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bcbio/bcbio-nextgen | bcbio/variation/validateplot.py | classifyplot_from_valfile | def classifyplot_from_valfile(val_file, outtype="png", title=None, size=None,
samples=None, callers=None):
"""Create a plot from a summarized validation file.
Does new-style plotting of summarized metrics of
false negative rate and false discovery rate.
https://en.wikipedi... | python | def classifyplot_from_valfile(val_file, outtype="png", title=None, size=None,
samples=None, callers=None):
"""Create a plot from a summarized validation file.
Does new-style plotting of summarized metrics of
false negative rate and false discovery rate.
https://en.wikipedi... | [
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bcbio/bcbio-nextgen | bcbio/variation/validateplot.py | create | def create(plot_data, header, ploti, sample_config, out_file_base, outtype="png",
title=None, size=None):
"""Create plots of validation results for a sample, labeling prep strategies.
"""
if mpl is None or plt is None or sns is None:
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"""Create plots of validation results for a sample, labeling prep strategies.
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bcbio/bcbio-nextgen | bcbio/variation/validateplot.py | plot_prep_methods | def plot_prep_methods(df, prep, prepi, out_file_base, outtype, title=None,
size=None):
"""Plot comparison between BAM preparation methods.
"""
samples = df[(df["bamprep"] == prep)]["sample"].unique()
assert len(samples) >= 1, samples
out_file = "%s-%s.%s" % (out_file_base, samp... | python | def plot_prep_methods(df, prep, prepi, out_file_base, outtype, title=None,
size=None):
"""Plot comparison between BAM preparation methods.
"""
samples = df[(df["bamprep"] == prep)]["sample"].unique()
assert len(samples) >= 1, samples
out_file = "%s-%s.%s" % (out_file_base, samp... | [
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bcbio/bcbio-nextgen | bcbio/variation/validateplot.py | _seaborn | def _seaborn(df, prep, prepi, out_file, title=None, size=None):
"""Plot using seaborn wrapper around matplotlib.
"""
plt.ioff()
sns.set(style='dark')
vtypes = df["variant.type"].unique()
callers = sorted(df["caller"].unique())
cats = _check_cats(["concordant", "discordant-missing-total",
... | python | def _seaborn(df, prep, prepi, out_file, title=None, size=None):
"""Plot using seaborn wrapper around matplotlib.
"""
plt.ioff()
sns.set(style='dark')
vtypes = df["variant.type"].unique()
callers = sorted(df["caller"].unique())
cats = _check_cats(["concordant", "discordant-missing-total",
... | [
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bcbio/bcbio-nextgen | bcbio/variation/validateplot.py | _check_cats | def _check_cats(cats, vtypes, df, prep, callers):
"""Only include categories in the final output if they have values.
"""
out = []
for cat in cats:
all_vals = []
for vtype in vtypes:
vals, labels, maxval = _get_chart_info(df, vtype, cat, prep, callers)
all_vals.ex... | python | def _check_cats(cats, vtypes, df, prep, callers):
"""Only include categories in the final output if they have values.
"""
out = []
for cat in cats:
all_vals = []
for vtype in vtypes:
vals, labels, maxval = _get_chart_info(df, vtype, cat, prep, callers)
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bcbio/bcbio-nextgen | bcbio/variation/validateplot.py | _get_chart_info | def _get_chart_info(df, vtype, cat, prep, callers):
"""Retrieve values for a specific variant type, category and prep method.
"""
maxval_raw = max(list(df["value.floor"]))
curdf = df[(df["variant.type"] == vtype) & (df["category"] == cat)
& (df["bamprep"] == prep)]
vals = []
label... | python | def _get_chart_info(df, vtype, cat, prep, callers):
"""Retrieve values for a specific variant type, category and prep method.
"""
maxval_raw = max(list(df["value.floor"]))
curdf = df[(df["variant.type"] == vtype) & (df["category"] == cat)
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vals = []
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bcbio/bcbio-nextgen | bcbio/variation/validateplot.py | _annotate | def _annotate(ax, annotate, height, left, width):
"""Annotate axis with labels.
"""
annotate_yrange_factor = 0.010
xticks = np.array(left) + width / 2.0
ymin, ymax = ax.get_ylim()
yrange = ymax - ymin
# Reset ymax and ymin so there's enough room to see the annotation of
# the top-most
... | python | def _annotate(ax, annotate, height, left, width):
"""Annotate axis with labels.
"""
annotate_yrange_factor = 0.010
xticks = np.array(left) + width / 2.0
ymin, ymax = ax.get_ylim()
yrange = ymax - ymin
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bcbio/bcbio-nextgen | bcbio/variation/validateplot.py | _ggplot | def _ggplot(df, out_file):
"""Plot faceted items with ggplot wrapper on top of matplotlib.
XXX Not yet functional
"""
import ggplot as gg
df["variant.type"] = [vtype_labels[x] for x in df["variant.type"]]
df["category"] = [cat_labels[x] for x in df["category"]]
df["caller"] = [caller_labels.... | python | def _ggplot(df, out_file):
"""Plot faceted items with ggplot wrapper on top of matplotlib.
XXX Not yet functional
"""
import ggplot as gg
df["variant.type"] = [vtype_labels[x] for x in df["variant.type"]]
df["category"] = [cat_labels[x] for x in df["category"]]
df["caller"] = [caller_labels.... | [
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bcbio/bcbio-nextgen | bcbio/variation/validateplot.py | get_floor_value | def get_floor_value(x, cat, vartype, floors):
"""Modify values so all have the same relative scale for differences.
Using the chosen base heights, adjusts an individual sub-plot to be consistent
relative to that height.
"""
all_base = floors[vartype]
cur_max = floors[(cat, vartype)]
if cur_... | python | def get_floor_value(x, cat, vartype, floors):
"""Modify values so all have the same relative scale for differences.
Using the chosen base heights, adjusts an individual sub-plot to be consistent
relative to that height.
"""
all_base = floors[vartype]
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bcbio/bcbio-nextgen | bcbio/variation/validateplot.py | get_group_floors | def get_group_floors(df, cat_labels):
"""Retrieve the floor for a given row of comparisons, creating a normalized set of differences.
We need to set non-zero floors so large numbers (like concordance) don't drown out small
numbers (like discordance). This defines the height for a row of comparisons as eith... | python | def get_group_floors(df, cat_labels):
"""Retrieve the floor for a given row of comparisons, creating a normalized set of differences.
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bcbio/bcbio-nextgen | scripts/bcbio_nextgen.py | _sanity_check_args | def _sanity_check_args(args):
"""Ensure dependent arguments are correctly specified
"""
if "scheduler" in args and "queue" in args:
if args.scheduler and not args.queue:
if args.scheduler != "sge":
return "IPython parallel scheduler (-s) specified. This also requires a qu... | python | def _sanity_check_args(args):
"""Ensure dependent arguments are correctly specified
"""
if "scheduler" in args and "queue" in args:
if args.scheduler and not args.queue:
if args.scheduler != "sge":
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bcbio/bcbio-nextgen | scripts/bcbio_nextgen.py | _add_inputs_to_kwargs | def _add_inputs_to_kwargs(args, kwargs, parser):
"""Convert input system config, flow cell directory and sample yaml to kwargs.
Handles back compatibility with previous commandlines while allowing flexible
specification of input parameters.
"""
inputs = [x for x in [args.global_config, args.fc_dir]... | python | def _add_inputs_to_kwargs(args, kwargs, parser):
"""Convert input system config, flow cell directory and sample yaml to kwargs.
Handles back compatibility with previous commandlines while allowing flexible
specification of input parameters.
"""
inputs = [x for x in [args.global_config, args.fc_dir]... | [
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bcbio/bcbio-nextgen | bcbio/broad/metrics.py | _add_commas | def _add_commas(s, sep=','):
"""Add commas to output counts.
From: http://code.activestate.com/recipes/498181
"""
if len(s) <= 3:
return s
return _add_commas(s[:-3], sep) + sep + s[-3:] | python | def _add_commas(s, sep=','):
"""Add commas to output counts.
From: http://code.activestate.com/recipes/498181
"""
if len(s) <= 3:
return s
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bcbio/bcbio-nextgen | bcbio/broad/metrics.py | bed_to_interval | def bed_to_interval(orig_bed, bam_file):
"""Add header and format BED bait and target files for Picard if necessary.
