def run_rnaseq(bam_file, data, out_dir):
"""
Run qualimap for a rnaseq bam file and parse results
"""
strandedness = {"firststrand": "strand-specific-reverse",
"secondstrand": "strand-specific-forward",
"unstranded": "non-strand-specific"}
# Qualimap results should be saved to a directory named after sample.
# MultiQC (for parsing additional data) picks the sample name after the dir as follows:
# <sample name>/raw_data_qualimapReport/insert_size_histogram.txt
results_dir = os.path.join(out_dir, dd.get_sample_name(data))
report_file = os.path.join(results_dir, "qualimapReport.html")
config = data["config"]
gtf_file = dd.get_gtf_file(data)
single_end = not bam.is_paired(bam_file)
library = strandedness[dd.get_strandedness(data)]
if not utils.file_exists(report_file):
with file_transaction(data, results_dir) as tx_out_dir:
utils.safe_makedir(tx_out_dir)
raw_file = os.path.join(tx_out_dir, "rnaseq_qc_results.txt")
bam.index(bam_file, config)
cmd = _rnaseq_qualimap_cmd(data, bam_file, tx_out_dir, gtf_file, single_end, library)
do.run(cmd, "Qualimap for {}".format(dd.get_sample_name(data)))
cmd = "sed -i 's/bam file = .*/bam file = %s.bam/' %s" % (dd.get_sample_name(data), raw_file)
do.run(cmd, "Fix Name Qualimap for {}".format(dd.get_sample_name(data)))
metrics = _parse_rnaseq_qualimap_metrics(report_file)
metrics.update(_detect_duplicates(bam_file, results_dir, data))
metrics.update(_detect_rRNA(data))
metrics.update({"Average_insert_size": bam.estimate_fragment_size(bam_file)})
metrics = _parse_metrics(metrics)
return metrics
def run_rnaseq(bam_file, data, out_dir):
"""
Run qualimap for a rnaseq bam file and parse results
"""
strandedness = {"firststrand": "strand-specific-reverse",
"secondstrand": "strand-specific-forward",
"unstranded": "non-strand-specific"}
report_file = os.path.join(out_dir, "qualimapReport.html")
raw_file = os.path.join(out_dir, "rnaseq_qc_results.txt")
config = data["config"]
gtf_file = dd.get_gtf_file(data)
single_end = not bam.is_paired(bam_file)
library = strandedness[dd.get_strandedness(data)]
if not utils.file_exists(report_file):
utils.safe_makedir(out_dir)
bam.index(bam_file, config)
cmd = _rnaseq_qualimap_cmd(data, bam_file, out_dir, gtf_file, single_end, library)
do.run(cmd, "Qualimap for {}".format(dd.get_sample_name(data)))
cmd = "sed -i 's/bam file = .*/bam file = %s.bam/' %s" % (dd.get_sample_name(data), raw_file)
do.run(cmd, "Fix Name Qualimap for {}".format(dd.get_sample_name(data)))
metrics = _parse_rnaseq_qualimap_metrics(report_file)
metrics.update(_detect_duplicates(bam_file, out_dir, data))
metrics.update(_detect_rRNA(data))
metrics.update({"Average insert size": bam.estimate_fragment_size(bam_file)})
metrics = _parse_metrics(metrics)
return metrics
def run_rnaseq(bam_file, data, out_dir):
"""
Run qualimap for a rnaseq bam file and parse results
"""
strandedness = {"firststrand": "strand-specific-reverse",
"secondstrand": "strand-specific-forward",
"unstranded": "non-strand-specific"}
report_file = os.path.join(out_dir, "qualimapReport.html")
raw_file = os.path.join(out_dir, "rnaseq_qc_results.txt")
config = data["config"]
gtf_file = dd.get_gtf_file(data)
single_end = not bam.is_paired(bam_file)
library = strandedness[dd.get_strandedness(data)]
if not utils.file_exists(report_file):
utils.safe_makedir(out_dir)
bam.index(bam_file, config)
cmd = _rnaseq_qualimap_cmd(data, bam_file, out_dir, gtf_file, single_end, library)
do.run(cmd, "Qualimap for {}".format(dd.get_sample_name(data)))
cmd = "sed -i 's/bam file = .*/bam file = %s.bam/' %s" % (dd.get_sample_name(data), raw_file)
do.run(cmd, "Fix Name Qualimap for {}".format(dd.get_sample_name(data)))
metrics = _parse_rnaseq_qualimap_metrics(report_file)
metrics.update(_detect_duplicates(bam_file, out_dir, data))
metrics.update(_detect_rRNA(data))
metrics.update({"Average insert size": bam.estimate_fragment_size(bam_file)})
metrics = _parse_metrics(metrics)
return metrics
def run_rnaseq(bam_file, data, out_dir):
"""
Run qualimap for a rnaseq bam file and parse results
"""
strandedness = {
"firststrand": "strand-specific-reverse",
"secondstrand": "strand-specific-forward",
"unstranded": "non-strand-specific"
