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bcbio/bcbio-nextgen | bcbio/galaxy/nglims.py | prep_samples_and_config | def prep_samples_and_config(run_folder, ldetails, fastq_dir, config):
"""Prepare sample fastq files and provide global sample configuration for the flowcell.
Handles merging of fastq files split by lane and also by the bcl2fastq
preparation process.
"""
fastq_final_dir = utils.safe_makedir(os.path.... | python | def prep_samples_and_config(run_folder, ldetails, fastq_dir, config):
"""Prepare sample fastq files and provide global sample configuration for the flowcell.
Handles merging of fastq files split by lane and also by the bcl2fastq
preparation process.
"""
fastq_final_dir = utils.safe_makedir(os.path.... | [
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bcbio/bcbio-nextgen | bcbio/galaxy/nglims.py | _prep_sample_and_config | def _prep_sample_and_config(ldetail_group, fastq_dir, fastq_final_dir):
"""Prepare output fastq file and configuration for a single sample.
Only passes non-empty files through for processing.
"""
files = []
print("->", ldetail_group[0]["name"], len(ldetail_group))
for read in ["R1", "R2"]:
... | python | def _prep_sample_and_config(ldetail_group, fastq_dir, fastq_final_dir):
"""Prepare output fastq file and configuration for a single sample.
Only passes non-empty files through for processing.
"""
files = []
print("->", ldetail_group[0]["name"], len(ldetail_group))
for read in ["R1", "R2"]:
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bcbio/bcbio-nextgen | bcbio/galaxy/nglims.py | _write_sample_config | def _write_sample_config(run_folder, ldetails):
"""Generate a bcbio-nextgen YAML configuration file for processing a sample.
"""
out_file = os.path.join(run_folder, "%s.yaml" % os.path.basename(run_folder))
with open(out_file, "w") as out_handle:
fc_name, fc_date = flowcell.parse_dirname(run_fol... | python | def _write_sample_config(run_folder, ldetails):
"""Generate a bcbio-nextgen YAML configuration file for processing a sample.
"""
out_file = os.path.join(run_folder, "%s.yaml" % os.path.basename(run_folder))
with open(out_file, "w") as out_handle:
fc_name, fc_date = flowcell.parse_dirname(run_fol... | [
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bcbio/bcbio-nextgen | bcbio/galaxy/nglims.py | _prepare_sample | def _prepare_sample(data, run_folder):
"""Extract passed keywords from input LIMS information.
"""
want = set(["description", "files", "genome_build", "name", "analysis", "upload", "algorithm"])
out = {}
for k, v in data.items():
if k in want:
out[k] = _relative_paths(v, run_fold... | python | def _prepare_sample(data, run_folder):
"""Extract passed keywords from input LIMS information.
"""
want = set(["description", "files", "genome_build", "name", "analysis", "upload", "algorithm"])
out = {}
for k, v in data.items():
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bcbio/bcbio-nextgen | bcbio/galaxy/nglims.py | _select_default_algorithm | def _select_default_algorithm(analysis):
"""Provide default algorithm sections from templates or standard
"""
if not analysis or analysis == "Standard":
return "Standard", {"aligner": "bwa", "platform": "illumina", "quality_format": "Standard",
"recalibrate": False, "real... | python | def _select_default_algorithm(analysis):
"""Provide default algorithm sections from templates or standard
"""
if not analysis or analysis == "Standard":
return "Standard", {"aligner": "bwa", "platform": "illumina", "quality_format": "Standard",
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bcbio/bcbio-nextgen | bcbio/galaxy/nglims.py | _relative_paths | def _relative_paths(xs, base_path):
"""Adjust paths to be relative to the provided base path.
"""
if isinstance(xs, six.string_types):
if xs.startswith(base_path):
return xs.replace(base_path + "/", "", 1)
else:
return xs
elif isinstance(xs, (list, tuple)):
... | python | def _relative_paths(xs, base_path):
"""Adjust paths to be relative to the provided base path.
"""
if isinstance(xs, six.string_types):
if xs.startswith(base_path):
return xs.replace(base_path + "/", "", 1)
else:
return xs
elif isinstance(xs, (list, tuple)):
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bcbio/bcbio-nextgen | bcbio/galaxy/nglims.py | _get_fastq_files | def _get_fastq_files(ldetail, read, fastq_dir):
"""Retrieve fastq files corresponding to the sample and read number.
"""
return glob.glob(os.path.join(fastq_dir, "Project_%s" % ldetail["project_name"],
"Sample_%s" % ldetail["name"],
"%s_*_%... | python | def _get_fastq_files(ldetail, read, fastq_dir):
"""Retrieve fastq files corresponding to the sample and read number.
"""
return glob.glob(os.path.join(fastq_dir, "Project_%s" % ldetail["project_name"],
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bcbio/bcbio-nextgen | bcbio/galaxy/nglims.py | _concat_bgzip_fastq | def _concat_bgzip_fastq(finputs, out_dir, read, ldetail):
"""Concatenate multiple input fastq files, preparing a bgzipped output file.
"""
out_file = os.path.join(out_dir, "%s_%s.fastq.gz" % (ldetail["name"], read))
if not utils.file_exists(out_file):
with file_transaction(out_file) as tx_out_fi... | python | def _concat_bgzip_fastq(finputs, out_dir, read, ldetail):
"""Concatenate multiple input fastq files, preparing a bgzipped output file.
"""
out_file = os.path.join(out_dir, "%s_%s.fastq.gz" % (ldetail["name"], read))
if not utils.file_exists(out_file):
with file_transaction(out_file) as tx_out_fi... | [
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bcbio/bcbio-nextgen | bcbio/galaxy/nglims.py | get_runinfo | def get_runinfo(galaxy_url, galaxy_apikey, run_folder, storedir):
"""Retrieve flattened run information for a processed directory from Galaxy nglims API.
"""
galaxy_api = GalaxyApiAccess(galaxy_url, galaxy_apikey)
fc_name, fc_date = flowcell.parse_dirname(run_folder)
galaxy_info = galaxy_api.run_det... | python | def get_runinfo(galaxy_url, galaxy_apikey, run_folder, storedir):
"""Retrieve flattened run information for a processed directory from Galaxy nglims API.
"""
galaxy_api = GalaxyApiAccess(galaxy_url, galaxy_apikey)
fc_name, fc_date = flowcell.parse_dirname(run_folder)
galaxy_info = galaxy_api.run_det... | [
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bcbio/bcbio-nextgen | bcbio/galaxy/nglims.py | _flatten_lane_details | def _flatten_lane_details(runinfo):
"""Provide flattened lane information with multiplexed barcodes separated.
"""
out = []
for ldetail in runinfo["details"]:
# handle controls
if "project_name" not in ldetail and ldetail["description"] == "control":
ldetail["project_name"] =... | python | def _flatten_lane_details(runinfo):
"""Provide flattened lane information with multiplexed barcodes separated.
"""
out = []
for ldetail in runinfo["details"]:
# handle controls
if "project_name" not in ldetail and ldetail["description"] == "control":
ldetail["project_name"] =... | [
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bcbio/bcbio-nextgen | bcbio/distributed/split.py | grouped_parallel_split_combine | def grouped_parallel_split_combine(args, split_fn, group_fn, parallel_fn,
parallel_name, combine_name,
file_key, combine_arg_keys,
split_outfile_i=-1):
"""Parallel split runner that allows grouping of samples du... | python | def grouped_parallel_split_combine(args, split_fn, group_fn, parallel_fn,
parallel_name, combine_name,
file_key, combine_arg_keys,
split_outfile_i=-1):
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bcbio/bcbio-nextgen | bcbio/distributed/split.py | parallel_split_combine | def parallel_split_combine(args, split_fn, parallel_fn,
parallel_name, combiner,
file_key, combine_arg_keys, split_outfile_i=-1):
"""Split, run split items in parallel then combine to output file.
split_fn: Split an input file into parts for processing. Ret... | python | def parallel_split_combine(args, split_fn, parallel_fn,
parallel_name, combiner,
file_key, combine_arg_keys, split_outfile_i=-1):
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bcbio/bcbio-nextgen | bcbio/distributed/split.py | _get_extra_args | def _get_extra_args(extra_args, arg_keys):
"""Retrieve extra arguments to pass along to combine function.