"""
with open(orig_bed) as in_handle:
line = in_handle.readline()
if line.startswith("@"):
yield orig_bed
else:
with pysam.Samfile(bam_file, "rb") as bam_handl... | python | def bed_to_interval(orig_bed, bam_file):
"""Add header and format BED bait and target files for Picard if necessary.
"""
with open(orig_bed) as in_handle:
line = in_handle.readline()
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bcbio/bcbio-nextgen | bcbio/broad/metrics.py | PicardMetricsParser.get_summary_metrics | def get_summary_metrics(self, align_metrics, dup_metrics,
insert_metrics=None, hybrid_metrics=None, vrn_vals=None,
rnaseq_metrics=None):
"""Retrieve a high level summary of interesting metrics.
"""
with open(align_metrics) as in_handle:
align_vals = self._pars... | python | def get_summary_metrics(self, align_metrics, dup_metrics,
insert_metrics=None, hybrid_metrics=None, vrn_vals=None,
rnaseq_metrics=None):
"""Retrieve a high level summary of interesting metrics.
"""
with open(align_metrics) as in_handle:
align_vals = self._pars... | [
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bcbio/bcbio-nextgen | bcbio/broad/metrics.py | PicardMetricsParser.extract_metrics | def extract_metrics(self, metrics_files):
"""Return summary information for a lane of metrics files.
"""
extension_maps = dict(
align_metrics=(self._parse_align_metrics, "AL"),
dup_metrics=(self._parse_dup_metrics, "DUP"),
hs_metrics=(self._parse_hybrid_metric... | python | def extract_metrics(self, metrics_files):
"""Return summary information for a lane of metrics files.
"""
extension_maps = dict(
align_metrics=(self._parse_align_metrics, "AL"),
dup_metrics=(self._parse_dup_metrics, "DUP"),
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bcbio/bcbio-nextgen | bcbio/broad/metrics.py | PicardMetrics.report | def report(self, align_bam, ref_file, is_paired, bait_file, target_file,
variant_region_file, config):
"""Produce report metrics using Picard with sorted aligned BAM file.
"""
dup_metrics = self._get_current_dup_metrics(align_bam)
align_metrics = self._collect_align_metric... | python | def report(self, align_bam, ref_file, is_paired, bait_file, target_file,
variant_region_file, config):
"""Produce report metrics using Picard with sorted aligned BAM file.
"""
dup_metrics = self._get_current_dup_metrics(align_bam)
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bcbio/bcbio-nextgen | bcbio/broad/metrics.py | PicardMetrics._get_current_dup_metrics | def _get_current_dup_metrics(self, align_bam):
"""Retrieve duplicate information from input BAM file.
"""
metrics_file = "%s.dup_metrics" % os.path.splitext(align_bam)[0]
if not file_exists(metrics_file):
dups = 0
with pysam.Samfile(align_bam, "rb") as bam_handle:... | python | def _get_current_dup_metrics(self, align_bam):
"""Retrieve duplicate information from input BAM file.
"""
metrics_file = "%s.dup_metrics" % os.path.splitext(align_bam)[0]
if not file_exists(metrics_file):
dups = 0
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bcbio/bcbio-nextgen | bcbio/broad/metrics.py | PicardMetrics._check_metrics_file | def _check_metrics_file(self, bam_name, metrics_ext):
"""Check for an existing metrics file for the given BAM.
"""
base, _ = os.path.splitext(bam_name)
try:
int(base[-1])
can_glob = False
except ValueError:
can_glob = True
check_fname =... | python | def _check_metrics_file(self, bam_name, metrics_ext):
"""Check for an existing metrics file for the given BAM.
"""
base, _ = os.path.splitext(bam_name)
try:
int(base[-1])
can_glob = False
except ValueError:
can_glob = True
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bcbio/bcbio-nextgen | bcbio/broad/metrics.py | PicardMetrics._hybrid_select_metrics | def _hybrid_select_metrics(self, dup_bam, bait_file, target_file):
"""Generate metrics for hybrid selection efficiency.
"""
metrics = self._check_metrics_file(dup_bam, "hs_metrics")
if not file_exists(metrics):
with bed_to_interval(bait_file, dup_bam) as ready_bait:
... | python | def _hybrid_select_metrics(self, dup_bam, bait_file, target_file):
"""Generate metrics for hybrid selection efficiency.
"""
metrics = self._check_metrics_file(dup_bam, "hs_metrics")
if not file_exists(metrics):
with bed_to_interval(bait_file, dup_bam) as ready_bait:
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bcbio/bcbio-nextgen | bcbio/broad/metrics.py | PicardMetrics._variant_eval_metrics | def _variant_eval_metrics(self, dup_bam):
"""Find metrics for evaluating variant effectiveness.
"""
base, ext = os.path.splitext(dup_bam)
end_strip = "-dup"
base = base[:-len(end_strip)] if base.endswith(end_strip) else base
mfiles = glob.glob("%s*eval_metrics" % base)
... | python | def _variant_eval_metrics(self, dup_bam):
"""Find metrics for evaluating variant effectiveness.
"""
base, ext = os.path.splitext(dup_bam)
end_strip = "-dup"
base = base[:-len(end_strip)] if base.endswith(end_strip) else base
mfiles = glob.glob("%s*eval_metrics" % base)
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bcbio/bcbio-nextgen | bcbio/broad/metrics.py | RNASeqPicardMetrics.report | def report(self, align_bam, ref_file, gtf_file, is_paired=False, rrna_file="null"):
"""Produce report metrics for a RNASeq experiment using Picard
with a sorted aligned BAM file.
"""
# collect duplication metrics
dup_metrics = self._get_current_dup_metrics(align_bam)
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"""Produce report metrics for a RNASeq experiment using Picard
with a sorted aligned BAM file.
"""
# collect duplication metrics
dup_metrics = self._get_current_dup_metrics(align_bam)
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bcbio/bcbio-nextgen | bcbio/variation/gatk.py | standard_cl_params | def standard_cl_params(items):
"""Shared command line parameters for GATK programs.
Handles no removal of duplicate reads for amplicon or
non mark duplicate experiments. If we have pre-aligned inputs we
ignore the value or mark duplicates (since they may already be
marked in the input BAM).
"""... | python | def standard_cl_params(items):
"""Shared command line parameters for GATK programs.
Handles no removal of duplicate reads for amplicon or
non mark duplicate experiments. If we have pre-aligned inputs we
ignore the value or mark duplicates (since they may already be
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bcbio/bcbio-nextgen | bcbio/variation/gatk.py | _shared_gatk_call_prep | def _shared_gatk_call_prep(align_bams, items, ref_file, region, out_file, num_cores=1):
"""Shared preparation work for GATK variant calling.
"""
data = items[0]
config = data["config"]
broad_runner = broad.runner_from_config(config)
gatk_type = broad_runner.gatk_type()
for x in align_bams:
... | python | def _shared_gatk_call_prep(align_bams, items, ref_file, region, out_file, num_cores=1):
"""Shared preparation work for GATK variant calling.
"""
data = items[0]
config = data["config"]
broad_runner = broad.runner_from_config(config)
gatk_type = broad_runner.gatk_type()
for x in align_bams:
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bcbio/bcbio-nextgen | bcbio/variation/gatk.py | unified_genotyper | def unified_genotyper(align_bams, items, ref_file, assoc_files,
region=None, out_file=None):
"""Perform SNP genotyping on the given alignment file.
"""
if out_file is None:
out_file = "%s-variants.vcf.gz" % utils.splitext_plus(align_bams[0])[0]
if not utils.file_exists(out... | python | def unified_genotyper(align_bams, items, ref_file, assoc_files,
region=None, out_file=None):
"""Perform SNP genotyping on the given alignment file.
"""
if out_file is None:
out_file = "%s-variants.vcf.gz" % utils.splitext_plus(align_bams[0])[0]
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bcbio/bcbio-nextgen | bcbio/variation/gatk.py | _joint_calling | def _joint_calling(items):
"""Determine if this call feeds downstream into joint calls.
"""
jointcaller = tz.get_in(("config", "algorithm", "jointcaller"), items[0])
if jointcaller:
assert len(items) == 1, "Can only do joint calling preparation with GATK with single samples"
assert tz.ge... | python | def _joint_calling(items):
"""Determine if this call feeds downstream into joint calls.
