def summarize_vc(items):
"""CWL target: summarize variant calls and validation for multiple samples.
"""
items = [
utils.to_single_data(x) for x in validate.summarize_grading(items)
]
out = {"validate": items[0]["validate"], "variants": {"calls": []}}
added = set([])
for data in items:
if data.get("vrn_file"):
names = dd.get_batches(data)
if not names:
names = [dd.get_sample_name(data)]
cur_name = "%s-%s" % (names[0], dd.get_variantcaller(data))
if cur_name not in added:
out_file = os.path.join(
utils.safe_makedir(
os.path.join(dd.get_work_dir(data), "variants",
"calls")), "%s.vcf.gz" % cur_name)
added.add(cur_name)
# Ideally could symlink here but doesn't appear to work with
# Docker container runs on Toil where PATHs don't get remapped
utils.copy_plus(os.path.realpath(data["vrn_file"]), out_file)
vcfutils.bgzip_and_index(out_file, data["config"])
out["variants"]["calls"].append(out_file)
return [out]
def main(cosmic_version, bcbio_genome_dir):
work_dir = utils.safe_makedir(os.path.join(os.getcwd(), "cosmic-prep"))
os.chdir(work_dir)
for genome_build, bcbio_build, add_chr in [("GRCh37", "GRCh37", False), ("GRCh38", "hg38", True)]:
bcbio_base = os.path.join(bcbio_genome_dir, "genomes", "Hsapiens", bcbio_build)
if not os.path.exists(bcbio_base):
continue
bcbio_ref = os.path.join(bcbio_base, "seq", "%s.fa" % bcbio_build)
sorted_inputs = []
for fname in get_cosmic_files(genome_build, cosmic_version):
sorted_inputs.append(sort_to_ref(fname, bcbio_ref, add_chr=add_chr))
out_dir = utils.safe_makedir(os.path.join("v%s" % cosmic_version, "bcbio_ready", bcbio_build))
out_file = os.path.join(out_dir, "cosmic.vcf.gz")
ready_cosmic = combine_cosmic(sorted_inputs, bcbio_ref, out_file)
variation_dir = utils.safe_makedir(os.path.join(bcbio_base, "variation"))
utils.copy_plus(ready_cosmic, os.path.join(variation_dir, os.path.basename(ready_cosmic)))
print("Created COSMIC v%s resource in %s" % (cosmic_version,
os.path.join(variation_dir, os.path.basename(ready_cosmic))))
if bcbio_build == "GRCh37":
bcbio_base = os.path.join(bcbio_genome_dir, "genomes", "Hsapiens", "hg19")
if not os.path.exists(bcbio_base):
continue
out_dir = utils.safe_makedir(os.path.join("v%s" % cosmic_version, "bcbio_ready", "hg19"))
out_file = os.path.join(out_dir, "cosmic.vcf.gz")
hg19_cosmic = map_coords_to_ucsc(ready_cosmic, bcbio_ref, out_file)
variation_dir = utils.safe_makedir(os.path.join(bcbio_base, "variation"))
utils.copy_plus(hg19_cosmic, os.path.join(variation_dir, os.path.basename(hg19_cosmic)))
print("Created COSMIC v%s resource in %s" % (cosmic_version,
os.path.join(variation_dir, os.path.basename(hg19_cosmic))))
def summarize_vc(items):
"""CWL target: summarize variant calls and validation for multiple samples.
"""
items = [utils.to_single_data(x) for x in validate.summarize_grading(items)]
out = {"validate": items[0]["validate"],
"variants": {"calls": [], "gvcf": []}}
added = set([])
for data in items:
if data.get("vrn_file"):
names = dd.get_batches(data)
if not names:
names = [dd.get_sample_name(data)]
batch_name = names[0]
if data.get("vrn_file_joint") is not None:
to_add = [("vrn_file", "gvcf", dd.get_sample_name(data)),
("vrn_file_joint", "calls", batch_name)]
else:
to_add = [("vrn_file", "calls", batch_name)]
for vrn_key, out_key, name in to_add:
cur_name = "%s-%s" % (name, dd.get_variantcaller(data))
if cur_name not in added:
out_file = os.path.join(utils.safe_makedir(os.path.join(dd.get_work_dir(data),
"variants", out_key)),
"%s.vcf.gz" % cur_name)
added.add(cur_name)
# Ideally could symlink here but doesn't appear to work with
# Docker container runs on Toil where PATHs don't get remapped
utils.copy_plus(os.path.realpath(data[vrn_key]), out_file)
vcfutils.bgzip_and_index(out_file, data["config"])
out["variants"][out_key].append(out_file)
return [out]
def main(cosmic_version, bcbio_genome_dir, overwrite=False, clean=False):
work_dir = utils.safe_makedir(os.path.join(os.getcwd(), "cosmic-prep"))
os.chdir(work_dir)
for genome_build, bcbio_build, add_chr in [("GRCh37", "GRCh37", False), ("GRCh38", "hg38", True)]:
bcbio_base = os.path.join(bcbio_genome_dir, "genomes", "Hsapiens", bcbio_build)
installed_file = os.path.join(bcbio_base, "variation", f"cosmic-v{cosmic_version}.vcf.gz")
installed_link = os.path.join(bcbio_base, "variation", "cosmic.vcf.gz")
logging.info(f"Beginning COSMIC v{cosmic_version} prep for {genome_build}.")
if not os.path.exists(bcbio_base):
continue
if os.path.exists(installed_file):
if not overwrite:
logging.info(f"{installed_file} exists, please use the --overwrite flag to overwrite the existing files if you want to reinstall.")
continue
else:
logging.info(f"{installed_file} exists, removing.")
remove_installed(installed_file, installed_link)
bcbio_ref = os.path.join(bcbio_base, "seq", f"{bcbio_build}.fa")
cosmic_vcf_files = get_cosmic_vcf_files(genome_build, cosmic_version, clean)
sorted_inputs = []
for fname in cosmic_vcf_files:
sorted_inputs.append(sort_to_ref(fname, bcbio_ref, add_chr=add_chr))
out_dir = utils.safe_makedir(os.path.join(f"v{cosmic_version}", "bcbio_ready", bcbio_build))
out_file = os.path.join(out_dir, "cosmic.vcf.gz")
ready_cosmic = combine_cosmic(sorted_inputs, bcbio_ref, out_file)
variation_dir = utils.safe_makedir(os.path.join(bcbio_base, "variation"))
utils.copy_plus(ready_cosmic, installed_file)
logging.info(f"Created COSMIC v{cosmic_version} resource in {installed_file}.")
logging.info(f"Linking {installed_file} as {installed_link}.")
make_links(installed_file, installed_link)
update_version_file(bcbio_base, cosmic_version)
logging.info(f"Finished COSMIC v{cosmic_version} prep for {genome_build}.")