Special cases like reference files and configuration information
are passed as single items, the rest as lists mapping to each data
item combined.
"""
# XXX back compatible hack -- should h... | python | def _get_extra_args(extra_args, arg_keys):
"""Retrieve extra arguments to pass along to combine function.
Special cases like reference files and configuration information
are passed as single items, the rest as lists mapping to each data
item combined.
"""
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bcbio/bcbio-nextgen | bcbio/distributed/split.py | _organize_output | def _organize_output(output, combine_map, file_key, combine_arg_keys):
"""Combine output details for parallelization.
file_key is the key name of the output file used in merging. We extract
this file from the output data.
combine_arg_keys are extra items to pass along to the combine function.
"""
... | python | def _organize_output(output, combine_map, file_key, combine_arg_keys):
"""Combine output details for parallelization.
file_key is the key name of the output file used in merging. We extract
this file from the output data.
combine_arg_keys are extra items to pass along to the combine function.
"""
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bcbio/bcbio-nextgen | bcbio/distributed/split.py | _get_split_tasks | def _get_split_tasks(args, split_fn, file_key, outfile_i=-1):
"""Split up input files and arguments, returning arguments for parallel processing.
outfile_i specifies the location of the output file in the arguments to
the processing function. Defaults to the last item in the list.
"""
split_args = ... | python | def _get_split_tasks(args, split_fn, file_key, outfile_i=-1):
"""Split up input files and arguments, returning arguments for parallel processing.
outfile_i specifies the location of the output file in the arguments to
the processing function. Defaults to the last item in the list.
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split_args = ... | [
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bcbio/bcbio-nextgen | bcbio/ngsalign/snap.py | remap_index_fn | def remap_index_fn(ref_file):
"""Map sequence references to snap reference directory, using standard layout.
"""
snap_dir = os.path.join(os.path.dirname(ref_file), os.pardir, "snap")
assert os.path.exists(snap_dir) and os.path.isdir(snap_dir), snap_dir
return snap_dir | python | def remap_index_fn(ref_file):
"""Map sequence references to snap reference directory, using standard layout.
"""
snap_dir = os.path.join(os.path.dirname(ref_file), os.pardir, "snap")
assert os.path.exists(snap_dir) and os.path.isdir(snap_dir), snap_dir
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | use_general_sv_bins | 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):
... | python | 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):
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | bin_approach | 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(("-crs... | python | 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(("-crs... | [
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _cnvkit_by_type | def _cnvkit_by_type(items, background):
"""Dispatch to specific CNVkit functionality based on input type.
"""
if len(items + background) == 1:
return _run_cnvkit_single(items[0])
elif vcfutils.get_paired_phenotype(items[0]):
return _run_cnvkit_cancer(items, background)
else:
... | python | def _cnvkit_by_type(items, background):
"""Dispatch to specific CNVkit functionality based on input type.
"""
if len(items + background) == 1:
return _run_cnvkit_single(items[0])
elif vcfutils.get_paired_phenotype(items[0]):
return _run_cnvkit_cancer(items, background)
else:
... | [
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _associate_cnvkit_out | def _associate_cnvkit_out(ckouts, items, is_somatic=False):
"""Associate cnvkit output with individual items.
"""
assert len(ckouts) == len(items)
out = []
upload_counts = collections.defaultdict(int)
for ckout, data in zip(ckouts, items):
ckout = copy.deepcopy(ckout)
ckout["vari... | python | def _associate_cnvkit_out(ckouts, items, is_somatic=False):
"""Associate cnvkit output with individual items.
"""
assert len(ckouts) == len(items)
out = []
upload_counts = collections.defaultdict(int)
for ckout, data in zip(ckouts, items):
ckout = copy.deepcopy(ckout)
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _run_cnvkit_single | def _run_cnvkit_single(data, background=None):
"""Process a single input file with BAM or uniform background.
"""
if not background:
background = []
ckouts = _run_cnvkit_shared([data], background)
if not ckouts:
return [data]
else:
assert len(ckouts) == 1
return _... | python | def _run_cnvkit_single(data, background=None):
"""Process a single input file with BAM or uniform background.
"""
if not background:
background = []
ckouts = _run_cnvkit_shared([data], background)
if not ckouts:
return [data]
else:
assert len(ckouts) == 1
return _... | [
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _run_cnvkit_population | def _run_cnvkit_population(items, background):
"""Run CNVkit on a population of samples.
Tries to calculate background based on case/controls, otherwise
uses samples from the same batch as background.
"""
if background and len(background) > 0:
inputs = items
else:
inputs, backgr... | python | def _run_cnvkit_population(items, background):
"""Run CNVkit on a population of samples.
Tries to calculate background based on case/controls, otherwise
uses samples from the same batch as background.
"""
if background and len(background) > 0:
inputs = items
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _prep_cmd | def _prep_cmd(cmd, tx_out_file):
"""Wrap CNVkit commands ensuring we use local temporary directories.
"""
cmd = " ".join(cmd) if isinstance(cmd, (list, tuple)) else cmd
return "export TMPDIR=%s && %s" % (os.path.dirname(tx_out_file), cmd) | python | def _prep_cmd(cmd, tx_out_file):
"""Wrap CNVkit commands ensuring we use local temporary directories.
"""
cmd = " ".join(cmd) if isinstance(cmd, (list, tuple)) else cmd
return "export TMPDIR=%s && %s" % (os.path.dirname(tx_out_file), cmd) | [
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _bam_to_outbase | def _bam_to_outbase(bam_file, work_dir, data):
"""Convert an input BAM file into CNVkit expected output.
Handles previous non-batch cases to avoid re-calculating,
returning both new and old values:
"""
batch = dd.get_batch(data) or dd.get_sample_name(data)
out_base = os.path.splitext(os.path.ba... | python | def _bam_to_outbase(bam_file, work_dir, data):
"""Convert an input BAM file into CNVkit expected output.
Handles previous non-batch cases to avoid re-calculating,
returning both new and old values:
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batch = dd.get_batch(data) or dd.get_sample_name(data)
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _run_cnvkit_shared | def _run_cnvkit_shared(inputs, backgrounds):
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"""
if tz.get_in(["depth", "bins", "normalized"], inputs[0]):
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"""Shared functionality to run CNVkit, parallelizing over multiple BAM files.
Handles new style cases where we have pre-normalized inputs and
old cases where we run CNVkit individually.
"""
if tz.get_in(["depth", "bins", "normalized"], inputs[0]):
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _get_general_coverage | def _get_general_coverage(data, itype):
"""Retrieve coverage information from new shared SV bins.
"""
work_bam = dd.get_align_bam(data) or dd.get_work_bam(data)
return [{"bam": work_bam, "file": tz.get_in(["depth", "bins", "target"], data),
"cnntype": "target", "itype": itype, "sample": dd.... | python | def _get_general_coverage(data, itype):
"""Retrieve coverage information from new shared SV bins.
"""
work_bam = dd.get_align_bam(data) or dd.get_work_bam(data)
return [{"bam": work_bam, "file": tz.get_in(["depth", "bins", "target"], data),
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _cnvkit_segment | def _cnvkit_segment(cnr_file, cov_interval, data, items, out_file=None, detailed=False):
"""Perform segmentation and copy number calling on normalized inputs
"""
if not out_file:
out_file = "%s.cns" % os.path.splitext(cnr_file)[0]
if not utils.file_uptodate(out_file, cnr_file):
with file... | python | def _cnvkit_segment(cnr_file, cov_interval, data, items, out_file=None, detailed=False):
"""Perform segmentation and copy number calling on normalized inputs
"""
if not out_file:
out_file = "%s.cns" % os.path.splitext(cnr_file)[0]
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _cnvkit_metrics | def _cnvkit_metrics(cnns, target_bed, antitarget_bed, cov_interval, items):
"""Estimate noise of a sample using a flat background.
