in_handle.readline().strip("\r\n").split("\t"),
in_handle.readline().... | [
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223,452 | bcbio/bcbio-nextgen | bcbio/structural/titancna.py | _should_run | def _should_run(het_file):
"""Check for enough input data to proceed with analysis.
"""
has_hets = False
with open(het_file) as in_handle:
for i, line in enumerate(in_handle):
if i > 1:
has_hets = True
break
return has_hets | python | def _should_run(het_file):
"""Check for enough input data to proceed with analysis.
"""
has_hets = False
with open(het_file) as in_handle:
for i, line in enumerate(in_handle):
if i > 1:
has_hets = True
break
return has_hets | [
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223,453 | bcbio/bcbio-nextgen | bcbio/structural/titancna.py | _titan_cn_file | def _titan_cn_file(cnr_file, work_dir, data):
"""Convert CNVkit or GATK4 normalized input into TitanCNA ready format.
"""
out_file = os.path.join(work_dir, "%s.cn" % (utils.splitext_plus(os.path.basename(cnr_file))[0]))
support_cols = {"cnvkit": ["chromosome", "start", "end", "log2"],
... | python | def _titan_cn_file(cnr_file, work_dir, data):
"""Convert CNVkit or GATK4 normalized input into TitanCNA ready format.
"""
out_file = os.path.join(work_dir, "%s.cn" % (utils.splitext_plus(os.path.basename(cnr_file))[0]))
support_cols = {"cnvkit": ["chromosome", "start", "end", "log2"],
... | [
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223,454 | bcbio/bcbio-nextgen | bcbio/structural/titancna.py | to_vcf | def to_vcf(in_file, caller, header_fn, vcf_fn, data, sep="\t"):
"""Convert output TitanCNA segs file into bgzipped VCF.
"""
out_file = "%s.vcf" % utils.splitext_plus(in_file)[0]
if not utils.file_exists(out_file + ".gz") and not utils.file_exists(out_file):
with file_transaction(data, out_file) ... | python | def to_vcf(in_file, caller, header_fn, vcf_fn, data, sep="\t"):
"""Convert output TitanCNA segs file into bgzipped VCF.
"""
out_file = "%s.vcf" % utils.splitext_plus(in_file)[0]
if not utils.file_exists(out_file + ".gz") and not utils.file_exists(out_file):
with file_transaction(data, out_file) ... | [
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223,455 | bcbio/bcbio-nextgen | bcbio/structural/metasv.py | run | def run(items):
"""Run MetaSV if we have enough supported callers, adding output to the set of calls.
"""
assert len(items) == 1, "Expect one input to MetaSV ensemble calling"
data = items[0]
work_dir = _sv_workdir(data)
out_file = os.path.join(work_dir, "variants.vcf.gz")
cmd = _get_cmd() +... | python | def run(items):
"""Run MetaSV if we have enough supported callers, adding output to the set of calls.
"""
assert len(items) == 1, "Expect one input to MetaSV ensemble calling"
data = items[0]
work_dir = _sv_workdir(data)
out_file = os.path.join(work_dir, "variants.vcf.gz")
cmd = _get_cmd() +... | [
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223,456 | bcbio/bcbio-nextgen | bcbio/rnaseq/count.py | combine_count_files | def combine_count_files(files, out_file=None, ext=".fpkm"):
"""
combine a set of count files into a single combined file
"""
files = list(files)
if not files:
return None
assert all([file_exists(x) for x in files]), \
"Some count files in %s do not exist." % files
for f in fi... | python | def combine_count_files(files, out_file=None, ext=".fpkm"):
"""
combine a set of count files into a single combined file
"""
files = list(files)
if not files:
return None
assert all([file_exists(x) for x in files]), \
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223,457 | bcbio/bcbio-nextgen | scripts/utils/cwltool2nextflow.py | nf_step_to_process | def nf_step_to_process(step, out_handle):
"""Convert CWL step into a nextflow process.
"""
pprint.pprint(step)
directives = []
for req in step["task_definition"]["requirements"]:
if req["requirement_type"] == "docker":
directives.append("container '%s'" % req["value"])
e... | python | def nf_step_to_process(step, out_handle):
"""Convert CWL step into a nextflow process.