# prepare hg19 from the GRCh37 file
if bcbio_build == "GRCh37":
genome_build = "hg19"
logging.info(f"Prepping COSMIC v{cosmic_version} for {genome_build} from the GRCh37 preparation.")
bcbio_base = os.path.join(bcbio_genome_dir, "genomes", "Hsapiens", genome_build)
if not os.path.exists(bcbio_base):
continue
if os.path.exists(installed_file):
installed_file = os.path.join(bcbio_base, "variation", f"cosmic-v{cosmic_version}.vcf.gz")
installed_link = os.path.join(bcbio_base, "variation", "cosmic.vcf.gz")
if not overwrite:
logging.info(f"{installed_file} exists, please use the --overwrite flag to overwrite the existing files if you want to reinstall.")
continue
else:
logging.info(f"{installed_file} exists, removing.")
remove_installed(installed_file, installed_link)
out_dir = utils.safe_makedir(os.path.join(f"v{cosmic_version}", "bcbio_ready", genome_build))
out_file = os.path.join(out_dir, f"cosmic-v{cosmic_version}.vcf.gz")
logging.info(f"Translating GRCh37 chromosome names to hg19 chromosome names.")
hg19_cosmic = map_coords_to_ucsc(ready_cosmic, bcbio_ref, out_file)
variation_dir = utils.safe_makedir(os.path.join(bcbio_base, "variation"))
utils.copy_plus(hg19_cosmic, installed_file)
logging.info(f"Created COSMIC v{cosmic_version} resource in {installed_file}.")
logging.info(f"Linking {installed_file} as {installed_link}.")
make_links(installed_file, installed_link)
update_version_file(bcbio_base, cosmic_version)
logging.info(f"Finished COSMIC v{cosmic_version} prep for {genome_build}.")
def _add_genes_to_bed(in_file, gene_file, fai_file, out_file, data, max_distance=10000):
"""Re-usable subcomponent that annotates BED file genes from another BED
"""
try:
input_rec = iter(pybedtools.BedTool(in_file)).next()
except StopIteration: # empty file
utils.copy_plus(in_file, out_file)
return
# keep everything after standard chrom/start/end, 1-based
extra_fields = range(4, len(input_rec.fields) + 1)
# keep the new gene annotation
gene_index = len(input_rec.fields) + 4
extra_fields.append(gene_index)
columns = ",".join([str(x) for x in extra_fields])
max_column = max(extra_fields) + 1
ops = ",".join(["distinct"] * len(extra_fields))
# swap over gene name to '.' if beyond maximum distance
# cut removes the last distance column which can cause issues
# with bedtools merge: 'ERROR: illegal character '.' found in integer conversion of string'
distance_filter = (r"""awk -F$'\t' -v OFS='\t' '{if ($NF > %s) $%s = "."} {print}'""" %
(max_distance, gene_index))
sort_cmd = bedutils.get_sort_cmd()
cat_cmd = "zcat" if in_file.endswith(".gz") else "cat"
# Ensure gene transcripts match reference genome
ready_gene_file = os.path.join(os.path.dirname(out_file), "%s-genomeonly.bed" %
(utils.splitext_plus(os.path.basename(gene_file))[0]))
ready_gene_file = bedutils.subset_to_genome(gene_file, ready_gene_file, data)
cmd = ("{cat_cmd} {in_file} | grep -v ^track | grep -v ^browser | grep -v ^# | "
"{sort_cmd} -k1,1 -k2,2n | "
"bedtools closest -g <(cut -f1,2 {fai_file} | {sort_cmd} -k1,1 -k2,2n) "
"-d -t all -a - -b <({sort_cmd} -k1,1 -k2,2n {ready_gene_file}) | "
"{distance_filter} | cut -f 1-{max_column} | "
"bedtools merge -i - -c {columns} -o {ops} -delim ',' -d -10 > {out_file}")
do.run(cmd.format(**locals()), "Annotate BED file with gene info")
def coverage_region_detailed_stats(target_name,
bed_file,
data,
out_dir,
extra_cutoffs=None):
"""
Calculate coverage at different completeness cutoff
for region in coverage option.
"""
if not bed_file or not utils.file_exists(bed_file):
return []
else:
ready_depth = tz.get_in(["depth", target_name], data)
if ready_depth:
cov_file = ready_depth["regions"]
dist_file = ready_depth["dist"]
else:
mosdepth_cov = run_mosdepth(data, target_name, bed_file)
cov_file = mosdepth_cov.regions
dist_file = mosdepth_cov.dist
out_cov_file = os.path.join(out_dir, os.path.basename(cov_file))
out_dist_file = os.path.join(out_dir, os.path.basename(dist_file))
if not utils.file_uptodate(out_cov_file, cov_file):
utils.copy_plus(cov_file, out_cov_file)
utils.copy_plus(dist_file, out_dist_file)
cutoffs = {1, 5, 10, 20, 50, 100, 250, 500, 1000, 5000, 10000, 50000}
if extra_cutoffs:
cutoffs = sorted(list(cutoffs | extra_cutoffs))
out_files = _calculate_percentiles(out_dist_file, cutoffs, out_dir,
data)
return [os.path.abspath(x) for x in out_files]
def _make_examples(bam_file, data, ref_file, region, out_file, work_dir):
"""Create example pileup images to feed into variant calling.
"""
region_bed = strelka2.get_region_bed(region, [data],
out_file,
want_gzip=False)
log_dir = utils.safe_makedir(os.path.join(work_dir, "log"))
example_dir = utils.safe_makedir(os.path.join(work_dir, "examples"))
if len(
glob.glob(
os.path.join(example_dir, "%s.tfrecord*.gz" %
dd.get_sample_name(data)))) == 0:
with tx_tmpdir(data) as tx_example_dir:
cmd = [
"dv_make_examples.py", "--cores",
dd.get_num_cores(data), "--ref", ref_file, "--reads", bam_file,
"--regions", region_bed, "--logdir", log_dir, "--examples",
tx_example_dir, "--sample",
dd.get_sample_name(data)
]
do.run(cmd,
"DeepVariant make_examples %s" % dd.get_sample_name(data))
for fname in glob.glob(
os.path.join(tx_example_dir, "%s.tfrecord*.gz" %
dd.get_sample_name(data))):
utils.copy_plus(
fname, os.path.join(example_dir, os.path.basename(fname)))
return example_dir
def _calculate_percentiles(cov_file, dist_file, cutoffs, out_dir, data):
"""Calculate percentage over over specified cutoff range.