Only used for panel/targeted data due to memory issues with whole genome
samples.
"""
if cov_interval == "genome":
return cnns
target_cnn = [x["file"] for ... | python | def _cnvkit_metrics(cnns, target_bed, antitarget_bed, cov_interval, items):
"""Estimate noise of a sample using a flat background.
Only used for panel/targeted data due to memory issues with whole genome
samples.
"""
if cov_interval == "genome":
return cnns
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _cnvkit_fix | def _cnvkit_fix(cnns, background_cnn, items, ckouts):
"""Normalize samples, correcting sources of bias.
"""
return [_cnvkit_fix_base(cnns, background_cnn, items, ckouts)] | python | def _cnvkit_fix(cnns, background_cnn, items, ckouts):
"""Normalize samples, correcting sources of bias.
"""
return [_cnvkit_fix_base(cnns, background_cnn, items, ckouts)] | [
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _select_background_cnns | def _select_background_cnns(cnns):
"""Select cnns to use for background calculations.
Uses background samples in cohort, and will remove CNNs with high
on target variability. Uses (number of segments * biweight midvariance) as metric
for variability with higher numbers being more unreliable.
"""
... | python | def _select_background_cnns(cnns):
"""Select cnns to use for background calculations.
Uses background samples in cohort, and will remove CNNs with high
on target variability. Uses (number of segments * biweight midvariance) as metric
for variability with higher numbers being more unreliable.
"""
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | cnvkit_background | def cnvkit_background(background_cnns, out_file, items, target_bed=None, antitarget_bed=None):
"""Calculate background reference, handling flat case with no normal sample.
"""
if not utils.file_exists(out_file):
with file_transaction(items[0], out_file) as tx_out_file:
cmd = [_get_cmd(),... | python | def cnvkit_background(background_cnns, out_file, items, target_bed=None, antitarget_bed=None):
"""Calculate background reference, handling flat case with no normal sample.
"""
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _get_batch_gender | def _get_batch_gender(items):
"""Retrieve gender for a batch of items if consistent.
Better not to specify for mixed populations, CNVkit will work
it out
https://github.com/bcbio/bcbio-nextgen/commit/1a0e217c8a4d3cee10fa890fb3cfd4db5034281d#r26279752
"""
genders = set([population.get_gender(x) ... | python | def _get_batch_gender(items):
"""Retrieve gender for a batch of items if consistent.
Better not to specify for mixed populations, CNVkit will work
it out
https://github.com/bcbio/bcbio-nextgen/commit/1a0e217c8a4d3cee10fa890fb3cfd4db5034281d#r26279752
"""
genders = set([population.get_gender(x) ... | [
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | targets_w_bins | def targets_w_bins(cnv_file, access_file, target_anti_fn, work_dir, data):
"""Calculate target and anti-target files with pre-determined bins.
"""
target_file = os.path.join(work_dir, "%s-target.bed" % dd.get_sample_name(data))
anti_file = os.path.join(work_dir, "%s-antitarget.bed" % dd.get_sample_name(... | python | def targets_w_bins(cnv_file, access_file, target_anti_fn, work_dir, data):
"""Calculate target and anti-target files with pre-determined bins.
"""
target_file = os.path.join(work_dir, "%s-target.bed" % dd.get_sample_name(data))
anti_file = os.path.join(work_dir, "%s-antitarget.bed" % dd.get_sample_name(... | [
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | targets_from_background | def targets_from_background(back_cnn, work_dir, data):
"""Retrieve target and antitarget BEDs from background CNN file.
"""
target_file = os.path.join(work_dir, "%s.target.bed" % dd.get_sample_name(data))
anti_file = os.path.join(work_dir, "%s.antitarget.bed" % dd.get_sample_name(data))
if not utils... | python | def targets_from_background(back_cnn, work_dir, data):
"""Retrieve target and antitarget BEDs from background CNN file.
"""
target_file = os.path.join(work_dir, "%s.target.bed" % dd.get_sample_name(data))
anti_file = os.path.join(work_dir, "%s.antitarget.bed" % dd.get_sample_name(data))
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _add_seg_to_output | def _add_seg_to_output(out, data, enumerate_chroms=False):
"""Export outputs to 'seg' format compatible with IGV and GenePattern.
"""
out_file = "%s.seg" % os.path.splitext(out["cns"])[0]
if not utils.file_exists(out_file):
with file_transaction(data, out_file) as tx_out_file:
cmd = ... | python | def _add_seg_to_output(out, data, enumerate_chroms=False):
"""Export outputs to 'seg' format compatible with IGV and GenePattern.
"""
out_file = "%s.seg" % os.path.splitext(out["cns"])[0]
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _add_variantcalls_to_output | def _add_variantcalls_to_output(out, data, items, is_somatic=False):
"""Call ploidy and convert into VCF and BED representations.
"""
call_file = "%s-call%s" % os.path.splitext(out["cns"])
if not utils.file_exists(call_file):
with file_transaction(data, call_file) as tx_call_file:
fi... | python | def _add_variantcalls_to_output(out, data, items, is_somatic=False):
"""Call ploidy and convert into VCF and BED representations.
"""
call_file = "%s-call%s" % os.path.splitext(out["cns"])
if not utils.file_exists(call_file):
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _add_segmetrics_to_output | def _add_segmetrics_to_output(out, data):
"""Add metrics for measuring reliability of CNV estimates.
"""
out_file = "%s-segmetrics.txt" % os.path.splitext(out["cns"])[0]
if not utils.file_exists(out_file):
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cmd = [os.path.join(os.p... | python | def _add_segmetrics_to_output(out, data):
"""Add metrics for measuring reliability of CNV estimates.
"""
out_file = "%s-segmetrics.txt" % os.path.splitext(out["cns"])[0]
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _add_gainloss_to_output | def _add_gainloss_to_output(out, data):
"""Add gainloss based on genes, helpful for identifying changes in smaller genes.
"""
out_file = "%s-gainloss.txt" % os.path.splitext(out["cns"])[0]
if not utils.file_exists(out_file):
with file_transaction(data, out_file) as tx_out_file:
cmd =... | python | def _add_gainloss_to_output(out, data):
"""Add gainloss based on genes, helpful for identifying changes in smaller genes.
"""
out_file = "%s-gainloss.txt" % os.path.splitext(out["cns"])[0]
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _add_coverage_bedgraph_to_output | def _add_coverage_bedgraph_to_output(out, data):
"""Add BedGraph representation of coverage to the output
"""
out_file = "%s.coverage.bedgraph" % os.path.splitext(out["cns"])[0]
if utils.file_exists(out_file):
out["bedgraph"] = out_file
return out
bam_file = dd.get_align_bam(data)
... | python | def _add_coverage_bedgraph_to_output(out, data):
"""Add BedGraph representation of coverage to the output
"""
out_file = "%s.coverage.bedgraph" % os.path.splitext(out["cns"])[0]
if utils.file_exists(out_file):
out["bedgraph"] = out_file
return out
bam_file = dd.get_align_bam(data)
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _add_plots_to_output | def _add_plots_to_output(out, data):
"""Add CNVkit plots summarizing called copy number values.
"""
out["plot"] = {}
diagram_plot = _add_diagram_plot(out, data)
if diagram_plot:
out["plot"]["diagram"] = diagram_plot
scatter = _add_scatter_plot(out, data)
if scatter:
out["plot... | python | def _add_plots_to_output(out, data):
"""Add CNVkit plots summarizing called copy number values.