"""
pprint.pprint(step)
directives = []
for req in step["task_definition"]["requirements"]:
if req["requirement_type"] == "docker":
directives.append("container '%s'" % req["value"])
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223,458 | bcbio/bcbio-nextgen | scripts/utils/cwltool2nextflow.py | nf_input_to_cl | def nf_input_to_cl(inp):
"""Convert an input description into command line argument.
"""
sep = " " if inp.get("separate") else ""
val = "'%s'" % inp.get("default") if inp.get("default") else "$%s" % inp["name"]
return "%s%s%s" % (inp["prefix"], sep, val) | python | def nf_input_to_cl(inp):
"""Convert an input description into command line argument.
"""
sep = " " if inp.get("separate") else ""
val = "'%s'" % inp.get("default") if inp.get("default") else "$%s" % inp["name"]
return "%s%s%s" % (inp["prefix"], sep, val) | [
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223,459 | bcbio/bcbio-nextgen | scripts/utils/cwltool2nextflow.py | _wf_to_dict | def _wf_to_dict(wf):
"""Parse a workflow into cwl2wdl style dictionary.
"""
inputs, outputs = _get_wf_inout(wf)
out = {"name": _id_to_name(wf.tool["id"]).replace("-", "_"), "inputs": inputs,
"outputs": outputs, "steps": [], "subworkflows": [],
"requirements": []}
for step in wf... | python | def _wf_to_dict(wf):
"""Parse a workflow into cwl2wdl style dictionary.
"""
inputs, outputs = _get_wf_inout(wf)
out = {"name": _id_to_name(wf.tool["id"]).replace("-", "_"), "inputs": inputs,
"outputs": outputs, "steps": [], "subworkflows": [],
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223,460 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _get_validate | def _get_validate(data):
"""Retrieve items to validate, from single samples or from combined joint calls.
"""
if data.get("vrn_file") and tz.get_in(["config", "algorithm", "validate"], data):
return utils.deepish_copy(data)
elif "group_orig" in data:
for sub in multi.get_orig_items(data)... | python | def _get_validate(data):
"""Retrieve items to validate, from single samples or from combined joint calls.
"""
if data.get("vrn_file") and tz.get_in(["config", "algorithm", "validate"], data):
return utils.deepish_copy(data)
elif "group_orig" in data:
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223,461 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | normalize_input_path | def normalize_input_path(x, data):
"""Normalize path for input files, handling relative paths.
Looks for non-absolute paths in local and fastq directories
"""
if x is None:
return None
elif os.path.isabs(x):
return os.path.normpath(x)
else:
for d in [data["dirs"].get("fas... | python | def normalize_input_path(x, data):
"""Normalize path for input files, handling relative paths.
Looks for non-absolute paths in local and fastq directories
"""
if x is None:
return None
elif os.path.isabs(x):
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223,462 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _get_caller_supplement | def _get_caller_supplement(caller, data):
"""Some callers like MuTect incorporate a second caller for indels.
"""
if caller == "mutect":
icaller = tz.get_in(["config", "algorithm", "indelcaller"], data)
if icaller:
caller = "%s/%s" % (caller, icaller)
return caller | python | def _get_caller_supplement(caller, data):
"""Some callers like MuTect incorporate a second caller for indels.
"""
if caller == "mutect":
icaller = tz.get_in(["config", "algorithm", "indelcaller"], data)
if icaller:
caller = "%s/%s" % (caller, icaller)
return caller | [
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223,463 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _pick_lead_item | def _pick_lead_item(items):
"""Choose lead item for a set of samples.
Picks tumors for tumor/normal pairs and first sample for batch groups.
"""
paired = vcfutils.get_paired(items)
if paired:
return paired.tumor_data
else:
return list(items)[0] | python | def _pick_lead_item(items):
"""Choose lead item for a set of samples.
Picks tumors for tumor/normal pairs and first sample for batch groups.