XXX Does not calculate the per-bin coverage estimations which we had
earlier with sambamba depth. Instead has a global metric of percent coverage
which provides a more defined look at coverage changes by depth.
"""
if not utils.file_exists(dist_file) or not utils.file_exists(cov_file):
return []
sample = dd.get_sample_name(data)
out_total_file = append_stem(dist_file, "_total_summary")
if not utils.file_exists(out_total_file):
with file_transaction(data, out_total_file) as tx_file:
with open(tx_file, 'w') as out_handle:
writer = csv.writer(out_handle, dialect="excel-tab")
writer.writerow(["cutoff_reads", "bases_pct", "sample"])
with open(dist_file) as in_handle:
for line in in_handle:
count, pct = line.strip().split()
count = int(count)
pct = "%.1f" % (float(pct) * 100.0)
if count >= min(cutoffs) and count <= max(cutoffs):
writer.writerow(
["percentage%s" % count, pct, sample])
if min(cutoffs) < count:
writer.writerow(
["percentage%s" % min(cutoffs), pct, sample])
# To move metrics to multiqc, will remove older files
# when bcbreport accepts these one, to avoid errors
# while porting everything to multiqc
# These files will be copied to final
out_total_fixed = os.path.join(os.path.dirname(out_total_file),
"%s_bcbio_coverage_avg.txt" % sample)
copy_plus(out_total_file, out_total_fixed)
return [out_total_fixed]
def summarize_sv(items):
"""CWL target: summarize structural variants for multiple samples.
XXX Need to support non-VCF output as tabix indexed output
"""
items = [utils.to_single_data(x) for x in items]
out = {"sv": {"calls": []}}
added = set([])
for data in items:
if data.get("sv"):
names = dd.get_batches(data)
if not names:
names = [dd.get_sample_name(data)]
batch_name = names[0]
cur_name = "%s-%s" % (batch_name, data["sv"]["variantcaller"])
ext = utils.splitext_plus(data["sv"]["vrn_file"])[-1]
if cur_name not in added and ext.startswith(".vcf"):
added.add(cur_name)
out_file = os.path.join(
utils.safe_makedir(
os.path.join(dd.get_work_dir(data), "sv", "calls")),
"%s%s" % (cur_name, ext))
utils.copy_plus(data["sv"]["vrn_file"], out_file)
out_file = vcfutils.bgzip_and_index(out_file, data["config"])
out["sv"]["calls"].append(out_file)
return [out]
def organize_noalign(data):
"""CWL target to skip alignment and organize input data.
"""
data = utils.to_single_data(data[0])
work_dir = utils.safe_makedir(os.path.join(dd.get_work_dir(data), "align", dd.get_sample_name(data)))
work_bam = os.path.join(work_dir, "%s-input.bam" % dd.get_sample_name(data))
utils.copy_plus(data["files"][0], work_bam)
bam.index(work_bam, data["config"])
data["align_bam"] = work_bam
return data
def _run_germline(align_bams, items, ref_file, assoc_files, region, out_file, work_dir):
if not utils.file_exists(out_file):
with file_transaction(items[0], work_dir) as tx_work_dir:
workflow_file = _configure_germline(align_bams, items, ref_file, region, out_file, tx_work_dir)
_run_workflow(items[0], workflow_file, tx_work_dir)
raw_file = os.path.join(work_dir, "results", "variants",
"genome.vcf.gz" if joint.want_gvcf(items) else "variants.vcf.gz")
utils.copy_plus(raw_file, out_file)
# Remove files with relative symlinks
utils.remove_plus(os.path.join(work_dir, "results", "variants", "genome.vcf.gz"))
return vcfutils.bgzip_and_index(out_file, items[0]["config"])
def summarize_vc(items):
"""CWL target: summarize variant calls and validation for multiple samples.
"""
items = [utils.to_single_data(x) for x in utils.flatten(items)]
items = [_normalize_vc_input(x) for x in items]
items = validate.summarize_grading(items)
items = [utils.to_single_data(x) for x in items]
out = {
"validate": validate.combine_validations(items),
"variants": {
"calls": [],
"gvcf": [],
"samples": []
}
}
added = set([])
variants_by_sample = collections.defaultdict(list)
sample_order = []
for data in items:
batch_samples = data.get("batch_samples", [dd.get_sample_name(data)])
for s in batch_samples:
if s not in sample_order:
sample_order.append(s)
if data.get("vrn_file"):
# Only get batches if we're actually doing variantcalling in bcbio
# otherwise we'll be using the original files
names = dd.get_batches(data) if dd.get_variantcaller(
data) else None
if not names:
names = [dd.get_sample_name(data)]
batch_name = names[0]
if data.get("vrn_file_joint") is not None:
to_add = [("vrn_file", "gvcf", dd.get_sample_name(data)),
("vrn_file_joint", "calls", batch_name)]
else:
to_add = [("vrn_file", "calls", batch_name)]
for vrn_key, out_key, name in to_add:
cur_name = "%s-%s" % (name, dd.get_variantcaller(data))
out_file = os.path.join(
utils.safe_makedir(
os.path.join(dd.get_work_dir(data), "variants",
out_key)), "%s.vcf.gz" % cur_name)
for s in batch_samples:
variants_by_sample[s].append(out_file)
if cur_name not in added:
added.add(cur_name)
# Ideally could symlink here but doesn't appear to work with
# Docker container runs on Toil where PATHs don't get remapped
utils.copy_plus(os.path.realpath(data[vrn_key]), out_file)
vcfutils.bgzip_and_index(out_file, data["config"])
out["variants"][out_key].append(out_file)
for sample in sample_order:
out["variants"]["samples"].append(variants_by_sample[sample])
return [out]
def _run_germline(align_bams, items, ref_file, assoc_files, region, out_file, work_dir):
if not utils.file_exists(out_file):
with file_transaction(items[0], work_dir) as tx_work_dir:
workflow_file = _configure_germline(align_bams, items, ref_file, region, out_file, tx_work_dir)
_run_workflow(items[0], workflow_file, tx_work_dir)
raw_file = os.path.join(work_dir, "results", "variants",
"genome.vcf.gz" if joint.want_gvcf(items) else "variants.vcf.gz")
utils.copy_plus(raw_file, out_file)
# Remove files with relative symlinks
utils.remove_plus(os.path.join(work_dir, "results", "variants", "genome.vcf.gz"))
return vcfutils.bgzip_and_index(out_file, items[0]["config"])
def _symlink_or_copy_grabix(in_file, out_file, data):
"""We cannot symlink in CWL, but may be able to use inputs or copy
"""
if cwlutils.is_cwl_run(data):
# Has grabix indexes, we're okay to go
if utils.file_exists(in_file + ".gbi"):
out_file = in_file
else:
utils.copy_plus(in_file, out_file)
else:
utils.symlink_plus(in_file, out_file)
return out_file
def _calculate_percentiles(in_file, sample, data=None, cutoffs=None):
"""
Parse pct bases per region to summarize it in
7 different pct of regions points with pct bases covered
higher than a completeness cutoff (5, 10, 20, 50 ...)