"""
jointcaller = tz.get_in(("config", "algorithm", "jointcaller"), items[0])
if jointcaller:
assert len(items) == 1, "Can only do joint calling preparation with GATK with single samples"
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bcbio/bcbio-nextgen | bcbio/variation/gatk.py | _supports_avx | def _supports_avx():
"""Check for support for Intel AVX acceleration."""
if os.path.exists("/proc/cpuinfo"):
with open("/proc/cpuinfo") as in_handle:
for line in in_handle:
if line.startswith("flags") and line.find("avx") > 0:
return True | python | def _supports_avx():
"""Check for support for Intel AVX acceleration."""
if os.path.exists("/proc/cpuinfo"):
with open("/proc/cpuinfo") as in_handle:
for line in in_handle:
if line.startswith("flags") and line.find("avx") > 0:
return True | [
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bcbio/bcbio-nextgen | bcbio/provenance/programs.py | jar_versioner | def jar_versioner(program_name, jar_name):
"""Retrieve version information based on jar file.
"""
def get_version(config):
try:
pdir = config_utils.get_program(program_name, config, "dir")
# not configured
except ValueError:
return ""
jar = os.path.bas... | python | def jar_versioner(program_name, jar_name):
"""Retrieve version information based on jar file.
"""
def get_version(config):
try:
pdir = config_utils.get_program(program_name, config, "dir")
# not configured
except ValueError:
return ""
jar = os.path.bas... | [
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bcbio/bcbio-nextgen | bcbio/provenance/programs.py | _get_cl_version | def _get_cl_version(p, config):
"""Retrieve version of a single commandline program.
"""
if not p.get("has_cl_version", True):
return ""
try:
prog = config_utils.get_program(p["cmd"], config)
except config_utils.CmdNotFound:
localpy_cmd = os.path.join(os.path.dirname(sys.exe... | python | def _get_cl_version(p, config):
"""Retrieve version of a single commandline program.
"""
if not p.get("has_cl_version", True):
return ""
try:
prog = config_utils.get_program(p["cmd"], config)
except config_utils.CmdNotFound:
localpy_cmd = os.path.join(os.path.dirname(sys.exe... | [
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bcbio/bcbio-nextgen | bcbio/provenance/programs.py | _get_brew_versions | def _get_brew_versions():
"""Retrieve versions of tools installed via brew.
"""
from bcbio import install
tooldir = install.get_defaults().get("tooldir")
brew_cmd = os.path.join(tooldir, "bin", "brew") if tooldir else "brew"
try:
vout = subprocess.check_output([brew_cmd, "list", "--versi... | python | def _get_brew_versions():
"""Retrieve versions of tools installed via brew.
"""
from bcbio import install
tooldir = install.get_defaults().get("tooldir")
brew_cmd = os.path.join(tooldir, "bin", "brew") if tooldir else "brew"
try:
vout = subprocess.check_output([brew_cmd, "list", "--versi... | [
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bcbio/bcbio-nextgen | bcbio/provenance/programs.py | _get_versions | def _get_versions(config=None):
"""Retrieve details on all programs available on the system.
"""
try:
from bcbio.pipeline import version
if hasattr(version, "__version__"):
bcbio_version = ("%s-%s" % (version.__version__, version.__git_revision__)
if ... | python | def _get_versions(config=None):
"""Retrieve details on all programs available on the system.
"""
try:
from bcbio.pipeline import version
if hasattr(version, "__version__"):
bcbio_version = ("%s-%s" % (version.__version__, version.__git_revision__)
if ... | [
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bcbio/bcbio-nextgen | bcbio/provenance/programs.py | _get_versions_manifest | def _get_versions_manifest(manifest_dir):
"""Retrieve versions from a pre-existing manifest of installed software.
"""
all_pkgs = _manifest_progs + [p.get("name", p["cmd"]) for p in _cl_progs] + [p["name"] for p in _alt_progs]
if os.path.exists(manifest_dir):
out = []
for plist in ["tool... | python | def _get_versions_manifest(manifest_dir):
"""Retrieve versions from a pre-existing manifest of installed software.
"""
all_pkgs = _manifest_progs + [p.get("name", p["cmd"]) for p in _cl_progs] + [p["name"] for p in _alt_progs]
if os.path.exists(manifest_dir):
out = []
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bcbio/bcbio-nextgen | bcbio/provenance/programs.py | write_versions | def write_versions(dirs, config=None, is_wrapper=False):
"""Write CSV file with versions used in analysis pipeline.
"""
out_file = _get_program_file(dirs)
if is_wrapper:
assert utils.file_exists(out_file), "Failed to create program versions from VM"
elif out_file is None:
for p in _g... | python | def write_versions(dirs, config=None, is_wrapper=False):
"""Write CSV file with versions used in analysis pipeline.
"""
out_file = _get_program_file(dirs)
if is_wrapper:
assert utils.file_exists(out_file), "Failed to create program versions from VM"
elif out_file is None:
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bcbio/bcbio-nextgen | bcbio/provenance/programs.py | get_version_manifest | def get_version_manifest(name, data=None, required=False):
"""Retrieve a version from the currently installed manifest.
"""
manifest_dir = _get_manifest_dir(data, name)
manifest_vs = _get_versions_manifest(manifest_dir) or []
for x in manifest_vs:
if x["program"] == name:
v = x.g... | python | def get_version_manifest(name, data=None, required=False):
"""Retrieve a version from the currently installed manifest.
"""
manifest_dir = _get_manifest_dir(data, name)
manifest_vs = _get_versions_manifest(manifest_dir) or []
for x in manifest_vs:
if x["program"] == name:
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bcbio/bcbio-nextgen | bcbio/provenance/programs.py | add_subparser | def add_subparser(subparsers):
"""Add command line option for exporting version information.
"""
parser = subparsers.add_parser("version",
help="Export versions of used software to stdout or a file ")
parser.add_argument("--workdir", help="Directory export programs to ... | python | def add_subparser(subparsers):
"""Add command line option for exporting version information.
"""
parser = subparsers.add_parser("version",
help="Export versions of used software to stdout or a file ")
parser.add_argument("--workdir", help="Directory export programs to ... | [
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bcbio/bcbio-nextgen | bcbio/provenance/programs.py | get_version | def get_version(name, dirs=None, config=None):
"""Retrieve the current version of the given program from cached names.
"""
if dirs:
p = _get_program_file(dirs)
else:
p = tz.get_in(["resources", "program_versions"], config)
if p:
with open(p) as in_handle:
for line... | python | def get_version(name, dirs=None, config=None):
"""Retrieve the current version of the given program from cached names.
"""
if dirs:
p = _get_program_file(dirs)
else:
p = tz.get_in(["resources", "program_versions"], config)
if p:
with open(p) as in_handle:
for line... | [
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bcbio/bcbio-nextgen | scripts/utils/hlas_to_pgroups.py | hla_choices | def hla_choices(orig_hla, min_parts=2):
"""Provide a range of options for HLA type, with decreasing resolution.
"""
yield orig_hla
try:
int(orig_hla[-1])
except ValueError:
yield orig_hla[:-1]
hla_parts = orig_hla.split(":")
for sub_i in range(len(hla_parts) - min_parts + 1):... | python | def hla_choices(orig_hla, min_parts=2):
"""Provide a range of options for HLA type, with decreasing resolution.
"""
yield orig_hla
try:
int(orig_hla[-1])
except ValueError:
yield orig_hla[:-1]
hla_parts = orig_hla.split(":")
for sub_i in range(len(hla_parts) - min_parts + 1):... | [
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bcbio/bcbio-nextgen | scripts/utils/hlas_to_pgroups.py | read_pgroups | def read_pgroups(in_file):
"""Read HLAs and the pgroups they fall in.
"""
out = {}
with open(in_file) as in_handle:
for line in (l for l in in_handle if not l.startswith("#")):
locus, alleles, group = line.strip().split(";")
for allele in alleles.split("/"):
... | python | def read_pgroups(in_file):
"""Read HLAs and the pgroups they fall in.
"""
out = {}
with open(in_file) as in_handle:
for line in (l for l in in_handle if not l.startswith("#")):
locus, alleles, group = line.strip().split(";")
for allele in alleles.split("/"):
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bcbio/bcbio-nextgen | scripts/utils/hlas_to_pgroups.py | read_hlas | def read_hlas(fasta_fai):
"""Get HLA alleles from the hg38 fasta fai file.
