def run(items):
"""Perform detection of structural variations with Manta.
"""
paired = vcfutils.get_paired(items)
data = paired.tumor_data if paired else items[0]
work_dir = _sv_workdir(data)
variant_file = _get_out_file(work_dir, paired)
if not utils.file_exists(variant_file):
with file_transaction(data, work_dir) as tx_work_dir:
utils.safe_makedir(tx_work_dir)
tx_workflow_file = _prep_config(items, paired, tx_work_dir)
_run_workflow(items, paired, tx_workflow_file, tx_work_dir)
assert utils.file_exists(variant_file), "Manta finished without output file %s" % variant_file
variant_file = shared.annotate_with_depth(variant_file, items)
out = []
upload_counts = collections.defaultdict(int)
for data in items:
if "break-point-inspector" in dd.get_tools_on(data):
if paired and paired.normal_bam and paired.tumor_name == dd.get_sample_name(data):
variant_file = _run_break_point_inspector(data, variant_file, paired, work_dir)
if "sv" not in data:
data["sv"] = []
final_vcf = shared.finalize_sv(variant_file, data, items)
vc = {"variantcaller": "manta",
"do_upload": upload_counts[final_vcf] == 0, # only upload a single file per batch
"vrn_file": final_vcf}
evidence_bam = _get_evidence_bam(work_dir, data)
if evidence_bam:
vc["read_evidence"] = evidence_bam
data["sv"].append(vc)
upload_counts[final_vcf] += 1
out.append(data)
return out
def run(items):
"""Perform detection of structural variations with Manta.
"""
paired = vcfutils.get_paired(items)
data = paired.tumor_data if paired else items[0]
work_dir = _sv_workdir(data)
variant_file = _get_out_file(work_dir, paired)
if not utils.file_exists(variant_file):
with file_transaction(data, work_dir) as tx_work_dir:
utils.safe_makedir(tx_work_dir)
tx_workflow_file = _prep_config(items, paired, tx_work_dir)
_run_workflow(items, paired, tx_workflow_file, tx_work_dir)
assert utils.file_exists(
variant_file), "Manta finished without output file %s" % variant_file
out = []
for data in items:
if paired and paired.normal_bam and "break-point-inspector" in dd.get_tools_on(
data):
variant_file = _run_break_point_inspector(data, variant_file,
paired)
if "sv" not in data:
data["sv"] = []
final_vcf = shared.finalize_sv(variant_file, data, items)
data["sv"].append({"variantcaller": "manta", "vrn_file": final_vcf})
out.append(data)
return out
def run(items):
"""Perform detection of structural variations with delly.
Performs post-call filtering with a custom filter tuned based
on NA12878 Moleculo and PacBio data, using calls prepared by
@ryanlayer and @cc2qe
Filters using the high quality variant pairs (DV) compared with
high quality reference pairs (DR).
"""
work_dir = utils.safe_makedir(
os.path.join(items[0]["dirs"]["work"], "structural",
items[0]["name"][-1], "delly"))
# Add core request for delly
config = copy.deepcopy(items[0]["config"])
delly_config = utils.get_in(config, ("resources", "delly"), {})
delly_config["cores"] = 1
config["resources"]["delly"] = delly_config
parallel = {
"type": "local",
"cores": config["algorithm"].get("num_cores", 1),
"progs": ["delly"]
}
work_bams = [dd.get_align_bam(d) for d in items]
ref_file = dd.get_ref_file(items[0])
sv_types = [
"DEL", "DUP"
] # "TRA" has invalid VCF END specifications that GATK doesn't like, "INV" very slow
exclude_file = _get_full_exclude_file(items, work_dir)
bytype_vcfs = run_multicore(
_run_delly,
[(work_bams, chrom, sv_type, ref_file, work_dir, items)
for (chrom, sv_type) in itertools.product(
sshared.get_sv_chroms(items, exclude_file), sv_types)], config,
parallel)
out_file = "%s.vcf.gz" % sshared.outname_from_inputs(bytype_vcfs)
combo_vcf = vcfutils.combine_variant_files(bytype_vcfs, out_file, ref_file,
config)
out = []
for data in items:
if "sv" not in data:
data["sv"] = []
base, ext = utils.splitext_plus(combo_vcf)
final_vcf = sshared.finalize_sv(combo_vcf, data, items)
if final_vcf:
delly_vcf = _delly_count_evidence_filter(final_vcf, data)
data["sv"].append({
"variantcaller": "delly",
"vrn_file": delly_vcf,
"exclude": exclude_file
})
out.append(data)
return out
def run(items):
"""Perform detection of structural variations with delly.
Performs post-call filtering with a custom filter tuned based
on NA12878 Moleculo and PacBio data, using calls prepared by
@ryanlayer and @cc2qe
Filters using the high quality variant pairs (DV) compared with
high quality reference pairs (DR).