"""
has_data = False
with open(in_file) as in_handle:
for i, line in enumerate(in_handle):
if i > 0:
has_data = True
break
if not has_data:
return []
out_file = append_stem(in_file, "_summary")
out_total_file = append_stem(in_file, "_total_summary")
if not utils.file_exists(out_file) or not utils.file_exists(
out_total_file):
dt = pd.read_csv(in_file, sep="\t", index_col=False)
pct = dict()
pct_bases = dict()
size = np.array(dt["chromEnd"]) - np.array(dt["chromStart"])
for cutoff in [h for h in list(dt) if h.startswith("percentage")]:
if cutoffs and int(cutoff.split("percentage")[1]) in cutoffs:
a = np.array(dt[cutoff])
for p_point in [0.01, 10, 25, 50, 75, 90, 99.9]:
q = np.percentile(a, p_point)
pct[(cutoff, p_point)] = q
pct_bases[cutoff] = sum(size * a) / float(sum(size))
with file_transaction(data, out_total_file) as tx_file:
with open(tx_file, 'w') as out_handle:
print >> out_handle, "cutoff_reads\tbases_pct\tsample"
for k in pct_bases:
print >> out_handle, "\t".join(
map(str, [k, pct_bases[k], sample]))
with file_transaction(data, out_file) as tx_file:
with open(tx_file, 'w') as out_handle:
print >> out_handle, "cutoff_reads\tregion_pct\tbases_pct\tsample"
for k in pct:
print >> out_handle, "\t".join(
map(str, [k[0], k[1], pct[k], sample]))
# To move metrics to multiqc, will remove older files
# when bcbreport accepts these one, to avoid errors
# while porting everything to multiqc
# These files will be copied to final
out_file_fixed = os.path.join(os.path.dirname(out_file),
"%s_bcbio_coverage.txt" % sample)
out_total_fixed = os.path.join(os.path.dirname(out_file),
"%s_bcbio_coverage_avg.txt" % sample)
copy_plus(out_file, out_file_fixed)
copy_plus(out_total_file, out_total_fixed)
return [out_file_fixed, out_total_fixed]
def _symlink_or_copy_grabix(in_file, out_file, data):
"""We cannot symlink in CWL, but may be able to use inputs or copy
"""
if cwlutils.is_cwl_run(data):
# Has grabix indexes, we're okay to go
if utils.file_exists(in_file + ".gbi"):
out_file = in_file
else:
utils.copy_plus(in_file, out_file)
else:
utils.symlink_plus(in_file, out_file)
return out_file
def summarize_sv(items):
"""CWL target: summarize structural variants for multiple samples.
XXX Need to support non-VCF output as tabix indexed output
"""
items = [
utils.to_single_data(x)
for x in vcvalidate.summarize_grading(items, "svvalidate")
]
out = {
"sv": {
"calls": [],
"prioritize": {
"tsv": [],
"raw": []
}
},
"svvalidate": vcvalidate.combine_validations(items, "svvalidate")
}
added = set([])
# Standard callers
for data in items:
if data.get("sv"):
names = dd.get_batches(data)
if not names:
names = [dd.get_sample_name(data)]
batch_name = names[0]
cur_name = "%s-%s" % (batch_name, data["sv"]["variantcaller"])
if data["sv"].get("vrn_file"):
ext = utils.splitext_plus(data["sv"]["vrn_file"])[-1]
if cur_name not in added and ext.startswith(".vcf"):
added.add(cur_name)
out_file = os.path.join(
utils.safe_makedir(
os.path.join(dd.get_work_dir(data), "sv",
"calls")), "%s%s" % (cur_name, ext))
utils.copy_plus(data["sv"]["vrn_file"], out_file)
out_file = vcfutils.bgzip_and_index(
out_file, data["config"])
out["sv"]["calls"].append(out_file)
# prioritization
for pdata in _group_by_sample(items):
prioritysv = [
x for x in prioritize.run([utils.deepish_copy(pdata)])[0].get(
"sv", []) if x["variantcaller"] == "sv-prioritize"
]
if prioritysv:
out["sv"]["prioritize"]["tsv"].append(prioritysv[0]["vrn_file"])
out["sv"]["prioritize"]["raw"].extend(
prioritysv[0]["raw_files"].values())
return [out]
def _make_examples(bam_file, data, ref_file, region_bed, out_file, work_dir):
"""Create example pileup images to feed into variant calling.
"""
log_dir = utils.safe_makedir(os.path.join(work_dir, "log"))
example_dir = utils.safe_makedir(os.path.join(work_dir, "examples"))
if len(glob.glob(os.path.join(example_dir, "%s.tfrecord*.gz" % dd.get_sample_name(data)))) == 0:
with tx_tmpdir(data) as tx_example_dir:
cmd = ["dv_make_examples.py", "--cores", dd.get_num_cores(data), "--ref", ref_file,
"--reads", bam_file, "--regions", region_bed, "--logdir", log_dir,
"--examples", tx_example_dir, "--sample", dd.get_sample_name(data)]
do.run(cmd, "DeepVariant make_examples %s" % dd.get_sample_name(data))
for fname in glob.glob(os.path.join(tx_example_dir, "%s.tfrecord*.gz" % dd.get_sample_name(data))):
utils.copy_plus(fname, os.path.join(example_dir, os.path.basename(fname)))
return example_dir
def _link_bam_file(in_file, new_dir, data):
"""Provide symlinks of BAM file and existing indexes if needed.
"""
new_dir = utils.safe_makedir(new_dir)
out_file = os.path.join(new_dir, os.path.basename(in_file))
if data.get("cwl_keys"):
# Has indexes, we're okay to go with the original file
if utils.file_exists(in_file + ".bai"):
out_file = in_file
else:
utils.copy_plus(in_file, out_file)
else:
utils.symlink_plus(in_file, out_file)
return out_file
def _handle_precalled(data):
"""Copy in external pre-called variants fed into analysis.