"""
out = []
with open(fasta_fai) as in_handle:
for line in in_handle:
if line.startswith("HLA"):
out.append(line.split()[0])
return out | python | def read_hlas(fasta_fai):
"""Get HLA alleles from the hg38 fasta fai file.
"""
out = []
with open(fasta_fai) as in_handle:
for line in in_handle:
if line.startswith("HLA"):
out.append(line.split()[0])
return out | [
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bcbio/bcbio-nextgen | bcbio/variation/split.py | split_vcf | def split_vcf(in_file, ref_file, config, out_dir=None):
"""Split a VCF file into separate files by chromosome.
"""
if out_dir is None:
out_dir = os.path.join(os.path.dirname(in_file), "split")
out_files = []
with open(ref.fasta_idx(ref_file, config)) as in_handle:
for line in in_hand... | python | def split_vcf(in_file, ref_file, config, out_dir=None):
"""Split a VCF file into separate files by chromosome.
"""
if out_dir is None:
out_dir = os.path.join(os.path.dirname(in_file), "split")
out_files = []
with open(ref.fasta_idx(ref_file, config)) as in_handle:
for line in in_hand... | [
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bcbio/bcbio-nextgen | bcbio/variation/split.py | subset_vcf | def subset_vcf(in_file, region, out_file, config):
"""Subset VCF in the given region, handling bgzip and indexing of input.
"""
work_file = vcfutils.bgzip_and_index(in_file, config)
if not file_exists(out_file):
with file_transaction(config, out_file) as tx_out_file:
bcftools = confi... | python | def subset_vcf(in_file, region, out_file, config):
"""Subset VCF in the given region, handling bgzip and indexing of input.
"""
work_file = vcfutils.bgzip_and_index(in_file, config)
if not file_exists(out_file):
with file_transaction(config, out_file) as tx_out_file:
bcftools = confi... | [
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bcbio/bcbio-nextgen | bcbio/variation/recalibrate.py | prep_recal | def prep_recal(data):
"""Do pre-BQSR recalibration, calculation of recalibration tables.
"""
if dd.get_recalibrate(data) in [True, "gatk"]:
logger.info("Prepare BQSR tables with GATK: %s " % str(dd.get_sample_name(data)))
dbsnp_file = tz.get_in(("genome_resources", "variation", "dbsnp"), dat... | python | def prep_recal(data):
"""Do pre-BQSR recalibration, calculation of recalibration tables.
"""
if dd.get_recalibrate(data) in [True, "gatk"]:
logger.info("Prepare BQSR tables with GATK: %s " % str(dd.get_sample_name(data)))
dbsnp_file = tz.get_in(("genome_resources", "variation", "dbsnp"), dat... | [
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bcbio/bcbio-nextgen | bcbio/variation/recalibrate.py | apply_recal | def apply_recal(data):
"""Apply recalibration tables to the sorted aligned BAM, producing recalibrated BAM.
"""
orig_bam = dd.get_align_bam(data) or dd.get_work_bam(data)
had_work_bam = "work_bam" in data
if dd.get_recalibrate(data) in [True, "gatk"]:
if data.get("prep_recal"):
l... | python | def apply_recal(data):
"""Apply recalibration tables to the sorted aligned BAM, producing recalibrated BAM.
"""
orig_bam = dd.get_align_bam(data) or dd.get_work_bam(data)
had_work_bam = "work_bam" in data
if dd.get_recalibrate(data) in [True, "gatk"]:
if data.get("prep_recal"):
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bcbio/bcbio-nextgen | bcbio/variation/recalibrate.py | _gatk_base_recalibrator | def _gatk_base_recalibrator(broad_runner, dup_align_bam, ref_file, platform,
dbsnp_file, intervals, data):
"""Step 1 of GATK recalibration process, producing table of covariates.
For GATK 4 we use local multicore spark runs:
https://github.com/broadinstitute/gatk/issues/2345
... | python | def _gatk_base_recalibrator(broad_runner, dup_align_bam, ref_file, platform,
dbsnp_file, intervals, data):
"""Step 1 of GATK recalibration process, producing table of covariates.
For GATK 4 we use local multicore spark runs:
https://github.com/broadinstitute/gatk/issues/2345
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bcbio/bcbio-nextgen | bcbio/variation/recalibrate.py | _gatk_apply_bqsr | def _gatk_apply_bqsr(data):
"""Parallel BQSR support for GATK4.
Normalized qualities to 3 bin outputs at 10, 20 and 30 based on pipeline standard
recommendations, which will help with output file sizes:
https://github.com/CCDG/Pipeline-Standardization/blob/master/PipelineStandard.md#base-quality-score-... | python | def _gatk_apply_bqsr(data):
"""Parallel BQSR support for GATK4.
Normalized qualities to 3 bin outputs at 10, 20 and 30 based on pipeline standard
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bcbio/bcbio-nextgen | bcbio/log/__init__.py | create_base_logger | def create_base_logger(config=None, parallel=None):
"""Setup base logging configuration, also handling remote logging.
Correctly sets up for local, multiprocessing and distributed runs.
Creates subscribers for non-local runs that will be references from
local logging.
Retrieves IP address using ti... | python | def create_base_logger(config=None, parallel=None):
"""Setup base logging configuration, also handling remote logging.
Correctly sets up for local, multiprocessing and distributed runs.
Creates subscribers for non-local runs that will be references from
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bcbio/bcbio-nextgen | bcbio/log/__init__.py | setup_local_logging | def setup_local_logging(config=None, parallel=None):
"""Setup logging for a local context, directing messages to appropriate base loggers.
Handles local, multiprocessing and distributed setup, connecting
to handlers created by the base logger.
"""
if config is None: config = {}
if parallel is N... | python | def setup_local_logging(config=None, parallel=None):
"""Setup logging for a local context, directing messages to appropriate base loggers.
Handles local, multiprocessing and distributed setup, connecting
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if config is None: config = {}
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bcbio/bcbio-nextgen | bcbio/log/__init__.py | setup_script_logging | def setup_script_logging():
"""
Use this logger for standalone scripts, or script-like subcommands,
such as bcbio_prepare_samples and bcbio_nextgen.py -w template.
"""
handlers = [logbook.NullHandler()]
format_str = ("[{record.time:%Y-%m-%dT%H:%MZ}] "
"{record.level_name}: {rec... | python | def setup_script_logging():
"""
Use this logger for standalone scripts, or script-like subcommands,
such as bcbio_prepare_samples and bcbio_nextgen.py -w template.
"""
handlers = [logbook.NullHandler()]
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bcbio/bcbio-nextgen | scripts/cwltool2wdl.py | _validate | def _validate(wdl_file):
"""Run validation on the generated WDL output using wdltool.
"""
start_dir = os.getcwd()
os.chdir(os.path.dirname(wdl_file))
print("Validating", wdl_file)
subprocess.check_call(["wdltool", "validate", wdl_file])
os.chdir(start_dir) | python | def _validate(wdl_file):
"""Run validation on the generated WDL output using wdltool.
"""
start_dir = os.getcwd()
os.chdir(os.path.dirname(wdl_file))
print("Validating", wdl_file)
subprocess.check_call(["wdltool", "validate", wdl_file])
os.chdir(start_dir) | [
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bcbio/bcbio-nextgen | scripts/cwltool2wdl.py | _wf_to_dict | def _wf_to_dict(wf, records):
"""Parse a workflow into cwl2wdl style dictionaries for base and sub-workflows.
"""
inputs, outputs, records = _get_wf_inout(wf, records)
out = {"name": _id_to_name(_clean_id(wf.tool["id"])), "inputs": inputs,
"outputs": outputs, "steps": [], "subworkflows": [],
... | python | def _wf_to_dict(wf, records):
"""Parse a workflow into cwl2wdl style dictionaries for base and sub-workflows.
"""
inputs, outputs, records = _get_wf_inout(wf, records)
out = {"name": _id_to_name(_clean_id(wf.tool["id"])), "inputs": inputs,
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bcbio/bcbio-nextgen | scripts/cwltool2wdl.py | _organize_step_scatter | def _organize_step_scatter(step, inputs, remapped):
"""Add scattering information from inputs, remapping input variables.
