def use_general_sv_bins(data):
"""Check if we should use a general binning approach for a sample.
Checks if CNVkit is enabled and we haven't already run CNVkit.
"""
if "cnvkit" in dd.get_svcaller(data) or "titancna" in dd.get_svcaller(
data):
if not _get_original_coverage(data):
return True
return False
def calculate_sv_coverage(data):
"""Calculate coverage within bins for downstream CNV calling.
Creates corrected cnr files with log2 ratios and depths.
"""
calcfns = {
"cnvkit": _calculate_sv_coverage_cnvkit,
"gatk-cnv": _calculate_sv_coverage_gatk
}
from bcbio.structural import cnvkit
data = utils.to_single_data(data)
if not cnvkit.use_general_sv_bins(data):
out_target_file, out_anti_file = (None, None)
else:
work_dir = utils.safe_makedir(
os.path.join(dd.get_work_dir(data), "structural",
dd.get_sample_name(data), "bins"))
out_target_file, out_anti_file = calcfns[cnvkit.bin_approach(data)](
data, work_dir)
if not os.path.exists(out_target_file):
out_target_file, out_anti_file = (None, None)
if "seq2c" in dd.get_svcaller(data):
from bcbio.structural import seq2c
seq2c_target = seq2c.precall(data)
else:
seq2c_target = None
if not tz.get_in(["depth", "bins"], data):
data = tz.update_in(data, ["depth", "bins"], lambda x: {})
data["depth"]["bins"] = {
"target": out_target_file,
"antitarget": out_anti_file,
"seq2c": seq2c_target
}
return [[data]]
def calculate_sv_coverage(data):
"""Calculate coverage within bins for downstream CNV calling.
Creates corrected cnr files with log2 ratios and depths.
"""
calcfns = {"cnvkit": _calculate_sv_coverage_cnvkit, "gatk-cnv": _calculate_sv_coverage_gatk}
from bcbio.structural import cnvkit
data = utils.to_single_data(data)
if not cnvkit.use_general_sv_bins(data):
out_target_file, out_anti_file = (None, None)
else:
work_dir = utils.safe_makedir(os.path.join(dd.get_work_dir(data), "structural",
dd.get_sample_name(data), "bins"))
out_target_file, out_anti_file = calcfns[cnvkit.bin_approach(data)](data, work_dir)
if not os.path.exists(out_target_file):
out_target_file, out_anti_file = (None, None)
if "seq2c" in dd.get_svcaller(data):
from bcbio.structural import seq2c
seq2c_target = seq2c.precall(data)
else:
seq2c_target = None
if not tz.get_in(["depth", "bins"], data):
data = tz.update_in(data, ["depth", "bins"], lambda x: {})
data["depth"]["bins"] = {"target": out_target_file, "antitarget": out_anti_file, "seq2c": seq2c_target}
return [[data]]
def calculate_sv_coverage(data):
"""Calculate coverage within bins for downstream CNV calling.
Creates corrected cnr files with log2 ratios and depths.
data is one sample
"""
calcfns = {"cnvkit": _calculate_sv_coverage_cnvkit, "gatk-cnv": _calculate_sv_coverage_gatk}
from bcbio.structural import cnvkit
data = utils.to_single_data(data)
from bcbio.structural import get_svcallers
sv_callers = get_svcallers(data)
has_cnvkit_or_gatkcnv = bool(set(["cnvkit", "gatk-cnv"]) & set(sv_callers))
if not cnvkit.use_general_sv_bins(data) or not has_cnvkit_or_gatkcnv:
out_target_file, out_anti_file = (None, None)
else:
work_dir = utils.safe_makedir(os.path.join(dd.get_work_dir(data), "structural",
dd.get_sample_name(data), "bins"))
out_target_file, out_anti_file = calcfns[cnvkit.bin_approach(data)](data, work_dir)
if not os.path.exists(out_target_file):
out_target_file, out_anti_file = (None, None)
if "seq2c" in dd.get_svcaller(data):
from bcbio.structural import seq2c
seq2c_target = seq2c.precall(data)
else:
seq2c_target = None
if "purecn" in dd.get_svcaller(data):
# set purecn_pon_build flag
batches = dd.get_batch(data)
if batches and "pon_build" in dd.get_batch(data):
data["config"]["algorithm"]["purecn_pon_build"] = True
from bcbio.structural import purecn
# still calculate coverage even when not building pon - for t-only analysis
purecn_target = purecn.get_coverage(data)
else:
purecn_target = None
if not tz.get_in(["depth", "bins"], data):
data = tz.update_in(data, ["depth", "bins"], lambda x: {})
data["depth"]["bins"] = {"target": out_target_file,
"antitarget": out_anti_file,
"seq2c": seq2c_target,
"purecn": purecn_target}
return [[data]]
def _variant_checkpoints(samples):
"""Check sample configuration to identify required steps in analysis.