"""
if data.get("vrn_file"):
vrn_file = data["vrn_file"]
if isinstance(vrn_file, (list, tuple)):
assert len(vrn_file) == 1
vrn_file = vrn_file[0]
precalled_dir = utils.safe_makedir(os.path.join(dd.get_work_dir(data), "precalled"))
ext = utils.splitext_plus(vrn_file)[-1]
orig_file = os.path.abspath(vrn_file)
our_vrn_file = os.path.join(precalled_dir, "%s-precalled%s" % (dd.get_sample_name(data), ext))
utils.copy_plus(orig_file, our_vrn_file)
data["vrn_file"] = our_vrn_file
return data
def _handle_precalled(data):
"""Copy in external pre-called variants fed into analysis.
"""
if data.get("vrn_file"):
vrn_file = data["vrn_file"]
if isinstance(vrn_file, (list, tuple)):
assert len(vrn_file) == 1
vrn_file = vrn_file[0]
precalled_dir = utils.safe_makedir(os.path.join(dd.get_work_dir(data), "precalled"))
ext = utils.splitext_plus(vrn_file)[-1]
orig_file = os.path.abspath(vrn_file)
our_vrn_file = os.path.join(precalled_dir, "%s-precalled%s" % (dd.get_sample_name(data), ext))
utils.copy_plus(orig_file, our_vrn_file)
data["vrn_file"] = our_vrn_file
return data
def _calculate_percentiles(in_file, sample, data=None, cutoffs=None):
"""
Parse pct bases per region to summarize it in
7 different pct of regions points with pct bases covered
higher than a completeness cutoff (5, 10, 20, 50 ...)
"""
has_data = False
with open(in_file) as in_handle:
for i, line in enumerate(in_handle):
if i > 0:
has_data = True
break
if not has_data:
return []
out_file = append_stem(in_file, "_summary")
out_total_file = append_stem(in_file, "_total_summary")
if not utils.file_exists(out_file) or not utils.file_exists(out_total_file):
dt = pd.read_csv(in_file, sep="\t", index_col=False)
pct = dict()
pct_bases = dict()
size = np.array(dt["chromEnd"]) - np.array(dt["chromStart"])
for cutoff in [h for h in list(dt) if h.startswith("percentage")]:
if cutoffs and int(cutoff.split("percentage")[1]) in cutoffs:
a = np.array(dt[cutoff])
for p_point in [0.01, 10, 25, 50, 75, 90, 99.9]:
q = np.percentile(a, p_point)
pct[(cutoff, p_point)] = q
pct_bases[cutoff] = sum(size * a) / float(sum(size))
with file_transaction(data, out_total_file) as tx_file:
with open(tx_file, 'w') as out_handle:
print >>out_handle, "cutoff_reads\tbases_pct\tsample"
for k in pct_bases:
print >>out_handle, "\t".join(map(str, [k, pct_bases[k], sample]))
with file_transaction(data, out_file) as tx_file:
with open(tx_file, 'w') as out_handle:
print >>out_handle, "cutoff_reads\tregion_pct\tbases_pct\tsample"
for k in pct:
print >>out_handle, "\t".join(map(str, [k[0], k[1], pct[k], sample]))
# To move metrics to multiqc, will remove older files
# when bcbreport accepts these one, to avoid errors
# while porting everything to multiqc
# These files will be copied to final
out_file_fixed = os.path.join(os.path.dirname(out_file), "%s_bcbio_coverage.txt" % sample)
out_total_fixed = os.path.join(os.path.dirname(out_file), "%s_bcbio_coverage_avg.txt" % sample)
copy_plus(out_file, out_file_fixed)
copy_plus(out_total_file, out_total_fixed)
return [out_file_fixed, out_total_fixed]
def _link_bam_file(in_file, new_dir, data):
"""Provide symlinks of BAM file and existing indexes if needed.
"""
new_dir = utils.safe_makedir(new_dir)
out_file = os.path.join(new_dir, os.path.basename(in_file))
if not utils.file_exists(out_file):
out_file = os.path.join(new_dir, "%s-prealign.bam" % dd.get_sample_name(data))
if data.get("cwl_keys"):
# Has indexes, we're okay to go with the original file
if utils.file_exists(in_file + ".bai"):
out_file = in_file
else:
utils.copy_plus(in_file, out_file)
else:
utils.symlink_plus(in_file, out_file)
return out_file
def _bgzip_from_fastq(data):
"""Prepare a bgzipped file from a fastq input, potentially gzipped (or bgzipped already).
"""
in_file = data["in_file"]
needs_convert = dd.get_quality_format(data).lower() == "illumina"
# special case, empty files that have been cleaned
if not objectstore.is_remote(in_file) and os.path.getsize(in_file) == 0:
needs_bgzip, needs_gunzip = False, False
elif in_file.endswith(".gz") and not objectstore.is_remote(in_file):
if needs_convert or dd.get_trim_ends(data):
needs_bgzip, needs_gunzip = True, True
else:
needs_bgzip, needs_gunzip = _check_gzipped_input(in_file, data)
elif in_file.endswith(".bz2"):
needs_bgzip, needs_gunzip = True, True
elif objectstore.is_remote(in_file) and not tz.get_in(["config", "algorithm", "align_split_size"], data):
needs_bgzip, needs_gunzip = False, False
else:
needs_bgzip, needs_gunzip = True, False
work_dir = utils.safe_makedir(os.path.join(data["dirs"]["work"], "align_prep"))
if needs_bgzip or needs_gunzip or needs_convert or dd.get_trim_ends(data) or objectstore.is_remote(in_file):
out_file = _bgzip_file(in_file, data["config"], work_dir,
needs_bgzip, needs_gunzip, needs_convert, data)
else:
out_file = os.path.join(work_dir, "%s_%s" % (dd.get_sample_name(data), os.path.basename(in_file)))
# We cannot symlink in CWL, but may be able to use inputs or copy
if data.get("is_cwl"):
# Has grabix indexes, we're okay to go
if utils.file_exists(in_file + ".gbi"):
return in_file
else:
return utils.copy_plus(in_file, out_file)
else:
utils.symlink_plus(in_file, out_file)
return out_file
def organize_noalign(data):
"""CWL target to skip alignment and organize input data.
"""
data = utils.to_single_data(data[0])
work_dir = utils.safe_makedir(os.path.join(dd.get_work_dir(data), "align", dd.get_sample_name(data)))
work_bam = os.path.join(work_dir, "%s-input.bam" % dd.get_sample_name(data))
if data.get("files"):
if data["files"][0].endswith(".cram"):
work_bam = cram.to_bam(data["files"][0], work_bam, data)
else:
assert data["files"][0].endswith(".bam"), data["files"][0]
utils.copy_plus(data["files"][0], work_bam)
bam.index(work_bam, data["config"])
else:
work_bam = None
data["align_bam"] = work_bam
return data
def organize_noalign(data):
"""CWL target to skip alignment and organize input data.