"""
paired = vcfutils.get_paired(items)
if paired:
return paired.tumor_data
else:
return list(items)[0] | [
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223,464 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _normalize_cwl_inputs | def _normalize_cwl_inputs(items):
"""Extract variation and validation data from CWL input list of batched samples.
"""
with_validate = {}
vrn_files = []
ready_items = []
batch_samples = []
for data in (cwlutils.normalize_missing(utils.to_single_data(d)) for d in items):
batch_samples... | python | def _normalize_cwl_inputs(items):
"""Extract variation and validation data from CWL input list of batched samples.
"""
with_validate = {}
vrn_files = []
ready_items = []
batch_samples = []
for data in (cwlutils.normalize_missing(utils.to_single_data(d)) for d in items):
batch_samples... | [
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223,465 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | compare_to_rm | def compare_to_rm(data):
"""Compare final variant calls against reference materials of known calls.
"""
if isinstance(data, (list, tuple)) and cwlutils.is_cwl_run(utils.to_single_data(data[0])):
data = _normalize_cwl_inputs(data)
toval_data = _get_validate(data)
toval_data = cwlutils.unpack_... | python | def compare_to_rm(data):
"""Compare final variant calls against reference materials of known calls.
"""
if isinstance(data, (list, tuple)) and cwlutils.is_cwl_run(utils.to_single_data(data[0])):
data = _normalize_cwl_inputs(data)
toval_data = _get_validate(data)
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223,466 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _annotate_validations | def _annotate_validations(eval_files, data):
"""Add annotations about potential problem regions to validation VCFs.
"""
for key in ["tp", "tp-calls", "fp", "fn"]:
if eval_files.get(key):
eval_files[key] = annotation.add_genome_context(eval_files[key], data)
return eval_files | python | def _annotate_validations(eval_files, data):
"""Add annotations about potential problem regions to validation VCFs.
"""
for key in ["tp", "tp-calls", "fp", "fn"]:
if eval_files.get(key):
eval_files[key] = annotation.add_genome_context(eval_files[key], data)
return eval_files | [
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223,467 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _setup_call_false | def _setup_call_false(vrn_file, rm_bed, base_dir, data, call_type):
"""Create set of false positives or ngatives for inputs with empty truth sets.
"""
out_file = os.path.join(base_dir, "%s.vcf.gz" % call_type)
if not utils.file_exists(out_file):
with file_transaction(data, out_file) as tx_out_fi... | python | def _setup_call_false(vrn_file, rm_bed, base_dir, data, call_type):
"""Create set of false positives or ngatives for inputs with empty truth sets.
"""
out_file = os.path.join(base_dir, "%s.vcf.gz" % call_type)
if not utils.file_exists(out_file):
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223,468 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _rtg_add_summary_file | def _rtg_add_summary_file(eval_files, base_dir, data):
"""Parse output TP FP and FN files to generate metrics for plotting.
"""
out_file = os.path.join(base_dir, "validate-summary.csv")
if not utils.file_uptodate(out_file, eval_files.get("tp", eval_files.get("fp", eval_files["fn"]))):
with file_... | python | def _rtg_add_summary_file(eval_files, base_dir, data):
"""Parse output TP FP and FN files to generate metrics for plotting.
"""
out_file = os.path.join(base_dir, "validate-summary.csv")
if not utils.file_uptodate(out_file, eval_files.get("tp", eval_files.get("fp", eval_files["fn"]))):
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223,469 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _prepare_inputs | def _prepare_inputs(vrn_file, rm_file, rm_interval_file, base_dir, data):
"""Prepare input VCF and BED files for validation.
"""
if not rm_file.endswith(".vcf.gz") or not os.path.exists(rm_file + ".tbi"):
rm_file = vcfutils.bgzip_and_index(rm_file, data["config"], out_dir=base_dir)
if len(vcfuti... | python | def _prepare_inputs(vrn_file, rm_file, rm_interval_file, base_dir, data):
"""Prepare input VCF and BED files for validation.