"""
def extract_scatter_id(inp):
_, ns_var = inp.split("#")
_, var = ns_var.split("/")
return var
scatter_local = {}
if "scatter" in step.tool:
as... | python | def _organize_step_scatter(step, inputs, remapped):
"""Add scattering information from inputs, remapping input variables.
"""
def extract_scatter_id(inp):
_, ns_var = inp.split("#")
_, var = ns_var.split("/")
return var
scatter_local = {}
if "scatter" in step.tool:
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bcbio/bcbio-nextgen | scripts/cwltool2wdl.py | _variable_type_to_read_fn | def _variable_type_to_read_fn(vartype, records):
"""Convert variant types into corresponding WDL standard library functions.
"""
fn_map = {"String": "read_string", "Array[String]": "read_lines",
"Array[Array[String]]": "read_tsv",
"Object": "read_object", "Array[Object]": "read_o... | python | def _variable_type_to_read_fn(vartype, records):
"""Convert variant types into corresponding WDL standard library functions.
"""
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bcbio/bcbio-nextgen | scripts/cwltool2wdl.py | _requirements_to_dict | def _requirements_to_dict(rs):
"""Convert supported requirements into dictionary for output.
"""
out = []
added = set([])
for r in rs:
if r["class"] == "DockerRequirement" and "docker" not in added:
added.add("docker")
out.append({"requirement_type": "docker", "value"... | python | def _requirements_to_dict(rs):
"""Convert supported requirements into dictionary for output.
"""
out = []
added = set([])
for r in rs:
if r["class"] == "DockerRequirement" and "docker" not in added:
added.add("docker")
out.append({"requirement_type": "docker", "value"... | [
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bcbio/bcbio-nextgen | bcbio/structural/purple.py | _get_jvm_opts | def _get_jvm_opts(out_file, data):
"""Retrieve Java options, adjusting memory for available cores.
"""
resources = config_utils.get_resources("purple", data["config"])
jvm_opts = resources.get("jvm_opts", ["-Xms750m", "-Xmx3500m"])
jvm_opts = config_utils.adjust_opts(jvm_opts, {"algorithm": {"memory... | python | def _get_jvm_opts(out_file, data):
"""Retrieve Java options, adjusting memory for available cores.
"""
resources = config_utils.get_resources("purple", data["config"])
jvm_opts = resources.get("jvm_opts", ["-Xms750m", "-Xmx3500m"])
jvm_opts = config_utils.adjust_opts(jvm_opts, {"algorithm": {"memory... | [
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bcbio/bcbio-nextgen | bcbio/structural/purple.py | _counts_to_amber | def _counts_to_amber(t_vals, n_vals):
"""Converts a line of CollectAllelicCounts into AMBER line.
"""
t_depth = int(t_vals["REF_COUNT"]) + int(t_vals["ALT_COUNT"])
n_depth = int(n_vals["REF_COUNT"]) + int(n_vals["ALT_COUNT"])
if n_depth > 0 and t_depth > 0:
t_baf = float(t_vals["ALT_COUNT"])... | python | def _counts_to_amber(t_vals, n_vals):
"""Converts a line of CollectAllelicCounts into AMBER line.
"""
t_depth = int(t_vals["REF_COUNT"]) + int(t_vals["ALT_COUNT"])
n_depth = int(n_vals["REF_COUNT"]) + int(n_vals["ALT_COUNT"])
if n_depth > 0 and t_depth > 0:
t_baf = float(t_vals["ALT_COUNT"])... | [
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bcbio/bcbio-nextgen | bcbio/structural/purple.py | _count_files_to_amber | def _count_files_to_amber(tumor_counts, normal_counts, work_dir, data):
"""Converts tumor and normal counts from GATK CollectAllelicCounts into Amber format.
"""
amber_dir = utils.safe_makedir(os.path.join(work_dir, "amber"))
out_file = os.path.join(amber_dir, "%s.amber.baf" % dd.get_sample_name(data))
... | python | def _count_files_to_amber(tumor_counts, normal_counts, work_dir, data):
"""Converts tumor and normal counts from GATK CollectAllelicCounts into Amber format.
"""
amber_dir = utils.safe_makedir(os.path.join(work_dir, "amber"))
out_file = os.path.join(amber_dir, "%s.amber.baf" % dd.get_sample_name(data))
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bcbio/bcbio-nextgen | bcbio/structural/purple.py | _amber_het_file | def _amber_het_file(method, vrn_files, work_dir, paired):
"""Create file of BAFs in normal heterozygous positions compatible with AMBER.
Two available methods:
- pon -- Use panel of normals with likely heterozygous sites.
- variants -- Use pre-existing variant calls, filtered to likely heterozygote... | python | def _amber_het_file(method, vrn_files, work_dir, paired):
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- pon -- Use panel of normals with likely heterozygous sites.
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bcbio/bcbio-nextgen | bcbio/structural/purple.py | _run_cobalt | def _run_cobalt(paired, work_dir):
"""Run Cobalt for counting read depth across genomic windows.
PURPLE requires even 1000bp windows so use integrated counting solution
directly rather than converting from CNVkit calculations. If this approach
is useful should be moved upstream to be available to other... | python | def _run_cobalt(paired, work_dir):
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bcbio/bcbio-nextgen | bcbio/structural/purple.py | _cobalt_ratio_file | def _cobalt_ratio_file(paired, work_dir):
"""Convert CNVkit binning counts into cobalt ratio output.
This contains read counts plus normalization for GC, from section 7.2
"Determine read depth ratios for tumor and reference genomes"
https://www.biorxiv.org/content/biorxiv/early/2018/09/20/415133.full.... | python | def _cobalt_ratio_file(paired, work_dir):
"""Convert CNVkit binning counts into cobalt ratio output.
This contains read counts plus normalization for GC, from section 7.2
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bcbio/bcbio-nextgen | bcbio/structural/purple.py | _export_to_vcf | def _export_to_vcf(cur):
"""Convert PURPLE custom output into VCF.
"""
if float(cur["copyNumber"]) > 2.0:
svtype = "DUP"
elif float(cur["copyNumber"]) < 2.0:
svtype = "DEL"
else:
svtype = None
if svtype:
info = ["END=%s" % cur["end"], "SVLEN=%s" % (int(cur["end"])... | python | def _export_to_vcf(cur):
"""Convert PURPLE custom output into VCF.
"""
if float(cur["copyNumber"]) > 2.0:
svtype = "DUP"
elif float(cur["copyNumber"]) < 2.0:
svtype = "DEL"
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bcbio/bcbio-nextgen | bcbio/rnaseq/pizzly.py | make_pizzly_gtf | def make_pizzly_gtf(gtf_file, out_file, data):
"""
pizzly needs the GTF to be in gene -> transcript -> exon order for each
gene. it also wants the gene biotype set as the source
"""
if file_exists(out_file):
return out_file
db = gtf.get_gtf_db(gtf_file)
with file_transaction(data, ou... | python | def make_pizzly_gtf(gtf_file, out_file, data):
"""
pizzly needs the GTF to be in gene -> transcript -> exon order for each
gene. it also wants the gene biotype set as the source
"""
if file_exists(out_file):
return out_file
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bcbio/bcbio-nextgen | bcbio/structural/validate.py | _validate_caller_vcf | def _validate_caller_vcf(call_vcf, truth_vcf, callable_bed, svcaller, work_dir, data):
"""Validate a caller VCF against truth within callable regions using SURVIVOR.
Combines files with SURIVOR merge and counts (https://github.com/fritzsedlazeck/SURVIVOR/)
"""
stats = _calculate_comparison_stats(truth_... | python | def _validate_caller_vcf(call_vcf, truth_vcf, callable_bed, svcaller, work_dir, data):
"""Validate a caller VCF against truth within callable regions using SURVIVOR.
Combines files with SURIVOR merge and counts (https://github.com/fritzsedlazeck/SURVIVOR/)
"""
stats = _calculate_comparison_stats(truth_... | [
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bcbio/bcbio-nextgen | bcbio/structural/validate.py | _survivor_merge | def _survivor_merge(call_vcf, truth_vcf, stats, work_dir, data):
"""Perform a merge of two callsets using SURVIVOR,
"""
out_file = os.path.join(work_dir, "eval-merge.vcf")
if not utils.file_uptodate(out_file, call_vcf):
in_call_vcf = call_vcf.replace(".vcf.gz", ".vcf")
if not utils.file_... | python | def _survivor_merge(call_vcf, truth_vcf, stats, work_dir, data):
"""Perform a merge of two callsets using SURVIVOR,
"""
out_file = os.path.join(work_dir, "eval-merge.vcf")
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bcbio/bcbio-nextgen | bcbio/structural/validate.py | _calculate_comparison_stats | def _calculate_comparison_stats(truth_vcf):
"""Identify calls to validate from the input truth VCF.