"""
data = utils.to_single_data(data[0])
work_dir = utils.safe_makedir(os.path.join(dd.get_work_dir(data), "align", dd.get_sample_name(data)))
work_bam = os.path.join(work_dir, "%s-input.bam" % dd.get_sample_name(data))
if data.get("files"):
if data["files"][0].endswith(".cram"):
work_bam = cram.to_bam(data["files"][0], work_bam, data)
else:
assert data["files"][0].endswith(".bam"), data["files"][0]
utils.copy_plus(data["files"][0], work_bam)
bam.index(work_bam, data["config"])
else:
work_bam = None
data["align_bam"] = work_bam
return data
def summarize_vc(items):
"""CWL target: summarize variant calls and validation for multiple samples.
"""
items = [utils.to_single_data(x) for x in utils.flatten(items)]
items = [_normalize_vc_input(x) for x in items]
items = validate.summarize_grading(items)
items = [utils.to_single_data(x) for x in items]
out = {"validate": validate.combine_validations(items),
"variants": {"calls": [], "gvcf": [], "samples": []}}
added = set([])
variants_by_sample = collections.defaultdict(list)
sample_order = []
for data in items:
batch_samples = data.get("batch_samples", [dd.get_sample_name(data)])
for s in batch_samples:
if s not in sample_order:
sample_order.append(s)
if data.get("vrn_file"):
# Only get batches if we're actually doing variantcalling in bcbio
# otherwise we'll be using the original files
names = dd.get_batches(data) if dd.get_variantcaller(data) else None
if not names:
names = [dd.get_sample_name(data)]
batch_name = names[0]
if data.get("vrn_file_joint") is not None:
to_add = [("vrn_file", "gvcf", dd.get_sample_name(data)),
("vrn_file_joint", "calls", batch_name)]
else:
to_add = [("vrn_file", "calls", batch_name)]
for vrn_key, out_key, name in to_add:
cur_name = "%s-%s" % (name, dd.get_variantcaller(data))
out_file = os.path.join(utils.safe_makedir(os.path.join(dd.get_work_dir(data),
"variants", out_key)),
"%s.vcf.gz" % cur_name)
for s in batch_samples:
variants_by_sample[s].append(out_file)
if cur_name not in added:
added.add(cur_name)
# Ideally could symlink here but doesn't appear to work with
# Docker container runs on Toil where PATHs don't get remapped
utils.copy_plus(os.path.realpath(data[vrn_key]), out_file)
vcfutils.bgzip_and_index(out_file, data["config"])
out["variants"][out_key].append(out_file)
for sample in sample_order:
out["variants"]["samples"].append(variants_by_sample[sample])
return [out]
def _handle_precalled(data):
"""Copy in external pre-called variants fed into analysis.
Symlinks for non-CWL runs where we want to ensure VCF present
in a local directory.
"""
if data.get("vrn_file") and not cwlutils.is_cwl_run(data):
vrn_file = data["vrn_file"]
if isinstance(vrn_file, (list, tuple)):
assert len(vrn_file) == 1
vrn_file = vrn_file[0]
precalled_dir = utils.safe_makedir(os.path.join(dd.get_work_dir(data), "precalled"))
ext = utils.splitext_plus(vrn_file)[-1]
orig_file = os.path.abspath(vrn_file)
our_vrn_file = os.path.join(precalled_dir, "%s-precalled%s" % (dd.get_sample_name(data), ext))
utils.copy_plus(orig_file, our_vrn_file)
data["vrn_file"] = our_vrn_file
return data
def main(cosmic_version, bcbio_genome_dir):
work_dir = utils.safe_makedir(os.path.join(os.getcwd(), "cosmic-prep"))
os.chdir(work_dir)
for genome_build, bcbio_build, add_chr in [("GRCh37", "GRCh37", False),
("GRCh38", "hg38", True)]:
bcbio_base = os.path.join(bcbio_genome_dir, "genomes", "Hsapiens",
bcbio_build)
if not os.path.exists(bcbio_base):
continue
bcbio_ref = os.path.join(bcbio_base, "seq", "%s.fa" % bcbio_build)
sorted_inputs = []
for fname in get_cosmic_files(genome_build, cosmic_version):
sorted_inputs.append(sort_to_ref(fname, bcbio_ref,
add_chr=add_chr))
out_dir = utils.safe_makedir(
os.path.join("v%s" % cosmic_version, "bcbio_ready", bcbio_build))
out_file = os.path.join(out_dir, "cosmic.vcf.gz")
ready_cosmic = combine_cosmic(sorted_inputs, bcbio_ref, out_file)
variation_dir = utils.safe_makedir(
os.path.join(bcbio_base, "variation"))
utils.copy_plus(
ready_cosmic,
os.path.join(variation_dir, os.path.basename(ready_cosmic)))
print("Created COSMIC v%s resource in %s" %
(cosmic_version,
os.path.join(variation_dir, os.path.basename(ready_cosmic))))
if bcbio_build == "GRCh37":
bcbio_base = os.path.join(bcbio_genome_dir, "genomes", "Hsapiens",
"hg19")
if not os.path.exists(bcbio_base):
continue
out_dir = utils.safe_makedir(
os.path.join("v%s" % cosmic_version, "bcbio_ready", "hg19"))
out_file = os.path.join(out_dir, "cosmic.vcf.gz")
hg19_cosmic = map_coords_to_ucsc(ready_cosmic, bcbio_ref, out_file)
variation_dir = utils.safe_makedir(
os.path.join(bcbio_base, "variation"))
utils.copy_plus(
hg19_cosmic,
os.path.join(variation_dir, os.path.basename(hg19_cosmic)))
print("Created COSMIC v%s resource in %s" %
(cosmic_version,
os.path.join(variation_dir, os.path.basename(hg19_cosmic))))
def _add_genes_to_bed(in_file, gene_file, fai_file, out_file, data, max_distance=10000):
"""Re-usable subcomponent that annotates BED file genes from another BED
"""
try:
input_rec = next(iter(pybedtools.BedTool(in_file)))
except StopIteration: # empty file
utils.copy_plus(in_file, out_file)
return
# keep everything after standard chrom/start/end, 1-based
extra_fields = list(range(4, len(input_rec.fields) + 1))
# keep the new gene annotation
gene_index = len(input_rec.fields) + 4
extra_fields.append(gene_index)
columns = ",".join([str(x) for x in extra_fields])
max_column = max(extra_fields) + 1
ops = ",".join(["distinct"] * len(extra_fields))