"""
out["plot"] = {}
diagram_plot = _add_diagram_plot(out, data)
if diagram_plot:
out["plot"]["diagram"] = diagram_plot
scatter = _add_scatter_plot(out, data)
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | _get_larger_chroms | def _get_larger_chroms(ref_file):
"""Retrieve larger chromosomes, avoiding the smaller ones for plotting.
"""
from scipy.cluster.vq import kmeans, vq
all_sizes = []
for c in ref.file_contigs(ref_file):
all_sizes.append(float(c.size))
all_sizes.sort()
if len(all_sizes) > 5:
# ... | python | def _get_larger_chroms(ref_file):
"""Retrieve larger chromosomes, avoiding the smaller ones for plotting.
"""
from scipy.cluster.vq import kmeans, vq
all_sizes = []
for c in ref.file_contigs(ref_file):
all_sizes.append(float(c.size))
all_sizes.sort()
if len(all_sizes) > 5:
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | segment_from_cnr | def segment_from_cnr(cnr_file, data, out_base):
"""Provide segmentation on a cnr file, used in external PureCN integration.
"""
cns_file = _cnvkit_segment(cnr_file, dd.get_coverage_interval(data),
data, [data], out_file="%s.cns" % out_base, detailed=True)
out = _add_seg_to... | python | def segment_from_cnr(cnr_file, data, out_base):
"""Provide segmentation on a cnr file, used in external PureCN integration.
"""
cns_file = _cnvkit_segment(cnr_file, dd.get_coverage_interval(data),
data, [data], out_file="%s.cns" % out_base, detailed=True)
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bcbio/bcbio-nextgen | bcbio/structural/cnvkit.py | export_theta | def export_theta(ckout, data):
"""Provide updated set of data with export information for TheTA2 input.
"""
cns_file = chromhacks.bed_to_standardonly(ckout["cns"], data, headers="chromosome")
cnr_file = chromhacks.bed_to_standardonly(ckout["cnr"], data, headers="chromosome")
out_file = "%s-theta.inp... | python | def export_theta(ckout, data):
"""Provide updated set of data with export information for TheTA2 input.
"""
cns_file = chromhacks.bed_to_standardonly(ckout["cns"], data, headers="chromosome")
cnr_file = chromhacks.bed_to_standardonly(ckout["cnr"], data, headers="chromosome")
out_file = "%s-theta.inp... | [
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bcbio/bcbio-nextgen | bcbio/rnaseq/stringtie.py | _stringtie_expression | def _stringtie_expression(bam, data, out_dir="."):
"""
only estimate expression the Stringtie, do not assemble new transcripts
"""
gtf_file = dd.get_gtf_file(data)
num_cores = dd.get_num_cores(data)
error_message = "The %s file for %s is missing. StringTie has an error."
stringtie = config_u... | python | def _stringtie_expression(bam, data, out_dir="."):
"""
only estimate expression the Stringtie, do not assemble new transcripts
"""
gtf_file = dd.get_gtf_file(data)
num_cores = dd.get_num_cores(data)
error_message = "The %s file for %s is missing. StringTie has an error."
stringtie = config_u... | [
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bcbio/bcbio-nextgen | bcbio/rnaseq/stringtie.py | run_stringtie_expression | def run_stringtie_expression(data):
"""
estimate expression from Stringtie, using the bcbio datadict
does not do transcriptome assembly
"""
bam = dd.get_work_bam(data)
sample_name = dd.get_sample_name(data)
out_dir = os.path.join("stringtie", sample_name)
isoform_fpkm = os.path.join(out_... | python | def run_stringtie_expression(data):
"""
estimate expression from Stringtie, using the bcbio datadict
does not do transcriptome assembly
"""
bam = dd.get_work_bam(data)
sample_name = dd.get_sample_name(data)
out_dir = os.path.join("stringtie", sample_name)
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bcbio/bcbio-nextgen | bcbio/upload/filesystem.py | update_file | def update_file(finfo, sample_info, config, pass_uptodate=False):
"""Update the file in local filesystem storage.
"""
storage_dir = utils.safe_makedir(_get_storage_dir(finfo, config))
if finfo.get("type") == "directory":
return _copy_finfo_directory(finfo, storage_dir)
else:
return _... | python | def update_file(finfo, sample_info, config, pass_uptodate=False):
"""Update the file in local filesystem storage.
"""
storage_dir = utils.safe_makedir(_get_storage_dir(finfo, config))
if finfo.get("type") == "directory":
return _copy_finfo_directory(finfo, storage_dir)
else:
return _... | [
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bcbio/bcbio-nextgen | bcbio/upload/filesystem.py | _copy_finfo | def _copy_finfo(finfo, storage_dir, pass_uptodate=False):
"""Copy a file into the output storage directory.
"""
out_file = _get_file_upload_path(finfo, storage_dir)
if not shared.up_to_date(out_file, finfo):
logger.info("Storing in local filesystem: %s" % out_file)
shutil.copy(finfo["pat... | python | def _copy_finfo(finfo, storage_dir, pass_uptodate=False):
"""Copy a file into the output storage directory.
"""
out_file = _get_file_upload_path(finfo, storage_dir)
if not shared.up_to_date(out_file, finfo):
logger.info("Storing in local filesystem: %s" % out_file)
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bcbio/bcbio-nextgen | bcbio/upload/filesystem.py | _copy_finfo_directory | def _copy_finfo_directory(finfo, out_dir):
"""Copy a directory into the final output directory.
"""
out_dir = _get_dir_upload_path(finfo, out_dir)
if not shared.up_to_date(out_dir, finfo):
logger.info("Storing directory in local filesystem: %s" % out_dir)
if os.path.exists(out_dir):
... | python | def _copy_finfo_directory(finfo, out_dir):
"""Copy a directory into the final output directory.
"""
out_dir = _get_dir_upload_path(finfo, out_dir)
if not shared.up_to_date(out_dir, finfo):
logger.info("Storing directory in local filesystem: %s" % out_dir)
if os.path.exists(out_dir):
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bcbio/bcbio-nextgen | bcbio/variation/naming.py | handle_synonyms | def handle_synonyms(in_file, ref_file, genome_build, work_dir, data):
"""Potentially handle remapping synonymous chromosome names between builds.
Handles tab delimited file formats like BED and VCF where the contig
is in the first column.
"""
if genome_build in GMAP and ref_file:
mappings =... | python | def handle_synonyms(in_file, ref_file, genome_build, work_dir, data):
"""Potentially handle remapping synonymous chromosome names between builds.
Handles tab delimited file formats like BED and VCF where the contig
is in the first column.
"""
if genome_build in GMAP and ref_file:
mappings =... | [
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bcbio/bcbio-nextgen | bcbio/variation/naming.py | _write_newname_file | def _write_newname_file(in_file, out_file, mappings):
"""Re-write an input file with contigs matching the correct reference.
"""
with utils.open_gzipsafe(in_file) as in_handle:
with open(out_file, "w") as out_handle:
for line in in_handle:
if line.startswith("#"):
... | python | def _write_newname_file(in_file, out_file, mappings):
"""Re-write an input file with contigs matching the correct reference.
"""
with utils.open_gzipsafe(in_file) as in_handle:
with open(out_file, "w") as out_handle:
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bcbio/bcbio-nextgen | bcbio/variation/naming.py | _matches_contigs | def _matches_contigs(in_file, contigs, checked_file):
"""Check if the contigs in the input file match the defined contigs in the reference genome.
"""
tocheck_contigs = 2
if utils.file_exists(checked_file):
with open(checked_file) as in_handle:
return in_handle.read().strip() == "mat... | python | def _matches_contigs(in_file, contigs, checked_file):
"""Check if the contigs in the input file match the defined contigs in the reference genome.
"""
tocheck_contigs = 2
if utils.file_exists(checked_file):
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bcbio/bcbio-nextgen | bcbio/ngsalign/novoalign.py | align_bam | def align_bam(in_bam, ref_file, names, align_dir, data):
"""Perform realignment of input BAM file; uses unix pipes for avoid IO.