"""
# Avoid very small events for average calculations
min_stat_size = 50
min_median_size = 250
sizes = []
svtypes = set([])
with utils.open_gzipsafe(truth_vcf) as in_handle:
for c... | python | def _calculate_comparison_stats(truth_vcf):
"""Identify calls to validate from the input truth VCF.
"""
# Avoid very small events for average calculations
min_stat_size = 50
min_median_size = 250
sizes = []
svtypes = set([])
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bcbio/bcbio-nextgen | bcbio/structural/validate.py | _get_start_end | def _get_start_end(parts, index=7):
"""Retrieve start and end for a VCF record, skips BNDs without END coords
"""
start = parts[1]
end = [x.split("=")[-1] for x in parts[index].split(";") if x.startswith("END=")]
if end:
end = end[0]
return start, end
return None, None | python | def _get_start_end(parts, index=7):
"""Retrieve start and end for a VCF record, skips BNDs without END coords
"""
start = parts[1]
end = [x.split("=")[-1] for x in parts[index].split(";") if x.startswith("END=")]
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bcbio/bcbio-nextgen | bcbio/structural/validate.py | _summarize_call | def _summarize_call(parts):
"""Provide summary metrics on size and svtype for a SV call.
"""
svtype = [x.split("=")[1] for x in parts[7].split(";") if x.startswith("SVTYPE=")]
svtype = svtype[0] if svtype else ""
start, end = _get_start_end(parts)
return {"svtype": svtype, "size": int(end) - int... | python | def _summarize_call(parts):
"""Provide summary metrics on size and svtype for a SV call.
"""
svtype = [x.split("=")[1] for x in parts[7].split(";") if x.startswith("SVTYPE=")]
svtype = svtype[0] if svtype else ""
start, end = _get_start_end(parts)
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bcbio/bcbio-nextgen | bcbio/structural/validate.py | _prep_callable_bed | def _prep_callable_bed(in_file, work_dir, stats, data):
"""Sort and merge callable BED regions to prevent SV double counting
"""
out_file = os.path.join(work_dir, "%s-merge.bed.gz" % utils.splitext_plus(os.path.basename(in_file))[0])
gsort = config_utils.get_program("gsort", data)
if not utils.file_... | python | def _prep_callable_bed(in_file, work_dir, stats, data):
"""Sort and merge callable BED regions to prevent SV double counting
"""
out_file = os.path.join(work_dir, "%s-merge.bed.gz" % utils.splitext_plus(os.path.basename(in_file))[0])
gsort = config_utils.get_program("gsort", data)
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bcbio/bcbio-nextgen | bcbio/structural/validate.py | _get_anns_to_remove | def _get_anns_to_remove(in_file):
"""Find larger annotations, if present in VCF, that slow down processing.
"""
to_remove = ["ANN", "LOF"]
to_remove_str = tuple(["##INFO=<ID=%s" % x for x in to_remove])
cur_remove = []
with utils.open_gzipsafe(in_file) as in_handle:
for line in in_handle... | python | def _get_anns_to_remove(in_file):
"""Find larger annotations, if present in VCF, that slow down processing.
"""
to_remove = ["ANN", "LOF"]
to_remove_str = tuple(["##INFO=<ID=%s" % x for x in to_remove])
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bcbio/bcbio-nextgen | bcbio/structural/validate.py | cnv_to_event | def cnv_to_event(name, data):
"""Convert a CNV to an event name.
"""
cur_ploidy = ploidy.get_ploidy([data])
if name.startswith("cnv"):
num = max([int(x) for x in name.split("_")[0].replace("cnv", "").split(";")])
if num < cur_ploidy:
return "DEL"
elif num > cur_ploidy... | python | def cnv_to_event(name, data):
"""Convert a CNV to an event name.
"""
cur_ploidy = ploidy.get_ploidy([data])
if name.startswith("cnv"):
num = max([int(x) for x in name.split("_")[0].replace("cnv", "").split(";")])
if num < cur_ploidy:
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bcbio/bcbio-nextgen | bcbio/structural/validate.py | _evaluate_one | def _evaluate_one(caller, svtype, size_range, ensemble, truth, data):
"""Compare a ensemble results for a caller against a specific caller and SV type.
"""
def cnv_matches(name):
return cnv_to_event(name, data) == svtype
def is_breakend(name):
return name.startswith("BND")
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"""Compare a ensemble results for a caller against a specific caller and SV type.
"""
def cnv_matches(name):
return cnv_to_event(name, data) == svtype
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bcbio/bcbio-nextgen | bcbio/structural/validate.py | _plot_evaluation_event | def _plot_evaluation_event(df_csv, svtype):
"""Provide plot of evaluation metrics for an SV event, stratified by event size.
"""
titles = {"INV": "Inversions", "DEL": "Deletions", "DUP": "Duplications",
"INS": "Insertions"}
out_file = "%s-%s.png" % (os.path.splitext(df_csv)[0], svtype)
... | python | def _plot_evaluation_event(df_csv, svtype):
"""Provide plot of evaluation metrics for an SV event, stratified by event size.
"""
titles = {"INV": "Inversions", "DEL": "Deletions", "DUP": "Duplications",
"INS": "Insertions"}
out_file = "%s-%s.png" % (os.path.splitext(df_csv)[0], svtype)
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bcbio/bcbio-nextgen | bcbio/structural/validate.py | evaluate | def evaluate(data):
"""Provide evaluations for multiple callers split by structural variant type.
"""
work_dir = utils.safe_makedir(os.path.join(data["dirs"]["work"], "structural",
dd.get_sample_name(data), "validate"))
truth_sets = tz.get_in(["config", "al... | python | def evaluate(data):
"""Provide evaluations for multiple callers split by structural variant type.
"""
work_dir = utils.safe_makedir(os.path.join(data["dirs"]["work"], "structural",
dd.get_sample_name(data), "validate"))
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bcbio/bcbio-nextgen | bcbio/variation/mutect2.py | _add_region_params | def _add_region_params(region, out_file, items, gatk_type):
"""Add parameters for selecting by region to command line.
"""
params = []
variant_regions = bedutils.population_variant_regions(items)
region = subset_variant_regions(variant_regions, region, out_file, items)
if region:
if gatk... | python | def _add_region_params(region, out_file, items, gatk_type):
"""Add parameters for selecting by region to command line.
"""
params = []
variant_regions = bedutils.population_variant_regions(items)
region = subset_variant_regions(variant_regions, region, out_file, items)
if region:
if gatk... | [
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bcbio/bcbio-nextgen | bcbio/variation/mutect2.py | _prep_inputs | def _prep_inputs(align_bams, ref_file, items):
"""Ensure inputs to calling are indexed as expected.
"""
broad_runner = broad.runner_from_path("picard", items[0]["config"])
broad_runner.run_fn("picard_index_ref", ref_file)
for x in align_bams:
bam.index(x, items[0]["config"]) | python | def _prep_inputs(align_bams, ref_file, items):
"""Ensure inputs to calling are indexed as expected.
"""
broad_runner = broad.runner_from_path("picard", items[0]["config"])
broad_runner.run_fn("picard_index_ref", ref_file)
for x in align_bams:
bam.index(x, items[0]["config"]) | [
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bcbio/bcbio-nextgen | bcbio/variation/mutect2.py | mutect2_caller | 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+.
"""
if out_file is None:
out_file = "%s-variants.vcf.gz" % utils.splitext_plus(ali... | python | 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+.
"""
if out_file is None:
out_file = "%s-variants.vcf.gz" % utils.splitext_plus(ali... | [
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bcbio/bcbio-nextgen | bcbio/variation/mutect2.py | _mutect2_filter | def _mutect2_filter(broad_runner, in_file, out_file, ref_file):
"""Filter of MuTect2 calls, a separate step in GATK4.