# swap over gene name to '.' if beyond maximum distance
# cut removes the last distance column which can cause issues
# with bedtools merge: 'ERROR: illegal character '.' found in integer conversion of string'
distance_filter = (r"""awk -F$'\t' -v OFS='\t' '{if ($NF > %s || $NF < -%s) $%s = "."} {print}'""" %
(max_distance, max_distance, gene_index))
sort_cmd = bedutils.get_sort_cmd(os.path.dirname(out_file))
cat_cmd = "zcat" if in_file.endswith(".gz") else "cat"
# Ensure gene transcripts match reference genome
ready_gene_file = os.path.join(os.path.dirname(out_file), "%s-genomeonly.bed" %
(utils.splitext_plus(os.path.basename(gene_file))[0]))
ready_gene_file = bedutils.subset_to_genome(gene_file, ready_gene_file, data)
exports = "export TMPDIR=%s && %s" % (os.path.dirname(out_file), utils.local_path_export())
bcbio_py = sys.executable
gsort = config_utils.get_program("gsort", data)
cmd = ("{exports}{cat_cmd} {in_file} | grep -v ^track | grep -v ^browser | grep -v ^# | "
"{bcbio_py} -c 'from bcbio.variation import bedutils; bedutils.remove_bad()' | "
"{gsort} - {fai_file} | "
"bedtools closest -g {fai_file} "
"-D ref -t first -a - -b <({gsort} {ready_gene_file} {fai_file}) | "
"{distance_filter} | cut -f 1-{max_column} | "
"bedtools merge -i - -c {columns} -o {ops} -delim ',' -d -10 > {out_file}")
do.run(cmd.format(**locals()), "Annotate BED file with gene info")
def _run_germline(align_bams, items, ref_file, assoc_files, region, out_file,
work_dir):
if not utils.file_exists(out_file):
with file_transaction(items[0], work_dir) as tx_work_dir:
workflow_file = _configure_germline(align_bams, items, ref_file,
region, out_file, tx_work_dir)
if workflow_file:
has_variants = True
_run_workflow(items[0], workflow_file, tx_work_dir)
else:
has_variants = False
vcfutils.write_empty_vcf(
out_file, items[0]["config"],
[dd.get_sample_name(d) for d in items])
if has_variants:
raw_file = os.path.join(
work_dir, "results", "variants", "genome.vcf.gz"
if joint.want_gvcf(items) else "variants.vcf.gz")
utils.copy_plus(raw_file, out_file)
# Remove files with relative symlinks
utils.remove_plus(
os.path.join(work_dir, "results", "variants", "genome.vcf.gz"))
return vcfutils.bgzip_and_index(out_file, items[0]["config"])
def coverage_region_detailed_stats(bed_file,
data,
out_dir,
extra_cutoffs=None):
"""
Calculate coverage at different completeness cutoff
for region in coverage option.
"""
if not bed_file or not utils.file_exists(bed_file):
return []
else:
cov_file, dist_file = _run_mosdepth(bed_file, data)
out_cov_file = os.path.join(out_dir, os.path.basename(cov_file))
out_dist_file = os.path.join(out_dir, os.path.basename(dist_file))
if not utils.file_uptodate(out_cov_file, cov_file):
utils.copy_plus(cov_file, out_cov_file)
utils.copy_plus(dist_file, out_dist_file)
cutoffs = {1, 5, 10, 20, 50, 100, 250, 500, 1000, 5000, 10000, 50000}
if extra_cutoffs:
cutoffs = sorted(list(cutoffs | extra_cutoffs))
out_files = _calculate_percentiles(out_cov_file, out_dist_file,
cutoffs, out_dir, data)
return [os.path.abspath(x) for x in out_files]
def summarize_sv(items):
"""CWL target: summarize structural variants for multiple samples.
XXX Need to support non-VCF output as tabix indexed output
"""
items = [utils.to_single_data(x) for x in vcvalidate.summarize_grading(items, "svvalidate")]
out = {"sv": {"calls": [],
"supplemental": [],
"prioritize": {"tsv": [],
"raw": []}},
"svvalidate": vcvalidate.combine_validations(items, "svvalidate")}
added = set([])
# Standard callers
for data in items:
if data.get("sv"):
if data["sv"].get("vrn_file"):
ext = utils.splitext_plus(data["sv"]["vrn_file"])[-1]
cur_name = _useful_basename(data)
if cur_name not in added and ext.startswith(".vcf"):
added.add(cur_name)
out_file = os.path.join(utils.safe_makedir(os.path.join(dd.get_work_dir(data),
"sv", "calls")),
"%s%s" % (cur_name, ext))
utils.copy_plus(data["sv"]["vrn_file"], out_file)
out_file = vcfutils.bgzip_and_index(out_file, data["config"])
out["sv"]["calls"].append(out_file)
if data["sv"].get("supplemental"):
out["sv"]["supplemental"].extend([x for x in data["sv"]["supplemental"] if x])
# prioritization
for pdata in _group_by_sample(items):
prioritysv = [x for x in prioritize.run([utils.deepish_copy(pdata)])[0].get("sv", [])
if x["variantcaller"] == "sv-prioritize"]
if prioritysv:
out["sv"]["prioritize"]["tsv"].append(prioritysv[0]["vrn_file"])
out["sv"]["prioritize"]["raw"].extend(prioritysv[0]["raw_files"].values())
return [out]
def coverage_region_detailed_stats(target_name, bed_file, data, out_dir):
"""
Calculate coverage at different completeness cutoff
for region in coverage option.
"""
if bed_file and utils.file_exists(bed_file):
ready_depth = tz.get_in(["depth", target_name], data)
if ready_depth:
cov_file = ready_depth["regions"]
dist_file = ready_depth["dist"]
thresholds_file = ready_depth.get("thresholds")
out_cov_file = os.path.join(out_dir, os.path.basename(cov_file))
out_dist_file = os.path.join(out_dir, os.path.basename(dist_file))
out_thresholds_file = os.path.join(out_dir, os.path.basename(thresholds_file)) \
if thresholds_file and os.path.isfile(thresholds_file) else None
if not utils.file_uptodate(out_cov_file, cov_file):
utils.copy_plus(cov_file, out_cov_file)
utils.copy_plus(dist_file, out_dist_file)
utils.copy_plus(thresholds_file, out_thresholds_file) if out_thresholds_file else None
return [out_cov_file, out_dist_file] + ([out_thresholds_file] if out_thresholds_file else [])
return []
def coverage_region_detailed_stats(target_name, bed_file, data, out_dir):
"""
Calculate coverage at different completeness cutoff
for region in coverage option.