"""
config = data["config"]
out_file = os.path.join(align_dir, "{0}-sort.bam".format(names["lane"]))
novoalign = config_utils.get_program("novoalign", config)
samtools... | python | def align_bam(in_bam, ref_file, names, align_dir, data):
"""Perform realignment of input BAM file; uses unix pipes for avoid IO.
"""
config = data["config"]
out_file = os.path.join(align_dir, "{0}-sort.bam".format(names["lane"]))
novoalign = config_utils.get_program("novoalign", config)
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bcbio/bcbio-nextgen | bcbio/ngsalign/novoalign.py | _novoalign_args_from_config | def _novoalign_args_from_config(config, need_quality=True):
"""Select novoalign options based on configuration parameters.
"""
if need_quality:
qual_format = config["algorithm"].get("quality_format", "").lower()
qual_flags = ["-F", "ILMFQ" if qual_format == "illumina" else "STDFQ"]
else:... | python | def _novoalign_args_from_config(config, need_quality=True):
"""Select novoalign options based on configuration parameters.
"""
if need_quality:
qual_format = config["algorithm"].get("quality_format", "").lower()
qual_flags = ["-F", "ILMFQ" if qual_format == "illumina" else "STDFQ"]
else:... | [
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bcbio/bcbio-nextgen | bcbio/ngsalign/novoalign.py | remap_index_fn | def remap_index_fn(ref_file):
"""Map sequence references to equivalent novoalign indexes.
"""
checks = [os.path.splitext(ref_file)[0].replace("/seq/", "/novoalign/"),
os.path.splitext(ref_file)[0] + ".ndx",
ref_file + ".bs.ndx",
ref_file + ".ndx"]
for check in c... | python | def remap_index_fn(ref_file):
"""Map sequence references to equivalent novoalign indexes.
"""
checks = [os.path.splitext(ref_file)[0].replace("/seq/", "/novoalign/"),
os.path.splitext(ref_file)[0] + ".ndx",
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bcbio/bcbio-nextgen | bcbio/variation/sentieon.py | license_export | def license_export(data):
"""Retrieve export statement for sentieon license server.
"""
resources = config_utils.get_resources("sentieon", data["config"])
server = resources.get("keyfile")
if not server:
server = tz.get_in(["resources", "sentieon", "keyfile"], data)
if not server:
... | python | def license_export(data):
"""Retrieve export statement for sentieon license server.
"""
resources = config_utils.get_resources("sentieon", data["config"])
server = resources.get("keyfile")
if not server:
server = tz.get_in(["resources", "sentieon", "keyfile"], data)
if not server:
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bcbio/bcbio-nextgen | bcbio/variation/sentieon.py | _get_interval | def _get_interval(variant_regions, region, out_file, items):
"""Retrieve interval to run analysis in. Handles no targets, BED and regions
region can be a single region or list of multiple regions for multicore calling.
"""
target = shared.subset_variant_regions(variant_regions, region, out_file, items)... | python | def _get_interval(variant_regions, region, out_file, items):
"""Retrieve interval to run analysis in. Handles no targets, BED and regions
region can be a single region or list of multiple regions for multicore calling.
"""
target = shared.subset_variant_regions(variant_regions, region, out_file, items)... | [
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bcbio/bcbio-nextgen | bcbio/variation/sentieon.py | run_tnscope | def run_tnscope(align_bams, items, ref_file, assoc_files,
region=None, out_file=None):
"""Call variants with Sentieon's TNscope somatic caller.
"""
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)... | python | def run_tnscope(align_bams, items, ref_file, assoc_files,
region=None, out_file=None):
"""Call variants with Sentieon's TNscope somatic caller.
"""
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)... | [
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bcbio/bcbio-nextgen | bcbio/variation/sentieon.py | run_gvcftyper | def run_gvcftyper(vrn_files, out_file, region, data):
"""Produce joint called variants from input gVCF files.
"""
if not utils.file_exists(out_file):
with file_transaction(data, out_file) as tx_out_file:
license = license_export(data)
ref_file = dd.get_ref_file(data)
... | python | def run_gvcftyper(vrn_files, out_file, region, data):
"""Produce joint called variants from input gVCF files.
"""
if not utils.file_exists(out_file):
with file_transaction(data, out_file) as tx_out_file:
license = license_export(data)
ref_file = dd.get_ref_file(data)
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bcbio/bcbio-nextgen | bcbio/variation/sentieon.py | bqsr_table | def bqsr_table(data):
"""Generate recalibration tables as inputs to BQSR.
"""
in_file = dd.get_align_bam(data)
out_file = "%s-recal-table.txt" % utils.splitext_plus(in_file)[0]
if not utils.file_uptodate(out_file, in_file):
with file_transaction(data, out_file) as tx_out_file:
as... | python | def bqsr_table(data):
"""Generate recalibration tables as inputs to BQSR.
"""
in_file = dd.get_align_bam(data)
out_file = "%s-recal-table.txt" % utils.splitext_plus(in_file)[0]
if not utils.file_uptodate(out_file, in_file):
with file_transaction(data, out_file) as tx_out_file:
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bcbio/bcbio-nextgen | bcbio/ngsalign/rtg.py | to_sdf | def to_sdf(files, data):
"""Convert a fastq or BAM input into a SDF indexed file.
"""
# BAM
if len(files) == 1 and files[0].endswith(".bam"):
qual = []
format = ["-f", "sam-pe" if bam.is_paired(files[0]) else "sam-se"]
inputs = [files[0]]
# fastq
else:
qual = ["-q... | python | def to_sdf(files, data):
"""Convert a fastq or BAM input into a SDF indexed file.
"""
# BAM
if len(files) == 1 and files[0].endswith(".bam"):
qual = []
format = ["-f", "sam-pe" if bam.is_paired(files[0]) else "sam-se"]
inputs = [files[0]]
# fastq
else:
qual = ["-q... | [
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bcbio/bcbio-nextgen | bcbio/ngsalign/rtg.py | to_fastq_apipe_cl | def to_fastq_apipe_cl(sdf_file, start=None, end=None):
"""Return a command lines to provide streaming fastq input.
For paired end, returns a forward and reverse command line. For
single end returns a single command line and None for the pair.
"""
cmd = ["rtg", "sdf2fastq", "--no-gzip", "-o", "-"]
... | python | def to_fastq_apipe_cl(sdf_file, start=None, end=None):
"""Return a command lines to provide streaming fastq input.
For paired end, returns a forward and reverse command line. For
single end returns a single command line and None for the pair.
"""
cmd = ["rtg", "sdf2fastq", "--no-gzip", "-o", "-"]
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bcbio/bcbio-nextgen | bcbio/pipeline/tools.py | get_tabix_cmd | def get_tabix_cmd(config):
"""Retrieve tabix command, handling new bcftools tabix and older tabix.
"""
try:
bcftools = config_utils.get_program("bcftools", config)
# bcftools has terrible error codes and stderr output, swallow those.
bcftools_tabix = subprocess.check_output("{bcftool... | python | def get_tabix_cmd(config):
"""Retrieve tabix command, handling new bcftools tabix and older tabix.
"""
try:
bcftools = config_utils.get_program("bcftools", config)
# bcftools has terrible error codes and stderr output, swallow those.
bcftools_tabix = subprocess.check_output("{bcftool... | [
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bcbio/bcbio-nextgen | bcbio/pipeline/tools.py | get_bgzip_cmd | def get_bgzip_cmd(config, is_retry=False):
"""Retrieve command to use for bgzip, trying to use bgzip parallel threads.
By default, parallel bgzip is enabled in bcbio. If it causes problems
please report them. You can turn parallel bgzip off with `tools_off: [pbgzip]`
"""
num_cores = tz.get_in(["alg... | python | def get_bgzip_cmd(config, is_retry=False):
"""Retrieve command to use for bgzip, trying to use bgzip parallel threads.