"""
checkpoints = {}
checkpoints["vc"] = any([dd.get_variantcaller(d) for d in samples])
checkpoints["sv"] = any([dd.get_svcaller(d) for d in samples])
checkpoints["jointvc"] = any([dd.get_jointcaller(d) or ("gvcf" in dd.get_tools_on(d)) for d in samples])
checkpoints["hla"] = any([dd.get_hlacaller(d) for d in samples])
return checkpoints
def use_general_sv_bins(data):
"""Check if we should use a general binning approach for a sample.
Checks if CNVkit is enabled and we haven't already run CNVkit.
"""
if any([c in dd.get_svcaller(data) for c in ["cnvkit", "titancna", "purecn", "gatk-cnv"]]):
if not _get_original_coverage(data):
return True
return False
def _variant_checkpoints(samples):
"""Check sample configuration to identify required steps in analysis.
"""
checkpoints = {}
checkpoints["vc"] = any([dd.get_variantcaller(d) for d in samples])
checkpoints["sv"] = any([dd.get_svcaller(d) for d in samples])
checkpoints["jointvc"] = any([dd.get_jointcaller(d) or ("gvcf" in dd.get_tools_on(d)) for d in samples])
checkpoints["hla"] = any([dd.get_hlacaller(d) for d in samples])
return checkpoints
def bin_approach(data):
"""Check for binning approach from configuration or normalized file.
"""
for approach in ["cnvkit", "gatk-cnv"]:
if approach in dd.get_svcaller(data):
return approach
norm_file = tz.get_in(["depth", "bins", "normalized"], data)
if norm_file.endswith(("-crstandardized.tsv", "-crdenoised.tsv")):
return "gatk-cnv"
if norm_file.endswith(".cnr"):
return "cnvkit"
def bin_approach(data):
"""Check for binning approach from configuration or normalized file.
"""
for approach in ["cnvkit", "gatk-cnv"]:
if approach in dd.get_svcaller(data):
return approach
norm_file = tz.get_in(["depth", "bins", "normalized"], data)
if norm_file.endswith(("-crstandardized.tsv", "-crdenoised.tsv")):
return "gatk-cnv"
if norm_file.endswith(".cnr"):
return "cnvkit"
def _variant_checkpoints(samples):
"""Check sample configuration to identify required steps in analysis.
"""
checkpoints = {}
checkpoints["vc"] = any([dd.get_variantcaller(d) for d in samples])
checkpoints["sv"] = any([dd.get_svcaller(d) for d in samples])
checkpoints["jointvc"] = any([(dd.get_jointcaller(d) or ("gvcf" in dd.get_tools_on(d))) and dd.get_batch(d)
for d in samples])
checkpoints["hla"] = any([dd.get_hlacaller(d) for d in samples])
checkpoints["align"] = any([(dd.get_aligner(d) or dd.get_bam_clean(d)) for d in samples])
checkpoints["align_split"] = not all([(dd.get_align_split_size(d) is False or
not dd.get_aligner(d))
for d in samples])
return checkpoints
def detect_sv(items, all_items=None, stage="standard"):
"""Top level parallel target for examining structural variation.
items = sample-sv_caller list, from one batch
"""
items = [utils.to_single_data(x) for x in items]
items = cwlutils.unpack_tarballs(items, items[0])
svcaller = items[0]["config"]["algorithm"].get("svcaller")
caller_fn = _get_callers(items, stage, special_cases=True).get(svcaller)
out = []
batch = dd.get_batch(items[0])
# no SV calling when just creating a PON for PureCN
if batch == "pon_build" and "purecn" in dd.get_svcaller(items[0]):
return out
if svcaller and caller_fn:
if (all_items and svcaller in _NEEDS_BACKGROUND
and not vcfutils.is_paired_analysis(
[x.get("align_bam") for x in items], items)):
names = set([dd.get_sample_name(x) for x in items])
background = [
x for x in all_items if dd.get_sample_name(x) not in names
]
for svdata in caller_fn(items, background):
out.append([svdata])
else:
for svdata in caller_fn(items):
out.append([svdata])
else:
for data in items:
out.append([data])
# Avoid nesting of callers for CWL runs for easier extraction
if cwlutils.is_cwl_run(items[0]):
out_cwl = []
for data in [utils.to_single_data(x) for x in out]:
# Run validation directly from CWL runs since we're single stage
data = validate.evaluate(data)
data["svvalidate"] = {
"summary": tz.get_in(["sv-validate", "csv"], data)
}
svs = data.get("sv")
if svs:
assert len(svs) == 1, svs
data["sv"] = svs[0]
else:
data["sv"] = {}
data = _add_supplemental(data)
out_cwl.append([data])
return out_cwl
return out
def _variant_checkpoints(samples):
"""Check sample configuration to identify required steps in analysis.