"""
work_dir = utils.safe_makedir(
os.path.join(items[0]["dirs"]["work"], "structural",
dd.get_sample_name(items[0]), "delly"))
# Add core request for delly
config = copy.deepcopy(items[0]["config"])
delly_config = utils.get_in(config, ("resources", "delly"), {})
delly_config["cores"] = 1
config["resources"]["delly"] = delly_config
parallel = {
"type": "local",
"cores": config["algorithm"].get("num_cores", 1),
"progs": ["delly"]
}
work_bams = [dd.get_align_bam(d) for d in items]
ref_file = dd.get_ref_file(items[0])
exclude_file = _get_full_exclude_file(items, work_bams, work_dir)
bytype_vcfs = run_multicore(
_run_delly, [(work_bams, chrom, ref_file, work_dir, items)
for chrom in sshared.get_sv_chroms(items, exclude_file)],
config, parallel)
out_file = "%s.vcf.gz" % sshared.outname_from_inputs(bytype_vcfs)
combo_vcf = vcfutils.combine_variant_files(bytype_vcfs, out_file, ref_file,
config)
out = []
upload_counts = collections.defaultdict(int)
for data in items:
if "sv" not in data:
data["sv"] = []
base, ext = utils.splitext_plus(combo_vcf)
final_vcf = sshared.finalize_sv(combo_vcf, data, items)
if final_vcf:
delly_vcf = _delly_count_evidence_filter(final_vcf, data)
data["sv"].append({
"variantcaller": "delly",
"vrn_file": delly_vcf,
"do_upload": upload_counts[final_vcf] ==
0, # only upload a single file per batch
"exclude": exclude_file
})
upload_counts[final_vcf] += 1
out.append(data)
return out
def run(items):
"""Perform detection of structural variations with delly.
Performs post-call filtering with a custom filter tuned based
on NA12878 Moleculo and PacBio data, using calls prepared by
@ryanlayer and @cc2qe
Filters using the high quality variant pairs (DV) compared with
high quality reference pairs (DR).
"""
work_dir = utils.safe_makedir(os.path.join(items[0]["dirs"]["work"], "structural",
dd.get_sample_name(items[0]), "delly"))
# Add core request for delly
config = copy.deepcopy(items[0]["config"])
delly_config = utils.get_in(config, ("resources", "delly"), {})
delly_config["cores"] = 1
config["resources"]["delly"] = delly_config
parallel = {"type": "local", "cores": config["algorithm"].get("num_cores", 1),
"progs": ["delly"]}
work_bams = [dd.get_align_bam(d) for d in items]
ref_file = dd.get_ref_file(items[0])
exclude_file = _get_full_exclude_file(items, work_bams, work_dir)
bytype_vcfs = run_multicore(_run_delly,
[(work_bams, chrom, ref_file, work_dir, items)
for chrom in sshared.get_sv_chroms(items, exclude_file)],
config, parallel)
out_file = "%s.vcf.gz" % sshared.outname_from_inputs(bytype_vcfs)
combo_vcf = vcfutils.combine_variant_files(bytype_vcfs, out_file, ref_file, config)
out = []
upload_counts = collections.defaultdict(int)
for data in items:
if "sv" not in data:
data["sv"] = []
base, ext = utils.splitext_plus(combo_vcf)
final_vcf = sshared.finalize_sv(combo_vcf, data, items)
if final_vcf:
delly_vcf = _delly_count_evidence_filter(final_vcf, data)
data["sv"].append({"variantcaller": "delly", "vrn_file": delly_vcf,
"do_upload": upload_counts[final_vcf] == 0, # only upload a single file per batch
"exclude": exclude_file})
upload_counts[final_vcf] += 1
out.append(data)
return out
def run(items):
"""Perform detection of structural variations with delly.
Performs post-call filtering with a custom filter tuned based
on NA12878 Moleculo and PacBio data, using calls prepared by
@ryanlayer and @cc2qe
Filters using the high quality variant pairs (DV) compared with
high quality reference pairs (DR).