By default, parallel bgzip is enabled in bcbio. If it causes problems
please report them. You can turn parallel bgzip off with `tools_off: [pbgzip]`
"""
num_cores = tz.get_in(["alg... | [
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | is_empty | def is_empty(bam_file):
"""Determine if a BAM file is empty
"""
bam_file = objectstore.cl_input(bam_file)
cmd = ("set -o pipefail; "
"samtools view {bam_file} | head -1 | wc -l")
p = subprocess.Popen(cmd.format(**locals()), shell=True,
executable=do.find_bash(),
... | python | def is_empty(bam_file):
"""Determine if a BAM file is empty
"""
bam_file = objectstore.cl_input(bam_file)
cmd = ("set -o pipefail; "
"samtools view {bam_file} | head -1 | wc -l")
p = subprocess.Popen(cmd.format(**locals()), shell=True,
executable=do.find_bash(),
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | fake_index | def fake_index(in_bam, data):
"""Create a fake index file for namesorted BAMs. bais require by CWL for consistency.
"""
index_file = "%s.bai" % in_bam
if not utils.file_exists(index_file):
with file_transaction(data, index_file) as tx_out_file:
with open(tx_out_file, "w") as out_hand... | python | def fake_index(in_bam, data):
"""Create a fake index file for namesorted BAMs. bais require by CWL for consistency.
"""
index_file = "%s.bai" % in_bam
if not utils.file_exists(index_file):
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | index | def index(in_bam, config, check_timestamp=True):
"""Index a BAM file, skipping if index present.
Centralizes BAM indexing providing ability to switch indexing approaches.
"""
assert is_bam(in_bam), "%s in not a BAM file" % in_bam
index_file = "%s.bai" % in_bam
alt_index_file = "%s.bai" % os.pat... | python | def index(in_bam, config, check_timestamp=True):
"""Index a BAM file, skipping if index present.
Centralizes BAM indexing providing ability to switch indexing approaches.
"""
assert is_bam(in_bam), "%s in not a BAM file" % in_bam
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | remove | def remove(in_bam):
"""
remove bam file and the index if exists
"""
if utils.file_exists(in_bam):
utils.remove_safe(in_bam)
if utils.file_exists(in_bam + ".bai"):
utils.remove_safe(in_bam + ".bai") | python | def remove(in_bam):
"""
remove bam file and the index if exists
"""
if utils.file_exists(in_bam):
utils.remove_safe(in_bam)
if utils.file_exists(in_bam + ".bai"):
utils.remove_safe(in_bam + ".bai") | [
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | idxstats | def idxstats(in_bam, data):
"""Return BAM index stats for the given file, using samtools idxstats.
"""
index(in_bam, data["config"], check_timestamp=False)
AlignInfo = collections.namedtuple("AlignInfo", ["contig", "length", "aligned", "unaligned"])
samtools = config_utils.get_program("samtools", da... | python | def idxstats(in_bam, data):
"""Return BAM index stats for the given file, using samtools idxstats.
"""
index(in_bam, data["config"], check_timestamp=False)
AlignInfo = collections.namedtuple("AlignInfo", ["contig", "length", "aligned", "unaligned"])
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | fai_from_bam | def fai_from_bam(ref_file, bam_file, out_file, data):
"""Create a fai index with only contigs in the input BAM file.
"""
contigs = set([x.contig for x in idxstats(bam_file, data)])
if not utils.file_uptodate(out_file, bam_file):
with open(ref.fasta_idx(ref_file, data["config"])) as in_handle:
... | python | def fai_from_bam(ref_file, bam_file, out_file, data):
"""Create a fai index with only contigs in the input BAM file.
"""
contigs = set([x.contig for x in idxstats(bam_file, data)])
if not utils.file_uptodate(out_file, bam_file):
with open(ref.fasta_idx(ref_file, data["config"])) as in_handle:
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | ref_file_from_bam | def ref_file_from_bam(bam_file, data):
"""Subset a fasta input file to only a fraction of input contigs.
"""
new_ref = os.path.join(utils.safe_makedir(os.path.join(dd.get_work_dir(data), "inputs", "ref")),
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if not utils.file_exists(ne... | python | def ref_file_from_bam(bam_file, data):
"""Subset a fasta input file to only a fraction of input contigs.
"""
new_ref = os.path.join(utils.safe_makedir(os.path.join(dd.get_work_dir(data), "inputs", "ref")),
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | get_downsample_pct | def get_downsample_pct(in_bam, target_counts, data):
"""Retrieve percentage of file to downsample to get to target counts.
Avoids minimal downsample which is not especially useful for
improving QC times; 90& or more of reads.
"""
total = sum(x.aligned for x in idxstats(in_bam, data))
with pysam... | python | def get_downsample_pct(in_bam, target_counts, data):
"""Retrieve percentage of file to downsample to get to target counts.
Avoids minimal downsample which is not especially useful for
improving QC times; 90& or more of reads.
"""
total = sum(x.aligned for x in idxstats(in_bam, data))
with pysam... | [
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | downsample | def downsample(in_bam, data, target_counts, work_dir=None):
"""Downsample a BAM file to the specified number of target counts.
"""
index(in_bam, data["config"], check_timestamp=False)
ds_pct = get_downsample_pct(in_bam, target_counts, data)
if ds_pct:
out_file = "%s-downsample%s" % os.path.s... | python | def downsample(in_bam, data, target_counts, work_dir=None):
"""Downsample a BAM file to the specified number of target counts.
"""
index(in_bam, data["config"], check_timestamp=False)
ds_pct = get_downsample_pct(in_bam, target_counts, data)
if ds_pct:
out_file = "%s-downsample%s" % os.path.s... | [
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | get_maxcov_downsample_cl | def get_maxcov_downsample_cl(data, in_pipe=None):
"""Retrieve command line for max coverage downsampling, fitting into bamsormadup output.
"""
max_cov = _get_maxcov_downsample(data) if dd.get_aligner(data) not in ["snap"] else None
if max_cov:
if in_pipe == "bamsormadup":
prefix = "l... | python | def get_maxcov_downsample_cl(data, in_pipe=None):
"""Retrieve command line for max coverage downsampling, fitting into bamsormadup output.
"""
max_cov = _get_maxcov_downsample(data) if dd.get_aligner(data) not in ["snap"] else None
if max_cov:
if in_pipe == "bamsormadup":
prefix = "l... | [
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | _get_maxcov_downsample | def _get_maxcov_downsample(data):
"""Calculate maximum coverage downsampling for whole genome samples.
Returns None if we're not doing downsampling.
"""
from bcbio.bam import ref
from bcbio.ngsalign import alignprep, bwa
from bcbio.variation import coverage
fastq_file = data["files"][0]
... | python | def _get_maxcov_downsample(data):
"""Calculate maximum coverage downsampling for whole genome samples.
Returns None if we're not doing downsampling.
"""
from bcbio.bam import ref
from bcbio.ngsalign import alignprep, bwa
from bcbio.variation import coverage
fastq_file = data["files"][0]
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | check_header | def check_header(in_bam, rgnames, ref_file, config):
"""Ensure passed in BAM header matches reference file and read groups names.
"""
_check_bam_contigs(in_bam, ref_file, config)
_check_sample(in_bam, rgnames) | python | def check_header(in_bam, rgnames, ref_file, config):
"""Ensure passed in BAM header matches reference file and read groups names.
"""
_check_bam_contigs(in_bam, ref_file, config)
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | _check_sample | def _check_sample(in_bam, rgnames):
"""Ensure input sample name matches expected run group names.
"""
with pysam.Samfile(in_bam, "rb") as bamfile:
rg = bamfile.header.get("RG", [{}])
msgs = []
warnings = []
if len(rg) > 1:
warnings.append("Multiple read groups found in input BAM.... | python | def _check_sample(in_bam, rgnames):
"""Ensure input sample name matches expected run group names.