"""
checkpoints = {}
checkpoints["vc"] = any([dd.get_variantcaller(d) or d.get("vrn_file") for d in samples])
checkpoints["sv"] = any([dd.get_svcaller(d) for d in samples])
checkpoints["jointvc"] = any([(dd.get_jointcaller(d) or "gvcf" in dd.get_tools_on(d))
for d in samples])
checkpoints["hla"] = any([dd.get_hlacaller(d) for d in samples])
checkpoints["align"] = any([(dd.get_aligner(d) or dd.get_bam_clean(d)) for d in samples])
checkpoints["align_split"] = not all([(dd.get_align_split_size(d) is False or
not dd.get_aligner(d))
for d in samples])
checkpoints["umi"] = any([dd.get_umi_consensus(d) for d in samples])
checkpoints["ensemble"] = any([dd.get_ensemble(d) for d in samples])
checkpoints["cancer"] = any(dd.get_phenotype(d) in ["tumor"] for d in samples)
return checkpoints
def _variant_checkpoints(samples):
"""Check sample configuration to identify required steps in analysis.
"""
checkpoints = {}
checkpoints["vc"] = any([dd.get_variantcaller(d) or d.get("vrn_file") for d in samples])
checkpoints["sv"] = any([dd.get_svcaller(d) for d in samples])
checkpoints["jointvc"] = any([(dd.get_jointcaller(d) or "gvcf" in dd.get_tools_on(d))
for d in samples])
checkpoints["hla"] = any([dd.get_hlacaller(d) for d in samples])
checkpoints["align"] = any([(dd.get_aligner(d) or dd.get_bam_clean(d)) for d in samples])
checkpoints["align_split"] = not all([(dd.get_align_split_size(d) is False or
not dd.get_aligner(d))
for d in samples])
checkpoints["archive"] = any([dd.get_archive(d) for d in samples])
checkpoints["umi"] = any([dd.get_umi_consensus(d) for d in samples])
checkpoints["ensemble"] = any([dd.get_ensemble(d) for d in samples])
checkpoints["cancer"] = any(dd.get_phenotype(d) in ["tumor"] for d in samples)
return checkpoints
def mutect2_caller(align_bams, items, ref_file, assoc_files,
region=None, out_file=None):
"""Call variation with GATK's MuTect2.
This requires the full non open-source version of GATK 3.5+.
items = 1 sample or T/N pair
"""
if out_file is None:
out_file = "%s-variants.vcf.gz" % utils.splitext_plus(align_bams[0])[0]
if not utils.file_exists(out_file):
# call somatic variants keeping germline sites and using germline 1KG resource
# use --native-pair-hmm-threads?
broad_runner = broad.runner_from_config(items[0]["config"])
gatk_type = broad_runner.gatk_type()
# shared Mutect2 settings for PureCN analysis in the case of:
# - PON creation
# - Tumor-only PureCN run
# - T/N PureCN run
# PURECN requirement alters Mutect2 variants calling!
if "purecn" in dd.get_svcaller(items[0]):
# mutect call for PON creation or purecn T-only analysis
_prep_inputs(align_bams, ref_file, items)
with file_transaction(items[0], out_file) as tx_out_file:
germline_resource = tz.get_in(["genome_resources", "variation", "af_only_gnomad"], items[0])
germline_path = os.path.normpath(os.path.join(os.path.dirname(ref_file), germline_resource))
input_bam = dd.get_work_bam(items[0])
tx_prefilt_vcf = utils.splitext_plus(tx_out_file)[0] + ".prefilt.vcf"
tx_vcf = os.path.splitext(tx_out_file)[0]
out_file_ungz = os.path.splitext(out_file)[0]
params = ["-T", "Mutect2"]
# T/N pair
if len(items) == 2:
paired = vcfutils.get_paired_bams(align_bams, items)
# not really running purecn with mutect1/gatk3
params += _add_tumor_params(paired, items, gatk_type)
logger.debug("You are running mutect2 in PureCN analysis in T/N mode, T-only + PON is recommended")
else: #T only
params += ["-I", input_bam]
# adding SNV PON from background/variant
snv_pon = tz.get_in(["config", "algorithm", "background", "variant"], items[0])
if snv_pon and dd.get_batch(items[0]) != "pon_build":
params += ["-pon", snv_pon]
params += ["--genotype-pon-sites"]
opt_list = config_utils.get_resources("mutect2", items[0]["config"]).get("options")