"""
if not rm_file.endswith(".vcf.gz") or not os.path.exists(rm_file + ".tbi"):
rm_file = vcfutils.bgzip_and_index(rm_file, data["config"], out_dir=base_dir)
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223,470 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _pick_best_quality_score | def _pick_best_quality_score(vrn_file):
"""Flexible quality score selection, picking the best available.
Implementation based on discussion:
https://github.com/bcbio/bcbio-nextgen/commit/a538cecd86c0000d17d3f9d4f8ac9d2da04f9884#commitcomment-14539249
(RTG=AVR/GATK=VQSLOD/MuTect=t_lod_fstar, otherwise... | python | def _pick_best_quality_score(vrn_file):
"""Flexible quality score selection, picking the best available.
Implementation based on discussion:
https://github.com/bcbio/bcbio-nextgen/commit/a538cecd86c0000d17d3f9d4f8ac9d2da04f9884#commitcomment-14539249
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223,471 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _get_merged_intervals | def _get_merged_intervals(rm_interval_file, vrn_file, base_dir, data):
"""Retrieve intervals to run validation on, merging reference and callable BED files.
"""
a_intervals = get_analysis_intervals(data, vrn_file, base_dir)
if a_intervals:
final_intervals = shared.remove_lcr_regions(a_intervals,... | python | def _get_merged_intervals(rm_interval_file, vrn_file, base_dir, data):
"""Retrieve intervals to run validation on, merging reference and callable BED files.
"""
a_intervals = get_analysis_intervals(data, vrn_file, base_dir)
if a_intervals:
final_intervals = shared.remove_lcr_regions(a_intervals,... | [
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223,472 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _callable_from_gvcf | def _callable_from_gvcf(data, vrn_file, out_dir):
"""Retrieve callable regions based on ref call regions in gVCF.
Uses https://github.com/lijiayong/gvcf_regions
"""
methods = {"freebayes": "freebayes", "platypus": "platypus",
"gatk-haplotype": "gatk"}
gvcf_type = methods.get(dd.get_v... | python | def _callable_from_gvcf(data, vrn_file, out_dir):
"""Retrieve callable regions based on ref call regions in gVCF.
Uses https://github.com/lijiayong/gvcf_regions
"""
methods = {"freebayes": "freebayes", "platypus": "platypus",
"gatk-haplotype": "gatk"}
gvcf_type = methods.get(dd.get_v... | [
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223,473 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | get_analysis_intervals | def get_analysis_intervals(data, vrn_file, base_dir):
"""Retrieve analysis regions for the current variant calling pipeline.
"""
from bcbio.bam import callable
if vrn_file and vcfutils.is_gvcf_file(vrn_file):
callable_bed = _callable_from_gvcf(data, vrn_file, base_dir)
if callable_bed:
... | python | def get_analysis_intervals(data, vrn_file, base_dir):
"""Retrieve analysis regions for the current variant calling pipeline.
"""
from bcbio.bam import callable
if vrn_file and vcfutils.is_gvcf_file(vrn_file):
callable_bed = _callable_from_gvcf(data, vrn_file, base_dir)
if callable_bed:
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223,474 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _get_location_list | def _get_location_list(interval_bed):
"""Retrieve list of locations to analyze from input BED file.
"""
import pybedtools
regions = collections.OrderedDict()
for region in pybedtools.BedTool(interval_bed):
regions[str(region.chrom)] = None
return regions.keys() | python | def _get_location_list(interval_bed):
"""Retrieve list of locations to analyze from input BED file.
"""
import pybedtools
regions = collections.OrderedDict()
for region in pybedtools.BedTool(interval_bed):
regions[str(region.chrom)] = None
return regions.keys() | [
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223,475 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _run_bcbio_variation | def _run_bcbio_variation(vrn_file, rm_file, rm_interval_file, base_dir, sample, caller, data):
"""Run validation of a caller against the truth set using bcbio.variation.
"""
val_config_file = _create_validate_config_file(vrn_file, rm_file, rm_interval_file,
... | python | def _run_bcbio_variation(vrn_file, rm_file, rm_interval_file, base_dir, sample, caller, data):
"""Run validation of a caller against the truth set using bcbio.variation.