"""
params = ["-T", "FilterMutectCalls", "--reference", ref_file, "--variant", in_file, "--output", out_file]
return broad_runner.cl_gatk(params, os.path.dirname(out_file)) | python | def _mutect2_filter(broad_runner, in_file, out_file, ref_file):
"""Filter of MuTect2 calls, a separate step in GATK4.
"""
params = ["-T", "FilterMutectCalls", "--reference", ref_file, "--variant", in_file, "--output", out_file]
return broad_runner.cl_gatk(params, os.path.dirname(out_file)) | [
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bcbio/bcbio-nextgen | bcbio/upload/irods.py | update_file | def update_file(finfo, sample_info, config):
"""
Update the file to an iRODS repository.
"""
ffinal = filesystem.update_file(finfo, sample_info, config, pass_uptodate=True)
_upload_dir_icommands_cli(config.get("dir"), config.get("folder"), config) | python | def update_file(finfo, sample_info, config):
"""
Update the file to an iRODS repository.
"""
ffinal = filesystem.update_file(finfo, sample_info, config, pass_uptodate=True)
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bcbio/bcbio-nextgen | bcbio/structural/__init__.py | _get_callers | def _get_callers(items, stage, special_cases=False):
"""Retrieve available callers for the provided stage.
Handles special cases like CNVkit that can be in initial or standard
depending on if fed into Lumpy analysis.
"""
callers = utils.deepish_copy(_CALLERS[stage])
if special_cases and "cnvkit... | python | def _get_callers(items, stage, special_cases=False):
"""Retrieve available callers for the provided stage.
Handles special cases like CNVkit that can be in initial or standard
depending on if fed into Lumpy analysis.
"""
callers = utils.deepish_copy(_CALLERS[stage])
if special_cases and "cnvkit... | [
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bcbio/bcbio-nextgen | bcbio/structural/__init__.py | _handle_multiple_svcallers | def _handle_multiple_svcallers(data, stage):
"""Retrieve configured structural variation caller, handling multiple.
"""
svs = get_svcallers(data)
# special cases -- prioritization
if stage == "ensemble" and dd.get_svprioritize(data):
svs.append("prioritize")
out = []
for svcaller in ... | python | def _handle_multiple_svcallers(data, stage):
"""Retrieve configured structural variation caller, handling multiple.
"""
svs = get_svcallers(data)
# special cases -- prioritization
if stage == "ensemble" and dd.get_svprioritize(data):
svs.append("prioritize")
out = []
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bcbio/bcbio-nextgen | bcbio/structural/__init__.py | finalize_sv | def finalize_sv(samples, config):
"""Combine results from multiple sv callers into a single ordered 'sv' key.
"""
by_bam = collections.OrderedDict()
for x in samples:
batch = dd.get_batch(x) or [dd.get_sample_name(x)]
try:
by_bam[x["align_bam"], tuple(batch)].append(x)
... | python | def finalize_sv(samples, config):
"""Combine results from multiple sv callers into a single ordered 'sv' key.
"""
by_bam = collections.OrderedDict()
for x in samples:
batch = dd.get_batch(x) or [dd.get_sample_name(x)]
try:
by_bam[x["align_bam"], tuple(batch)].append(x)
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bcbio/bcbio-nextgen | bcbio/structural/__init__.py | batch_for_sv | def batch_for_sv(samples):
"""Prepare a set of samples for parallel structural variant calling.
CWL input target -- groups samples into batches and structural variant
callers for parallel processing.
"""
samples = cwlutils.assign_complex_to_samples(samples)
to_process, extras, background = _bat... | python | def batch_for_sv(samples):
"""Prepare a set of samples for parallel structural variant calling.
CWL input target -- groups samples into batches and structural variant
callers for parallel processing.
"""
samples = cwlutils.assign_complex_to_samples(samples)
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bcbio/bcbio-nextgen | bcbio/structural/__init__.py | run | def run(samples, run_parallel, stage):
"""Run structural variation detection.
The stage indicates which level of structural variant calling to run.
- initial, callers that can be used in subsequent structural variation steps (cnvkit -> lumpy)
- standard, regular batch calling
- ensemble, post... | python | def run(samples, run_parallel, stage):
"""Run structural variation detection.
The stage indicates which level of structural variant calling to run.
- initial, callers that can be used in subsequent structural variation steps (cnvkit -> lumpy)
- standard, regular batch calling
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bcbio/bcbio-nextgen | bcbio/structural/__init__.py | detect_sv | def detect_sv(items, all_items=None, stage="standard"):
"""Top level parallel target for examining structural variation.
"""
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 = _... | python | def detect_sv(items, all_items=None, stage="standard"):
"""Top level parallel target for examining structural variation.
"""
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 = _... | [
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bcbio/bcbio-nextgen | bcbio/structural/__init__.py | _add_supplemental | def _add_supplemental(data):
"""Add additional supplemental files to CWL sv output, give useful names.
"""
if "supplemental" not in data["sv"]:
data["sv"]["supplemental"] = []
if data["sv"].get("variantcaller"):
cur_name = _useful_basename(data)
for k in ["cns", "vrn_bed"]:
... | python | def _add_supplemental(data):
"""Add additional supplemental files to CWL sv output, give useful names.
"""
if "supplemental" not in data["sv"]:
data["sv"]["supplemental"] = []
if data["sv"].get("variantcaller"):
cur_name = _useful_basename(data)
for k in ["cns", "vrn_bed"]:
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bcbio/bcbio-nextgen | bcbio/structural/__init__.py | _clean_name | def _clean_name(fname, data):
"""Remove standard prefixes from a filename before renaming with useful names.
"""
for to_remove in dd.get_batches(data) + [dd.get_sample_name(data), data["sv"]["variantcaller"]]:
for ext in ("-", "_"):
if fname.startswith("%s%s" % (to_remove, ext)):
... | python | def _clean_name(fname, data):
"""Remove standard prefixes from a filename before renaming with useful names.
"""
for to_remove in dd.get_batches(data) + [dd.get_sample_name(data), data["sv"]["variantcaller"]]:
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bcbio/bcbio-nextgen | bcbio/structural/__init__.py | _group_by_sample | def _group_by_sample(items):
"""Group a set of items by sample names + multiple callers for prioritization
"""
by_sample = collections.defaultdict(list)
for d in items:
by_sample[dd.get_sample_name(d)].append(d)
out = []
for sample_group in by_sample.values():
cur = utils.deepish... | python | def _group_by_sample(items):
"""Group a set of items by sample names + multiple callers for prioritization
"""
by_sample = collections.defaultdict(list)
for d in items:
by_sample[dd.get_sample_name(d)].append(d)
out = []
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bcbio/bcbio-nextgen | bcbio/structural/__init__.py | standardize_cnv_reference | def standardize_cnv_reference(data):
"""Standardize cnv_reference background to support multiple callers.
"""
out = tz.get_in(["config", "algorithm", "background", "cnv_reference"], data, {})
cur_callers = set(data["config"]["algorithm"].get("svcaller")) & _CNV_REFERENCE
if isinstance(out, six.strin... | python | def standardize_cnv_reference(data):
"""Standardize cnv_reference background to support multiple callers.
"""
out = tz.get_in(["config", "algorithm", "background", "cnv_reference"], data, {})
cur_callers = set(data["config"]["algorithm"].get("svcaller")) & _CNV_REFERENCE
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bcbio/bcbio-nextgen | bcbio/ngsalign/bowtie2.py | _bowtie2_args_from_config | def _bowtie2_args_from_config(config, curcl):
"""Configurable high level options for bowtie2.
"""
qual_format = config["algorithm"].get("quality_format", "")
if qual_format.lower() == "illumina":
qual_flags = ["--phred64-quals"]
else:
qual_flags = []
num_cores = config["algorithm... | python | def _bowtie2_args_from_config(config, curcl):
"""Configurable high level options for bowtie2.
"""
qual_format = config["algorithm"].get("quality_format", "")
if qual_format.lower() == "illumina":
qual_flags = ["--phred64-quals"]
else:
qual_flags = []
num_cores = config["algorithm... | [
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bcbio/bcbio-nextgen | bcbio/ngsalign/bowtie2.py | align | def align(fastq_file, pair_file, ref_file, names, align_dir, data,
extra_args=None):
"""Alignment with bowtie2.