# default is 50, sometimes 100 or 200 is recommended for better sensitivity in detection
# hom del CNVs (calling more variants helps)
interval_padding = 50
if opt_list:
opt_dict = dict(zip(opt_list[::2], opt_list[1::2]))
if "--interval_padding" in opt_dict:
interval_padding = opt_dict["--interval_padding"]
params += ["--max-mnp-distance", "0",
"--interval-padding", interval_padding,
"--germline-resource", germline_path,
"--genotype-germline-sites",
"--reference", ref_file,
"-O", tx_prefilt_vcf]
params += _add_region_params(region, out_file, items, gatk_type)
broad_runner.new_resources("mutect2")
gatk_cmd = broad_runner.cl_gatk(params, os.path.dirname(tx_out_file))
filter_cmd = _mutect2_filter(broad_runner, items, tx_prefilt_vcf, out_file_ungz, ref_file)
cmd = "{gatk_cmd} && {filter_cmd}"
do.run(cmd.format(**locals()), "MuTect2")
# no AF filter for PureCN variants
out_file = vcfutils.bgzip_and_index(out_file_ungz, items[0]["config"])
else:
# a regular mutect call
paired = vcfutils.get_paired_bams(align_bams, items)
f1r2_file = None
_prep_inputs(align_bams, ref_file, items)
with file_transaction(items[0], out_file) as tx_out_file:
params = ["-T", "Mutect2" if gatk_type == "gatk4" else "MuTect2",
"--annotation", "ClippingRankSumTest",
"--annotation", "DepthPerSampleHC"]
if gatk_type == "gatk4":
params += ["--reference", ref_file]
else:
params += ["-R", ref_file]
for a in annotation.get_gatk_annotations(items[0]["config"], include_baseqranksum=False):
params += ["--annotation", a]
# Avoid issues with BAM CIGAR reads that GATK doesn't like
if gatk_type == "gatk4":
params += ["--read-validation-stringency", "LENIENT"]
params += _add_tumor_params(paired, items, gatk_type)
params += _add_region_params(region, out_file, items, gatk_type)
if all(is_paired(bam) for bam in align_bams) and (
"mutect2_readmodel" in utils.get_in(items[0], "config", "tools_on")):
orientation_filter = True
else:
orientation_filter = False
if gatk_type == "gatk4" and orientation_filter:
f1r2_file = "{}-f1r2.tar.gz".format(utils.splitext_plus(out_file)[0])
params += ["--f1r2-tar-gz", f1r2_file]
# Avoid adding dbSNP/Cosmic so they do not get fed to variant filtering algorithm
# Not yet clear how this helps or hurts in a general case.
#params += _add_assoc_params(assoc_files)
resources = config_utils.get_resources("mutect2", items[0]["config"])
if "options" in resources:
params += [str(x) for x in resources.get("options", [])]
assert LooseVersion(broad_runner.gatk_major_version()) >= LooseVersion("3.5"), \
"Require full version of GATK 3.5+ for mutect2 calling"
broad_runner.new_resources("mutect2")
gatk_cmd = broad_runner.cl_gatk(params, os.path.dirname(tx_out_file))
if gatk_type == "gatk4":
tx_raw_prefilt_file = "%s-raw%s" % utils.splitext_plus(out_file)
tx_raw_file = "%s-raw-filt%s" % utils.splitext_plus(tx_out_file)
if orientation_filter:
tx_f1r2_file = "{}-read-orientation-model.tar.gz"
tx_f1r2_file = tx_f1r2_file.format(utils.splitext_plus(f1r2_file)[0])
tx_read_orient_cmd = _mutect2_read_filter(broad_runner,
f1r2_file,
tx_f1r2_file)
filter_cmd = _mutect2_filter(broad_runner, items,
tx_raw_prefilt_file,
tx_raw_file, ref_file,
tx_f1r2_file)
else:
filter_cmd = _mutect2_filter(broad_runner, items,
tx_raw_prefilt_file,
tx_raw_file, ref_file)
if orientation_filter:
cmd = "{gatk_cmd} -O {tx_raw_prefilt_file} && {tx_read_orient_cmd} && {filter_cmd}"
else:
cmd = "{gatk_cmd} -O {tx_raw_prefilt_file} && {filter_cmd}"
else:
tx_raw_file = "%s-raw%s" % utils.splitext_plus(tx_out_file)
cmd = "{gatk_cmd} > {tx_raw_file}"
do.run(cmd.format(**locals()), "MuTect2")
out_file = _af_filter(paired.tumor_data, tx_raw_file, out_file)
return vcfutils.bgzip_and_index(out_file, items[0]["config"])