"""
val_config_file = _create_validate_config_file(vrn_file, rm_file, rm_interval_file,
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223,476 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _create_validate_config | def _create_validate_config(vrn_file, rm_file, rm_interval_file, base_dir, data):
"""Create a bcbio.variation configuration input for validation.
"""
ref_call = {"file": str(rm_file), "name": "ref", "type": "grading-ref",
"fix-sample-header": True, "remove-refcalls": True}
a_intervals = ... | python | def _create_validate_config(vrn_file, rm_file, rm_interval_file, base_dir, data):
"""Create a bcbio.variation configuration input for validation.
"""
ref_call = {"file": str(rm_file), "name": "ref", "type": "grading-ref",
"fix-sample-header": True, "remove-refcalls": True}
a_intervals = ... | [
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223,477 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | summarize_grading | def summarize_grading(samples, vkey="validate"):
"""Provide summaries of grading results across all samples.
Handles both traditional pipelines (validation part of variants) and CWL
pipelines (validation at top level)
"""
samples = list(utils.flatten(samples))
if not _has_grading_info(samples, ... | python | def summarize_grading(samples, vkey="validate"):
"""Provide summaries of grading results across all samples.
Handles both traditional pipelines (validation part of variants) and CWL
pipelines (validation at top level)
"""
samples = list(utils.flatten(samples))
if not _has_grading_info(samples, ... | [
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223,478 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _summarize_combined | def _summarize_combined(samples, vkey):
"""Prepare summarized CSV and plot files for samples to combine together.
Helps handle cases where we want to summarize over multiple samples.
"""
validate_dir = utils.safe_makedir(os.path.join(samples[0]["dirs"]["work"], vkey))
combined, _ = _group_validate_... | python | def _summarize_combined(samples, vkey):
"""Prepare summarized CSV and plot files for samples to combine together.
Helps handle cases where we want to summarize over multiple samples.
"""
validate_dir = utils.safe_makedir(os.path.join(samples[0]["dirs"]["work"], vkey))
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223,479 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | combine_validations | def combine_validations(items, vkey="validate"):
"""Combine multiple batch validations into validation outputs.
"""
csvs = set([])
pngs = set([])
for v in [x.get(vkey) for x in items]:
if v and v.get("grading_summary"):
csvs.add(v.get("grading_summary"))
if v and v.get("g... | python | def combine_validations(items, vkey="validate"):
"""Combine multiple batch validations into validation outputs.
"""
csvs = set([])
pngs = set([])
for v in [x.get(vkey) for x in items]:
if v and v.get("grading_summary"):
csvs.add(v.get("grading_summary"))
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223,480 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | freq_summary | def freq_summary(val_file, call_file, truth_file, target_name):
"""Summarize true and false positive calls by variant type and frequency.
Resolve differences in true/false calls based on output from hap.py:
https://github.com/sequencing/hap.py
"""
out_file = "%s-freqs.csv" % utils.splitext_plus(val... | python | def freq_summary(val_file, call_file, truth_file, target_name):
"""Summarize true and false positive calls by variant type and frequency.
Resolve differences in true/false calls based on output from hap.py:
https://github.com/sequencing/hap.py
"""
out_file = "%s-freqs.csv" % utils.splitext_plus(val... | [
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223,481 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _read_call_freqs | def _read_call_freqs(in_file, sample_name):
"""Identify frequencies for calls in the input file.
"""
from bcbio.heterogeneity import bubbletree
out = {}
with VariantFile(in_file) as call_in:
for rec in call_in:
if rec.filter.keys() == ["PASS"]:
for name, sample in... | python | def _read_call_freqs(in_file, sample_name):
"""Identify frequencies for calls in the input file.
"""
from bcbio.heterogeneity import bubbletree
out = {}
with VariantFile(in_file) as call_in:
for rec in call_in:
if rec.filter.keys() == ["PASS"]:
for name, sample in... | [
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223,482 | bcbio/bcbio-nextgen | bcbio/variation/validate.py | _read_truth_freqs | def _read_truth_freqs(in_file):
"""Read frequency of calls from truth VCF.