"""
work_dir = utils.safe_makedir(os.path.join(items[0]["dirs"]["work"], "structural",
items[0]["name"][-1], "delly"))
# Add core request for delly
config = copy.deepcopy(items[0]["config"])
delly_config = utils.get_in(config, ("resources", "delly"), {})
delly_config["cores"] = 1
config["resources"]["delly"] = delly_config
parallel = {"type": "local", "cores": config["algorithm"].get("num_cores", 1),
"progs": ["delly"]}
work_bams = [dd.get_align_bam(d) for d in items]
ref_file = dd.get_ref_file(items[0])
sv_types = ["DEL", "DUP"] # "TRA" has invalid VCF END specifications that GATK doesn't like, "INV" very slow
exclude_file = _get_full_exclude_file(items, work_dir)
bytype_vcfs = run_multicore(_run_delly,
[(work_bams, chrom, sv_type, ref_file, work_dir, items)
for (chrom, sv_type)
in itertools.product(sshared.get_sv_chroms(items, exclude_file), sv_types)],
config, parallel)
out_file = "%s.vcf.gz" % sshared.outname_from_inputs(bytype_vcfs)
combo_vcf = vcfutils.combine_variant_files(bytype_vcfs, out_file, ref_file, config)
out = []
for data in items:
if "sv" not in data:
data["sv"] = []
base, ext = utils.splitext_plus(combo_vcf)
final_vcf = sshared.finalize_sv(combo_vcf, data, items)
if final_vcf:
delly_vcf = _delly_count_evidence_filter(final_vcf, data)
data["sv"].append({"variantcaller": "delly", "vrn_file": delly_vcf,
"exclude": exclude_file})
out.append(data)
return out
def run(items):
"""Perform detection of structural variations with Manta.
"""
paired = vcfutils.get_paired(items)
data = paired.tumor_data if paired else items[0]
work_dir = _sv_workdir(data)
variant_file = _get_out_file(work_dir, paired)
if not utils.file_exists(variant_file):
with file_transaction(data, work_dir) as tx_work_dir:
utils.safe_makedir(tx_work_dir)
tx_workflow_file = _prep_config(items, paired, tx_work_dir)
_run_workflow(items, paired, tx_workflow_file, tx_work_dir)
assert utils.file_exists(variant_file), "Manta finished without output file %s" % variant_file
out = []
for data in items:
if "sv" not in data:
data["sv"] = []
final_vcf = shared.finalize_sv(variant_file, data, items)
data["sv"].append({"variantcaller": "manta", "vrn_file": final_vcf})
out.append(data)
return out
def run(items):
"""Perform detection of structural variations with Manta.
"""
paired = vcfutils.get_paired(items)
data = paired.tumor_data if paired else items[0]
work_dir = _sv_workdir(data)
variant_file = _get_out_file(work_dir, paired)
if not utils.file_exists(variant_file):
with file_transaction(data, work_dir) as tx_work_dir:
utils.safe_makedir(tx_work_dir)
tx_workflow_file = _prep_config(items, paired, tx_work_dir)
_run_workflow(items, paired, tx_workflow_file, tx_work_dir)
assert utils.file_exists(
variant_file), "Manta finished without output file %s" % variant_file
variant_file = shared.annotate_with_depth(variant_file, items)
out = []
upload_counts = collections.defaultdict(int)
for data in items:
if "break-point-inspector" in dd.get_tools_on(data):
if paired and paired.normal_bam and paired.tumor_name == dd.get_sample_name(
data):
variant_file = _run_break_point_inspector(
data, variant_file, paired, work_dir)
if "sv" not in data:
data["sv"] = []
final_vcf = shared.finalize_sv(variant_file, data, items)
vc = {
"variantcaller": "manta",
"do_upload": upload_counts[final_vcf] ==
0, # only upload a single file per batch
"vrn_file": final_vcf
}
evidence_bam = _get_evidence_bam(work_dir, data)
if evidence_bam:
vc["read_evidence"] = evidence_bam
data["sv"].append(vc)
upload_counts[final_vcf] += 1
out.append(data)
return out
def run(items, background=None):
"""Detect copy number variations from batched set of samples using WHAM.
"""
if not background: background = []
background_bams = []
paired = vcfutils.get_paired_bams([x["align_bam"] for x in items], items)
if paired:
inputs = [paired.tumor_data]
if paired.normal_bam:
background = [paired.normal_data]
background_bams = [paired.normal_bam]
else:
assert not background
inputs, background = shared.find_case_control(items)
background_bams = [x["align_bam"] for x in background]
orig_vcf = _run_wham(inputs, background_bams)
out = []
for data in inputs:
if "sv" not in data:
data["sv"] = []
final_vcf = shared.finalize_sv(orig_vcf, data, items)
data["sv"].append({"variantcaller": "wham", "vrn_file": final_vcf})
out.append(data)
return out
def run(items, background=None):
"""Detect copy number variations from batched set of samples using WHAM.
"""
if not background: background = []
background_bams = []
paired = vcfutils.get_paired_bams([x["align_bam"] for x in items], items)
if paired:
inputs = [paired.tumor_data]
if paired.normal_bam:
background = [paired.normal_data]
background_bams = [paired.normal_bam]
else:
assert not background
inputs, background = shared.find_case_control(items)
background_bams = [x["align_bam"] for x in background]
orig_vcf = _run_wham(inputs, background_bams)
out = []
for data in inputs:
if "sv" not in data:
data["sv"] = []
final_vcf = shared.finalize_sv(orig_vcf, data, items)
data["sv"].append({"variantcaller": "wham", "vrn_file": final_vcf})
out.append(data)
return out