"""
with pysam.Samfile(in_bam, "rb") as bamfile:
rg = bamfile.header.get("RG", [{}])
msgs = []
warnings = []
if len(rg) > 1:
warnings.append("Multiple read groups found in input BAM.... | [
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | _check_bam_contigs | def _check_bam_contigs(in_bam, ref_file, config):
"""Ensure a pre-aligned BAM file matches the expected reference genome.
"""
# GATK allows chromosome M to be in multiple locations, skip checking it
allowed_outoforder = ["chrM", "MT"]
ref_contigs = [c.name for c in ref.file_contigs(ref_file, config)... | python | def _check_bam_contigs(in_bam, ref_file, config):
"""Ensure a pre-aligned BAM file matches the expected reference genome.
"""
# GATK allows chromosome M to be in multiple locations, skip checking it
allowed_outoforder = ["chrM", "MT"]
ref_contigs = [c.name for c in ref.file_contigs(ref_file, config)... | [
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | sort | def sort(in_bam, config, order="coordinate", out_dir=None):
"""Sort a BAM file, skipping if already present.
"""
assert is_bam(in_bam), "%s in not a BAM file" % in_bam
if bam_already_sorted(in_bam, config, order):
return in_bam
sort_stem = _get_sort_stem(in_bam, order, out_dir)
sort_fil... | python | def sort(in_bam, config, order="coordinate", out_dir=None):
"""Sort a BAM file, skipping if already present.
"""
assert is_bam(in_bam), "%s in not a BAM file" % in_bam
if bam_already_sorted(in_bam, config, order):
return in_bam
sort_stem = _get_sort_stem(in_bam, order, out_dir)
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | aligner_from_header | def aligner_from_header(in_bam):
"""Identify aligner from the BAM header; handling pre-aligned inputs.
"""
from bcbio.pipeline.alignment import TOOLS
with pysam.Samfile(in_bam, "rb") as bamfile:
for pg in bamfile.header.get("PG", []):
for ka in TOOLS.keys():
if pg.get... | python | def aligner_from_header(in_bam):
"""Identify aligner from the BAM header; handling pre-aligned inputs.
"""
from bcbio.pipeline.alignment import TOOLS
with pysam.Samfile(in_bam, "rb") as bamfile:
for pg in bamfile.header.get("PG", []):
for ka in TOOLS.keys():
if pg.get... | [
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | sample_name | def sample_name(in_bam):
"""Get sample name from BAM file.
"""
with pysam.AlignmentFile(in_bam, "rb", check_sq=False) as in_pysam:
try:
if "RG" in in_pysam.header:
return in_pysam.header["RG"][0]["SM"]
except ValueError:
return None | python | def sample_name(in_bam):
"""Get sample name from BAM file.
"""
with pysam.AlignmentFile(in_bam, "rb", check_sq=False) as in_pysam:
try:
if "RG" in in_pysam.header:
return in_pysam.header["RG"][0]["SM"]
except ValueError:
return None | [
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | filter_primary | def filter_primary(bam_file, data):
"""Filter reads to primary only BAM.
Removes:
- not primary alignment (0x100) 256
- supplementary alignment (0x800) 2048
"""
stem, ext = os.path.splitext(bam_file)
out_file = stem + ".primary" + ext
if not utils.file_exists(out_file):
with... | python | def filter_primary(bam_file, data):
"""Filter reads to primary only BAM.
Removes:
- not primary alignment (0x100) 256
- supplementary alignment (0x800) 2048
"""
stem, ext = os.path.splitext(bam_file)
out_file = stem + ".primary" + ext
if not utils.file_exists(out_file):
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | estimate_max_mapq | def estimate_max_mapq(in_bam, nreads=1e6):
"""Guess maximum MAPQ in a BAM file of reads with alignments
"""
with pysam.Samfile(in_bam, "rb") as work_bam:
reads = tz.take(int(nreads), work_bam)
return max([x.mapq for x in reads if not x.is_unmapped]) | python | def estimate_max_mapq(in_bam, nreads=1e6):
"""Guess maximum MAPQ in a BAM file of reads with alignments
"""
with pysam.Samfile(in_bam, "rb") as work_bam:
reads = tz.take(int(nreads), work_bam)
return max([x.mapq for x in reads if not x.is_unmapped]) | [
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bcbio/bcbio-nextgen | bcbio/bam/__init__.py | convert_cufflinks_mapq | def convert_cufflinks_mapq(in_bam, out_bam=None):
"""Cufflinks expects the not-valid 255 MAPQ for uniquely mapped reads.
This detects the maximum mapping quality in a BAM file and sets
reads with that quality to be 255
"""
CUFFLINKSMAPQ = 255
if not out_bam:
out_bam = os.path.splitext(in... | python | def convert_cufflinks_mapq(in_bam, out_bam=None):
"""Cufflinks expects the not-valid 255 MAPQ for uniquely mapped reads.
This detects the maximum mapping quality in a BAM file and sets
reads with that quality to be 255
"""
CUFFLINKSMAPQ = 255
if not out_bam:
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bcbio/bcbio-nextgen | bcbio/variation/annotation.py | get_gatk_annotations | def get_gatk_annotations(config, include_depth=True, include_baseqranksum=True,
gatk_input=True):
"""Retrieve annotations to use for GATK VariantAnnotator.
If include_depth is false, we'll skip annotating DP. Since GATK downsamples
this will undercount on high depth sequencing and ... | python | def get_gatk_annotations(config, include_depth=True, include_baseqranksum=True,
gatk_input=True):
"""Retrieve annotations to use for GATK VariantAnnotator.
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bcbio/bcbio-nextgen | bcbio/variation/annotation.py | finalize_vcf | def finalize_vcf(in_file, variantcaller, items):
"""Perform cleanup and dbSNP annotation of the final VCF.
- Adds contigs to header for bcftools compatibility
- adds sample information for tumor/normal
"""
out_file = "%s-annotated%s" % utils.splitext_plus(in_file)
if not utils.file_uptodate(out... | python | def finalize_vcf(in_file, variantcaller, items):
"""Perform cleanup and dbSNP annotation of the final VCF.
- Adds contigs to header for bcftools compatibility
- adds sample information for tumor/normal
"""
out_file = "%s-annotated%s" % utils.splitext_plus(in_file)
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bcbio/bcbio-nextgen | bcbio/variation/annotation.py | _add_vcf_header_sample_cl | def _add_vcf_header_sample_cl(in_file, items, base_file):
"""Add phenotype information to a VCF header.
Encode tumor/normal relationships in VCF header.
Could also eventually handle more complicated pedigree information if useful.
"""
paired = vcfutils.get_paired(items)
if paired:
toadd... | python | def _add_vcf_header_sample_cl(in_file, items, base_file):
"""Add phenotype information to a VCF header.
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bcbio/bcbio-nextgen | bcbio/variation/annotation.py | _update_header | def _update_header(orig_vcf, base_file, new_lines, chrom_process_fn=None):
"""Fix header with additional lines and remapping of generic sample names.
"""
new_header = "%s-sample_header.txt" % utils.splitext_plus(base_file)[0]
with open(new_header, "w") as out_handle:
chrom_line = None
wi... | python | def _update_header(orig_vcf, base_file, new_lines, chrom_process_fn=None):
"""Fix header with additional lines and remapping of generic sample names.
"""
new_header = "%s-sample_header.txt" % utils.splitext_plus(base_file)[0]
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bcbio/bcbio-nextgen | bcbio/variation/annotation.py | _add_dbsnp | def _add_dbsnp(orig_file, dbsnp_file, data, out_file=None, post_cl=None):
"""Annotate a VCF file with dbSNP.
vcfanno has flexible matching for NON_REF gVCF positions, matching
at position and REF allele, matching ALT NON_REF as a wildcard.