Currently handles DREAM data, needs generalization for other datasets.
"""
out = {}
with VariantFile(in_file) as bcf_in:
for rec in bcf_in:
freq = float(rec.info.get("VAF", 1.0))
out[_get_key(... | python | def _read_truth_freqs(in_file):
"""Read frequency of calls from truth VCF.
Currently handles DREAM data, needs generalization for other datasets.
"""
out = {}
with VariantFile(in_file) as bcf_in:
for rec in bcf_in:
freq = float(rec.info.get("VAF", 1.0))
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223,483 | bcbio/bcbio-nextgen | bcbio/cwl/cwlutils.py | to_rec | def to_rec(samples, default_keys=None):
"""Convert inputs into CWL records, useful for single item parallelization.
"""
recs = samples_to_records([normalize_missing(utils.to_single_data(x)) for x in samples], default_keys)
return [[x] for x in recs] | python | def to_rec(samples, default_keys=None):
"""Convert inputs into CWL records, useful for single item parallelization.
"""
recs = samples_to_records([normalize_missing(utils.to_single_data(x)) for x in samples], default_keys)
return [[x] for x in recs] | [
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223,484 | bcbio/bcbio-nextgen | bcbio/cwl/cwlutils.py | to_rec_single | def to_rec_single(samples, default_keys=None):
"""Convert output into a list of single CWL records.
"""
out = []
for data in samples:
recs = samples_to_records([normalize_missing(utils.to_single_data(data))], default_keys)
assert len(recs) == 1
out.append(recs[0])
return out | python | def to_rec_single(samples, default_keys=None):
"""Convert output into a list of single CWL records.
"""
out = []
for data in samples:
recs = samples_to_records([normalize_missing(utils.to_single_data(data))], default_keys)
assert len(recs) == 1
out.append(recs[0])
return out | [
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223,485 | bcbio/bcbio-nextgen | bcbio/cwl/cwlutils.py | handle_combined_input | def handle_combined_input(args):
"""Check for cases where we have a combined input nested list.
In these cases the CWL will be double nested:
[[[rec_a], [rec_b]]]
and we remove the outer nesting.
"""
cur_args = args[:]
while len(cur_args) == 1 and isinstance(cur_args[0], (list, tuple)):
... | python | def handle_combined_input(args):
"""Check for cases where we have a combined input nested list.
In these cases the CWL will be double nested:
[[[rec_a], [rec_b]]]
and we remove the outer nesting.
"""
cur_args = args[:]
while len(cur_args) == 1 and isinstance(cur_args[0], (list, tuple)):
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223,486 | bcbio/bcbio-nextgen | bcbio/cwl/cwlutils.py | normalize_missing | def normalize_missing(xs):
"""Normalize missing values to avoid string 'None' inputs.
"""
if isinstance(xs, dict):
for k, v in xs.items():
xs[k] = normalize_missing(v)
elif isinstance(xs, (list, tuple)):
xs = [normalize_missing(x) for x in xs]
elif isinstance(xs, six.stri... | python | def normalize_missing(xs):
"""Normalize missing values to avoid string 'None' inputs.
"""
if isinstance(xs, dict):
for k, v in xs.items():
xs[k] = normalize_missing(v)
elif isinstance(xs, (list, tuple)):
xs = [normalize_missing(x) for x in xs]
elif isinstance(xs, six.stri... | [
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223,487 | bcbio/bcbio-nextgen | bcbio/cwl/cwlutils.py | unpack_tarballs | def unpack_tarballs(xs, data, use_subdir=True):
"""Unpack workflow tarballs into ready to use directories.
"""
if isinstance(xs, dict):
for k, v in xs.items():
xs[k] = unpack_tarballs(v, data, use_subdir)
elif isinstance(xs, (list, tuple)):
xs = [unpack_tarballs(x, data, use_... | python | def unpack_tarballs(xs, data, use_subdir=True):
"""Unpack workflow tarballs into ready to use directories.