"""
config = data["config"]
analysis_config = ANALYSIS.get(data["analysis"].lower())
assert analysis_config, "Analysis %s is not supported by bowtie2" % (data["analysis"])
ou... | python | def align(fastq_file, pair_file, ref_file, names, align_dir, data,
extra_args=None):
"""Alignment with bowtie2.
"""
config = data["config"]
analysis_config = ANALYSIS.get(data["analysis"].lower())
assert analysis_config, "Analysis %s is not supported by bowtie2" % (data["analysis"])
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bcbio/bcbio-nextgen | bcbio/cwl/hpc.py | create_cromwell_config | def create_cromwell_config(args, work_dir, sample_file):
"""Prepare a cromwell configuration within the current working directory.
"""
docker_attrs = ["String? docker", "String? docker_user"]
cwl_attrs = ["Int? cpuMin", "Int? cpuMax", "Int? memoryMin", "Int? memoryMax", "String? outDirMin",
... | python | def create_cromwell_config(args, work_dir, sample_file):
"""Prepare a cromwell configuration within the current working directory.
"""
docker_attrs = ["String? docker", "String? docker_user"]
cwl_attrs = ["Int? cpuMin", "Int? cpuMax", "Int? memoryMin", "Int? memoryMax", "String? outDirMin",
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bcbio/bcbio-nextgen | bcbio/cwl/hpc.py | _get_file_paths | def _get_file_paths(cur):
"""Retrieve a list of file paths, recursively traversing the
"""
out = []
if isinstance(cur, (list, tuple)):
for x in cur:
new = _get_file_paths(x)
if new:
out.extend(new)
elif isinstance(cur, dict):
if "class" in cur:... | python | def _get_file_paths(cur):
"""Retrieve a list of file paths, recursively traversing the
"""
out = []
if isinstance(cur, (list, tuple)):
for x in cur:
new = _get_file_paths(x)
if new:
out.extend(new)
elif isinstance(cur, dict):
if "class" in cur:... | [
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bcbio/bcbio-nextgen | bcbio/cwl/hpc.py | _load_custom_config | def _load_custom_config(run_config):
"""Load custom configuration input HOCON file for cromwell.
"""
from pyhocon import ConfigFactory, HOCONConverter, ConfigTree
conf = ConfigFactory.parse_file(run_config)
out = {}
if "database" in conf:
out["database"] = HOCONConverter.to_hocon(ConfigT... | python | def _load_custom_config(run_config):
"""Load custom configuration input HOCON file for cromwell.
"""
from pyhocon import ConfigFactory, HOCONConverter, ConfigTree
conf = ConfigFactory.parse_file(run_config)
out = {}
if "database" in conf:
out["database"] = HOCONConverter.to_hocon(ConfigT... | [
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bcbio/bcbio-nextgen | bcbio/cwl/hpc.py | _args_to_cromwell | def _args_to_cromwell(args):
"""Convert input arguments into cromwell inputs for config and command line.
"""
default_config = {"slurm": {"timelimit": "1-00:00", "account": ""},
"sge": {"memtype": "mem_free", "pename": "smp"},
"lsf": {"walltime": "24:00", "account... | python | def _args_to_cromwell(args):
"""Convert input arguments into cromwell inputs for config and command line.
"""
default_config = {"slurm": {"timelimit": "1-00:00", "account": ""},
"sge": {"memtype": "mem_free", "pename": "smp"},
"lsf": {"walltime": "24:00", "account... | [
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bcbio/bcbio-nextgen | bcbio/cwl/hpc.py | _get_filesystem_types | def _get_filesystem_types(args, sample_file):
"""Retrieve the types of inputs and staging based on sample JSON and arguments.
"""
out = set([])
ext = "" if args.no_container else "_container"
with open(sample_file) as in_handle:
for f in _get_file_paths(json.load(in_handle)):
if ... | python | def _get_filesystem_types(args, sample_file):
"""Retrieve the types of inputs and staging based on sample JSON and arguments.
"""
out = set([])
ext = "" if args.no_container else "_container"
with open(sample_file) as in_handle:
for f in _get_file_paths(json.load(in_handle)):
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bcbio/bcbio-nextgen | bcbio/cwl/hpc.py | _get_filesystem_config | def _get_filesystem_config(file_types):
"""Retrieve filesystem configuration, including support for specified file types.
"""
out = " filesystems {\n"
for file_type in sorted(list(file_types)):
if file_type in _FILESYSTEM_CONFIG:
out += _FILESYSTEM_CONFIG[file_type]
out += " ... | python | def _get_filesystem_config(file_types):
"""Retrieve filesystem configuration, including support for specified file types.
"""
out = " filesystems {\n"
for file_type in sorted(list(file_types)):
if file_type in _FILESYSTEM_CONFIG:
out += _FILESYSTEM_CONFIG[file_type]
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bcbio/bcbio-nextgen | bcbio/cwl/hpc.py | _get_engine_filesystem_config | def _get_engine_filesystem_config(file_types, args, conf_args):
"""Retriever authorization and engine filesystem configuration.
"""
file_types = [x.replace("_container", "") for x in list(file_types)]
out = ""
if "gcp" in file_types:
out += _AUTH_CONFIG_GOOGLE
if "s3" in file_types:
... | python | def _get_engine_filesystem_config(file_types, args, conf_args):
"""Retriever authorization and engine filesystem configuration.
"""
file_types = [x.replace("_container", "") for x in list(file_types)]
out = ""
if "gcp" in file_types:
out += _AUTH_CONFIG_GOOGLE
if "s3" in file_types:
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bcbio/bcbio-nextgen | bcbio/variation/normalize.py | normalize | def normalize(in_file, data, passonly=False, normalize_indels=True, split_biallelic=True,
rerun_effects=True, remove_oldeffects=False, nonrefonly=False, work_dir=None):
"""Normalizes variants and reruns SnpEFF for resulting VCF
"""
if remove_oldeffects:
out_file = "%s-noeff-nomultialle... | python | def normalize(in_file, data, passonly=False, normalize_indels=True, split_biallelic=True,
rerun_effects=True, remove_oldeffects=False, nonrefonly=False, work_dir=None):
"""Normalizes variants and reruns SnpEFF for resulting VCF
"""
if remove_oldeffects:
out_file = "%s-noeff-nomultialle... | [
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bcbio/bcbio-nextgen | bcbio/variation/normalize.py | _normalize | def _normalize(in_file, data, passonly=False, normalize_indels=True, split_biallelic=True,
remove_oldeffects=False, nonrefonly=False, work_dir=None):
"""Convert multi-allelic variants into single allelic.
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"""Convert multi-allelic variants into single allelic.
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bcbio/bcbio-nextgen | bcbio/rnaseq/sailfish.py | sleuthify_sailfish | def sleuthify_sailfish(sailfish_dir):
"""
if installed, use wasabi to create abundance.h5 output for use with
sleuth
"""
if not R_package_path("wasabi"):
return None
else:
rscript = Rscript_cmd()
cmd = """{rscript} --no-environ -e 'library("wasabi"); prepare_fish_for_sleu... | python | def sleuthify_sailfish(sailfish_dir):
"""
if installed, use wasabi to create abundance.h5 output for use with
sleuth
"""
if not R_package_path("wasabi"):
return None
else:
rscript = Rscript_cmd()
cmd = """{rscript} --no-environ -e 'library("wasabi"); prepare_fish_for_sleu... | [
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sleuth | [
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] | 6a9348c0054ccd5baffd22f1bb7d0422f6978b20 | https://github.com/bcbio/bcbio-nextgen/blob/6a9348c0054ccd5baffd22f1bb7d0422f6978b20/bcbio/rnaseq/sailfish.py#L66-L77 | train |
bcbio/bcbio-nextgen | bcbio/rnaseq/sailfish.py | create_combined_fasta | def create_combined_fasta(data):
"""
if there are genomes to be disambiguated, create a FASTA file of
all of the transcripts for all genomes
"""
out_dir = os.path.join(dd.get_work_dir(data), "inputs", "transcriptome")
items = disambiguate.split([data])
fasta_files = []
for i in items:
... | python | def create_combined_fasta(data):
"""
if there are genomes to be disambiguated, create a FASTA file of
all of the transcripts for all genomes
"""
out_dir = os.path.join(dd.get_work_dir(data), "inputs", "transcriptome")
items = disambiguate.split([data])
fasta_files = []
for i in items:
... | [
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