"""
orig_file = vcfutils.bgzip_and_index(orig_file, data["c... | python | def _add_dbsnp(orig_file, dbsnp_file, data, out_file=None, post_cl=None):
"""Annotate a VCF file with dbSNP.
vcfanno has flexible matching for NON_REF gVCF positions, matching
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bcbio/bcbio-nextgen | bcbio/variation/annotation.py | get_context_files | def get_context_files(data):
"""Retrieve pre-installed annotation files for annotating genome context.
"""
ref_file = dd.get_ref_file(data)
all_files = []
for ext in [".bed.gz"]:
all_files += sorted(glob.glob(os.path.normpath(os.path.join(os.path.dirname(ref_file), os.pardir,
... | python | def get_context_files(data):
"""Retrieve pre-installed annotation files for annotating genome context.
"""
ref_file = dd.get_ref_file(data)
all_files = []
for ext in [".bed.gz"]:
all_files += sorted(glob.glob(os.path.normpath(os.path.join(os.path.dirname(ref_file), os.pardir,
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bcbio/bcbio-nextgen | bcbio/variation/annotation.py | add_genome_context | def add_genome_context(orig_file, data):
"""Annotate a file with annotations of genome context using vcfanno.
"""
out_file = "%s-context.vcf.gz" % utils.splitext_plus(orig_file)[0]
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with file_transaction(data, out_file) as tx_out_file:
... | python | def add_genome_context(orig_file, data):
"""Annotate a file with annotations of genome context using vcfanno.
"""
out_file = "%s-context.vcf.gz" % utils.splitext_plus(orig_file)[0]
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bcbio/bcbio-nextgen | bcbio/illumina/demultiplex.py | _submit_and_wait | def _submit_and_wait(cmd, cores, config, output_dir):
"""Submit command with batch script specified in configuration, wait until finished
"""
batch_script = "submit_bcl2fastq.sh"
if not os.path.exists(batch_script + ".finished"):
if os.path.exists(batch_script + ".failed"):
os.remove... | python | def _submit_and_wait(cmd, cores, config, output_dir):
"""Submit command with batch script specified in configuration, wait until finished
"""
batch_script = "submit_bcl2fastq.sh"
if not os.path.exists(batch_script + ".finished"):
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bcbio/bcbio-nextgen | bcbio/workflow/template.py | _prep_items_from_base | def _prep_items_from_base(base, in_files, metadata, separators, force_single=False):
"""Prepare a set of configuration items for input files.
"""
details = []
in_files = _expand_dirs(in_files, KNOWN_EXTS)
in_files = _expand_wildcards(in_files)
ext_groups = collections.defaultdict(list)
for ... | python | def _prep_items_from_base(base, in_files, metadata, separators, force_single=False):
"""Prepare a set of configuration items for input files.
"""
details = []
in_files = _expand_dirs(in_files, KNOWN_EXTS)
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bcbio/bcbio-nextgen | bcbio/workflow/template.py | _find_glob_matches | def _find_glob_matches(in_files, metadata):
"""Group files that match by globs for merging, rather than by explicit pairs.
"""
reg_files = copy.deepcopy(in_files)
glob_files = []
for glob_search in [x for x in metadata.keys() if "*" in x]:
cur = []
for fname in in_files:
... | python | def _find_glob_matches(in_files, metadata):
"""Group files that match by globs for merging, rather than by explicit pairs.
"""
reg_files = copy.deepcopy(in_files)
glob_files = []
for glob_search in [x for x in metadata.keys() if "*" in x]:
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bcbio/bcbio-nextgen | bcbio/workflow/template.py | name_to_config | def name_to_config(template):
"""Read template file into a dictionary to use as base for all samples.
Handles well-known template names, pulled from GitHub repository and local
files.
"""
if objectstore.is_remote(template):
with objectstore.open_file(template) as in_handle:
conf... | python | def name_to_config(template):
"""Read template file into a dictionary to use as base for all samples.
Handles well-known template names, pulled from GitHub repository and local
files.
"""
if objectstore.is_remote(template):
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bcbio/bcbio-nextgen | bcbio/workflow/template.py | _write_config_file | def _write_config_file(items, global_vars, template, project_name, out_dir,
remotes):
"""Write configuration file, adding required top level attributes.
"""
config_dir = utils.safe_makedir(os.path.join(out_dir, "config"))
out_config_file = os.path.join(config_dir, "%s.yaml" % proj... | python | def _write_config_file(items, global_vars, template, project_name, out_dir,
remotes):
"""Write configuration file, adding required top level attributes.
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config_dir = utils.safe_makedir(os.path.join(out_dir, "config"))
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bcbio/bcbio-nextgen | bcbio/workflow/template.py | _set_global_vars | def _set_global_vars(metadata):
"""Identify files used multiple times in metadata and replace with global variables
"""
fnames = collections.defaultdict(list)
for sample in metadata.keys():
for k, v in metadata[sample].items():
if isinstance(v, six.string_types) and os.path.isfile(v)... | python | def _set_global_vars(metadata):
"""Identify files used multiple times in metadata and replace with global variables
"""
fnames = collections.defaultdict(list)
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bcbio/bcbio-nextgen | bcbio/workflow/template.py | _clean_string | def _clean_string(v, sinfo):
"""Test for and clean unicode present in template CSVs.
"""
if isinstance(v, (list, tuple)):
return [_clean_string(x, sinfo) for x in v]
else:
assert isinstance(v, six.string_types), v
try:
if hasattr(v, "decode"):
return s... | python | def _clean_string(v, sinfo):
"""Test for and clean unicode present in template CSVs.
"""
if isinstance(v, (list, tuple)):
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bcbio/bcbio-nextgen | bcbio/workflow/template.py | _parse_metadata | def _parse_metadata(in_handle):
"""Reads metadata from a simple CSV structured input file.
samplename,batch,phenotype
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"""
metadata = {}
reader = csv.reader(in_handle)
while 1:
header = next(reader)
if not header[0].startswith("#"):
break
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"""Reads metadata from a simple CSV structured input file.
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metadata = {}
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] | 6a9348c0054ccd5baffd22f1bb7d0422f6978b20 | https://github.com/bcbio/bcbio-nextgen/blob/6a9348c0054ccd5baffd22f1bb7d0422f6978b20/bcbio/workflow/template.py#L279-L308 | train |
bcbio/bcbio-nextgen | bcbio/workflow/template.py | _pname_and_metadata | def _pname_and_metadata(in_file):
"""Retrieve metadata and project name from the input metadata CSV file.
Uses the input file name for the project name and for back compatibility,
accepts the project name as an input, providing no metadata.
"""
if os.path.isfile(in_file):
with open(in_file)... | python | def _pname_and_metadata(in_file):
"""Retrieve metadata and project name from the input metadata CSV file.
Uses the input file name for the project name and for back compatibility,
accepts the project name as an input, providing no metadata.
"""
if os.path.isfile(in_file):
with open(in_file)... | [
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Uses the input file name for the project name and for back compatibility,
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] | 6a9348c0054ccd5baffd22f1bb7d0422f6978b20 | https://github.com/bcbio/bcbio-nextgen/blob/6a9348c0054ccd5baffd22f1bb7d0422f6978b20/bcbio/workflow/template.py#L318-L339 | train |
bcbio/bcbio-nextgen | bcbio/workflow/template.py | _handle_special_yaml_cases | def _handle_special_yaml_cases(v):
"""Handle values that pass integer, boolean, list or dictionary values.
"""
if "::" in v:
out = {}
for part in v.split("::"):
k_part, v_part = part.split(":")
out[k_part] = v_part.split(";")
v = out
elif ";" in v:
... | python | def _handle_special_yaml_cases(v):
"""Handle values that pass integer, boolean, list or dictionary values.
"""
if "::" in v:
out = {}
for part in v.split("::"):
k_part, v_part = part.split(":")
out[k_part] = v_part.split(";")
v = out
elif ";" in v:
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