"""
if isinstance(xs, dict):
for k, v in xs.items():
xs[k] = unpack_tarballs(v, data, use_subdir)
elif isinstance(xs, (list, tuple)):
xs = [unpack_tarballs(x, data, use_... | [
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223,488 | bcbio/bcbio-nextgen | bcbio/cwl/cwlutils.py | _get_all_cwlkeys | def _get_all_cwlkeys(items, default_keys=None):
"""Retrieve cwlkeys from inputs, handling defaults which can be null.
When inputs are null in some and present in others, this creates unequal
keys in each sample, confusing decision making about which are primary and extras.
"""
if default_keys:
... | python | def _get_all_cwlkeys(items, default_keys=None):
"""Retrieve cwlkeys from inputs, handling defaults which can be null.
When inputs are null in some and present in others, this creates unequal
keys in each sample, confusing decision making about which are primary and extras.
"""
if default_keys:
... | [
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223,489 | bcbio/bcbio-nextgen | bcbio/cwl/cwlutils.py | split_data_cwl_items | def split_data_cwl_items(items, default_keys=None):
"""Split a set of CWL output dictionaries into data samples and CWL items.
Handles cases where we're arrayed on multiple things, like a set of regional
VCF calls and data objects.
"""
key_lens = set([])
for data in items:
key_lens.add(... | python | def split_data_cwl_items(items, default_keys=None):
"""Split a set of CWL output dictionaries into data samples and CWL items.
Handles cases where we're arrayed on multiple things, like a set of regional
VCF calls and data objects.
"""
key_lens = set([])
for data in items:
key_lens.add(... | [
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223,490 | bcbio/bcbio-nextgen | bcbio/cwl/cwlutils.py | samples_to_records | def samples_to_records(samples, default_keys=None):
"""Convert samples into output CWL records.
"""
from bcbio.pipeline import run_info
RECORD_CONVERT_TO_LIST = set(["config__algorithm__tools_on", "config__algorithm__tools_off",
"reference__genome_context"])
all_key... | python | def samples_to_records(samples, default_keys=None):
"""Convert samples into output CWL records.
"""
from bcbio.pipeline import run_info
RECORD_CONVERT_TO_LIST = set(["config__algorithm__tools_on", "config__algorithm__tools_off",
"reference__genome_context"])
all_key... | [
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223,491 | bcbio/bcbio-nextgen | bcbio/cwl/cwlutils.py | assign_complex_to_samples | def assign_complex_to_samples(items):
"""Assign complex inputs like variants and align outputs to samples.
Handles list inputs to record conversion where we have inputs from multiple
locations and need to ensure they are properly assigned to samples in many
environments.
The unpleasant approach he... | python | def assign_complex_to_samples(items):
"""Assign complex inputs like variants and align outputs to samples.
Handles list inputs to record conversion where we have inputs from multiple
locations and need to ensure they are properly assigned to samples in many
environments.
The unpleasant approach he... | [
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223,492 | bcbio/bcbio-nextgen | bcbio/pipeline/variation.py | _normalize_vc_input | def _normalize_vc_input(data):
"""Normalize different types of variant calling inputs.
Handles standard and ensemble inputs.
"""
if data.get("ensemble"):
for k in ["batch_samples", "validate", "vrn_file"]:
data[k] = data["ensemble"][k]
data["config"]["algorithm"]["variantcal... | python | def _normalize_vc_input(data):
"""Normalize different types of variant calling inputs.
Handles standard and ensemble inputs.
"""
if data.get("ensemble"):
for k in ["batch_samples", "validate", "vrn_file"]:
data[k] = data["ensemble"][k]
data["config"]["algorithm"]["variantcal... | [
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223,493 | bcbio/bcbio-nextgen | bcbio/pipeline/variation.py | _get_orig_items | def _get_orig_items(data):
"""Retrieve original items in a batch, handling CWL and standard cases.
"""
if isinstance(data, dict):
if dd.get_align_bam(data) and tz.get_in(["metadata", "batch"], data) and "group_orig" in data:
return vmulti.get_orig_items(data)
else:
re... | python | def _get_orig_items(data):
"""Retrieve original items in a batch, handling CWL and standard cases.