"""
if bed_file and utils.file_exists(bed_file):
ready_depth = tz.get_in(["depth", target_name], data)
if ready_depth:
cov_file = ready_depth["regions"]
dist_file = ready_depth["dist"]
thresholds_file = ready_depth.get("thresholds")
out_cov_file = os.path.join(out_dir, os.path.basename(cov_file))
out_dist_file = os.path.join(out_dir, os.path.basename(dist_file))
out_thresholds_file = os.path.join(out_dir, os.path.basename(thresholds_file)) \
if thresholds_file and os.path.isfile(thresholds_file) else None
if not utils.file_uptodate(out_cov_file, cov_file):
utils.copy_plus(cov_file, out_cov_file)
utils.copy_plus(dist_file, out_dist_file)
utils.copy_plus(thresholds_file, out_thresholds_file) if out_thresholds_file else None
return [out_cov_file, out_dist_file] + ([out_thresholds_file] if out_thresholds_file else [])
return []
def _report_summary(samples, out_dir):
"""
Run coverage report with bcbiocov package
"""
try:
import bcbreport.prepare as bcbreport
except ImportError:
logger.info("skipping report. No bcbreport installed.")
return samples
# samples = utils.unpack_worlds(samples)
work_dir = dd.get_work_dir(samples[0])
parent_dir = utils.safe_makedir(out_dir)
with utils.chdir(parent_dir):
logger.info("copy qsignature")
qsignature_fn = os.path.join(work_dir, "qc", "qsignature",
"qsignature.ma")
if qsignature_fn: # this need to be inside summary/qc dict
if utils.file_exists(
qsignature_fn) and not utils.file_exists("qsignature.ma"):
shutil.copy(qsignature_fn, "bcbio_qsignature.ma")
out_dir = utils.safe_makedir("fastqc")
logger.info("summarize fastqc")
with utils.chdir(out_dir):
_merge_fastqc(samples)
logger.info("summarize metrics")
samples = _merge_metrics(samples)
logger.info("summarize target information")
samples = _merge_target_information(samples)
out_dir = utils.safe_makedir("coverage")
logger.info("summarize coverage")
for data in samples:
pfiles = tz.get_in(["summary", "qc", "coverage"], data, [])
if isinstance(pfiles, dict):
pfiles = [pfiles["base"]] + pfiles["secondary"]
elif pfiles:
pfiles = [pfiles]
for fn in pfiles:
if os.path.basename(fn).find("coverage_fixed") > -1:
utils.copy_plus(
fn, os.path.join(out_dir, os.path.basename(fn)))
out_dir = utils.safe_makedir("variants")
logger.info("summarize variants")
for data in samples:
pfiles = tz.get_in(["summary", "qc", "variants"], data, [])
if isinstance(pfiles, dict):
pfiles = [pfiles["base"]] + pfiles["secondary"]
elif pfiles:
pfiles = [pfiles]
for fn in pfiles:
if os.path.basename(fn).find("gc-depth-parse.tsv") > -1:
utils.copy_plus(
fn, os.path.join(out_dir, os.path.basename(fn)))
bcbreport.report(parent_dir)
out_report = os.path.join(parent_dir, "qc-coverage-report.html")
if not utils.file_exists(out_report):
rmd_file = os.path.join(parent_dir, "report-ready.Rmd")
run_file = "%s-run.R" % (os.path.splitext(out_report)[0])
with open(run_file, "w") as out_handle:
out_handle.write("""library(rmarkdown)\nrender("%s")\n""" %
rmd_file)
cmd = "%s %s" % (utils.Rscript_cmd(), run_file)
# Skip automated generation of coverage report to avoid error
# messages. We need to generalize coverage reporting and re-include.
# try:
# do.run(cmd, "Prepare coverage summary", log_error=False)
# except subprocess.CalledProcessError as msg:
# logger.info("Skipping generation of coverage report: %s" % (str(msg)))
if utils.file_exists("report-ready.html"):
shutil.move("report-ready.html", out_report)
return samples
def _report_summary(samples, out_dir):
"""
Run coverage report with bcbiocov package
"""
try:
import bcbreport.prepare as bcbreport
except ImportError:
logger.info("skipping report. No bcbreport installed.")
return samples
# samples = utils.unpack_worlds(samples)
work_dir = dd.get_work_dir(samples[0])
parent_dir = utils.safe_makedir(out_dir)
with utils.chdir(parent_dir):
logger.info("copy qsignature")
qsignature_fn = os.path.join(work_dir, "qc", "qsignature", "qsignature.ma")
if qsignature_fn: # this need to be inside summary/qc dict
if utils.file_exists(qsignature_fn) and not utils.file_exists("qsignature.ma"):
shutil.copy(qsignature_fn, "bcbio_qsignature.ma")
out_dir = utils.safe_makedir("fastqc")
logger.info("summarize fastqc")
with utils.chdir(out_dir):
_merge_fastqc(samples)
logger.info("summarize metrics")
samples = _merge_metrics(samples)
out_dir = utils.safe_makedir("coverage")
logger.info("summarize coverage")
for data in samples:
pfiles = tz.get_in(["summary", "qc", "coverage"], data, [])
if isinstance(pfiles, dict):
pfiles = [pfiles["base"]] + pfiles["secondary"]
elif pfiles:
pfiles = [pfiles]
for fn in pfiles:
if os.path.basename(fn).find("coverage_fixed") > -1:
utils.copy_plus(fn, os.path.join(out_dir, os.path.basename(fn)))
out_dir = utils.safe_makedir("variants")
logger.info("summarize variants")
for data in samples:
pfiles = tz.get_in(["summary", "qc", "variants"], data, [])
if isinstance(pfiles, dict):
pfiles = [pfiles["base"]] + pfiles["secondary"]
elif pfiles:
pfiles = [pfiles]
for fn in pfiles:
if os.path.basename(fn).find("gc-depth-parse.tsv") > -1:
utils.copy_plus(fn, os.path.join(out_dir, os.path.basename(fn)))
bcbreport.report(parent_dir)
out_report = os.path.join(parent_dir, "qc-coverage-report.html")
if not utils.file_exists(out_report):
rmd_file = os.path.join(parent_dir, "report-ready.Rmd")
run_file = "%s-run.R" % (os.path.splitext(out_report)[0])
with open(run_file, "w") as out_handle:
out_handle.write("""library(rmarkdown)\nrender("%s")\n""" % rmd_file)
cmd = "%s %s" % (utils.Rscript_cmd(), run_file)
# Skip automated generation of coverage report to avoid error
# messages. We need to generalize coverage reporting and re-include.
# try:
# do.run(cmd, "Prepare coverage summary", log_error=False)
# except subprocess.CalledProcessError, msg:
# logger.info("Skipping generation of coverage report: %s" % (str(msg)))
if utils.file_exists("report-ready.html"):
shutil.move("report-ready.html", out_report)
return samples