"""
if isinstance(data, dict):
if dd.get_align_bam(data) and tz.get_in(["metadata", "batch"], data) and "group_orig" in data:
return vmulti.get_orig_items(data)
else:
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223,494 | bcbio/bcbio-nextgen | bcbio/pipeline/variation.py | _symlink_to_workdir | def _symlink_to_workdir(data, key):
"""For CWL support, symlink files into a working directory if in read-only imports.
"""
orig_file = tz.get_in(key, data)
if orig_file and not orig_file.startswith(dd.get_work_dir(data)):
variantcaller = genotype.get_variantcaller(data, require_bam=False)
... | python | def _symlink_to_workdir(data, key):
"""For CWL support, symlink files into a working directory if in read-only imports.
"""
orig_file = tz.get_in(key, data)
if orig_file and not orig_file.startswith(dd.get_work_dir(data)):
variantcaller = genotype.get_variantcaller(data, require_bam=False)
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223,495 | bcbio/bcbio-nextgen | bcbio/pipeline/variation.py | _get_batch_representative | def _get_batch_representative(items, key):
"""Retrieve a representative data item from a batch.
Handles standard bcbio cases (a single data item) and CWL cases with
batches that have a consistent variant file.
"""
if isinstance(items, dict):
return items, items
else:
vals = set(... | python | def _get_batch_representative(items, key):
"""Retrieve a representative data item from a batch.
Handles standard bcbio cases (a single data item) and CWL cases with
batches that have a consistent variant file.
"""
if isinstance(items, dict):
return items, items
else:
vals = set(... | [
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223,496 | bcbio/bcbio-nextgen | bcbio/distributed/objectstore.py | _get_storage_manager | def _get_storage_manager(resource):
"""Return a storage manager which can process this resource."""
for manager in (AmazonS3, ArvadosKeep, SevenBridges, DNAnexus, AzureBlob, GoogleCloud, RegularServer):
if manager.check_resource(resource):
return manager()
raise ValueError("Unexpected o... | python | def _get_storage_manager(resource):
"""Return a storage manager which can process this resource."""
for manager in (AmazonS3, ArvadosKeep, SevenBridges, DNAnexus, AzureBlob, GoogleCloud, RegularServer):
if manager.check_resource(resource):
return manager()
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223,497 | bcbio/bcbio-nextgen | bcbio/distributed/objectstore.py | default_region | def default_region(fname):
"""Return the default region for the received resource.
Note:
This feature is available only for AmazonS3 storage manager.
"""
manager = _get_storage_manager(fname)
if hasattr(manager, "get_region"):
return manager.get_region()
raise NotImplementedErr... | python | def default_region(fname):
"""Return the default region for the received resource.
Note:
This feature is available only for AmazonS3 storage manager.
"""
manager = _get_storage_manager(fname)
if hasattr(manager, "get_region"):
return manager.get_region()
raise NotImplementedErr... | [
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This feature is available only for AmazonS3 storage manager. | [
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223,498 | bcbio/bcbio-nextgen | bcbio/distributed/objectstore.py | BlobHandle.blob_properties | def blob_properties(self):
"""Returns all user-defined metadata, standard HTTP properties,
and system properties for the blob.
"""
if not self._blob_properties:
self._blob_properties = self._blob_service.get_blob_properties(
container_name=self._container_name... | python | def blob_properties(self):
"""Returns all user-defined metadata, standard HTTP properties,
and system properties for the blob.
"""
if not self._blob_properties:
self._blob_properties = self._blob_service.get_blob_properties(
container_name=self._container_name... | [
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223,499 | bcbio/bcbio-nextgen | bcbio/distributed/objectstore.py | BlobHandle._chunk_offsets | def _chunk_offsets(self):
"""Iterator over chunk offests."""
index = 0
blob_size = self.blob_properties.get('content-length')
while index < blob_size:
yield index
index = index + self._chunk_size | python | def _chunk_offsets(self):
"""Iterator over chunk offests."""
index = 0
blob_size = self.blob_properties.get('content-length')
while index < blob_size:
yield index
index = index + self._chunk_size | [
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