}
# Qualimap results should be saved to a directory named after sample.
# MultiQC (for parsing additional data) picks the sample name after the dir as follows:
# <sample name>/raw_data_qualimapReport/insert_size_histogram.txt
results_dir = os.path.join(out_dir, dd.get_sample_name(data))
results_file = os.path.join(results_dir, "rnaseq_qc_results.txt")
report_file = os.path.join(results_dir, "qualimapReport.html")
config = data["config"]
gtf_file = dd.get_gtf_file(data)
single_end = not bam.is_paired(bam_file)
library = strandedness[dd.get_strandedness(data)]
if not utils.file_exists(results_file):
with file_transaction(data, results_dir) as tx_results_dir:
utils.safe_makedir(tx_results_dir)
bam.index(bam_file, config)
cmd = _rnaseq_qualimap_cmd(data, bam_file, tx_results_dir,
gtf_file, single_end, library)
do.run(cmd, "Qualimap for {}".format(dd.get_sample_name(data)))
tx_results_file = os.path.join(tx_results_dir,
"rnaseq_qc_results.txt")
cmd = "sed -i 's/bam file = .*/bam file = %s.bam/' %s" % (
dd.get_sample_name(data), tx_results_file)
do.run(cmd,
"Fix Name Qualimap for {}".format(dd.get_sample_name(data)))
metrics = _parse_rnaseq_qualimap_metrics(report_file)
metrics.update(_detect_duplicates(bam_file, results_dir, data))
metrics.update(_detect_rRNA(data))
metrics.update(
{"Average_insert_size": bam.estimate_fragment_size(bam_file)})
metrics = _parse_metrics(metrics)
# Qualimap output folder (results_dir) needs to be named after the sample (see comments above). However, in order
# to keep its name after upload, we need to put the base QC file (results_file) into the root directory (out_dir):
base_results_file = os.path.join(out_dir, os.path.basename(results_file))
shutil.copyfile(results_file, base_results_file)
return {
"base": base_results_file,
"secondary": _find_qualimap_secondary_files(results_dir,
base_results_file),
"metrics": metrics
}
def _rnaseq_qualimap(bam_file, data, out_dir):
"""
Run qualimap for a rnaseq bam file and parse results
"""
report_file = os.path.join(out_dir, "qualimapReport.html")
config = data["config"]
gtf_file = dd.get_gtf_file(data)
ref_file = dd.get_ref_file(data)
single_end = not bam.is_paired(bam_file)
if not utils.file_exists(report_file):
utils.safe_makedir(out_dir)
bam.index(bam_file, config)
cmd = _rnaseq_qualimap_cmd(config, bam_file, out_dir, gtf_file, single_end)
do.run(cmd, "Qualimap for {}".format(data["name"][-1]))
metrics = _parse_rnaseq_qualimap_metrics(report_file)
metrics.update(_detect_duplicates(bam_file, out_dir, config))
metrics.update(_detect_rRNA(config, bam_file, gtf_file, ref_file, out_dir, single_end))
metrics.update({"Fragment Length Mean": bam.estimate_fragment_size(bam_file)})
metrics = _parse_metrics(metrics)
return metrics
def _rnaseq_qualimap(bam_file, data, out_dir):
"""
Run qualimap for a rnaseq bam file and parse results
"""
report_file = os.path.join(out_dir, "qualimapReport.html")
config = data["config"]
gtf_file = dd.get_gtf_file(data)
ref_file = dd.get_ref_file(data)
single_end = not bam.is_paired(bam_file)
if not utils.file_exists(report_file):
utils.safe_makedir(out_dir)
bam.index(bam_file, config)
cmd = _rnaseq_qualimap_cmd(config, bam_file, out_dir, gtf_file, single_end)
do.run(cmd, "Qualimap for {}".format(data["name"][-1]))
metrics = _parse_rnaseq_qualimap_metrics(report_file)
metrics.update(_detect_duplicates(bam_file, out_dir, data))
metrics.update(_detect_rRNA(data))
metrics.update({"Fragment Length Mean": bam.estimate_fragment_size(bam_file)})
metrics = _parse_metrics(metrics)
return metrics
def run_rnaseq(bam_file, data, out_dir):
"""
Run qualimap for a rnaseq bam file and parse results
"""
strandedness = {
"firststrand": "strand-specific-reverse",
"secondstrand": "strand-specific-forward",
"unstranded": "non-strand-specific"
}
# Qualimap results should be saved to a directory named after sample.
# MultiQC (for parsing additional data) picks the sample name after the dir as follows:
# <sample name>/raw_data_qualimapReport/insert_size_histogram.txt
results_dir = os.path.join(out_dir, dd.get_sample_name(data))
report_file = os.path.join(results_dir, "qualimapReport.html")
raw_file = os.path.join(results_dir, "rnaseq_qc_results.txt")
config = data["config"]
gtf_file = dd.get_gtf_file(data)
single_end = not bam.is_paired(bam_file)
library = strandedness[dd.get_strandedness(data)]
if not utils.file_exists(report_file):
utils.safe_makedir(results_dir)
bam.index(bam_file, config)
cmd = _rnaseq_qualimap_cmd(data, bam_file, results_dir, gtf_file,
single_end, library)
do.run(cmd, "Qualimap for {}".format(dd.get_sample_name(data)))
cmd = "sed -i 's/bam file = .*/bam file = %s.bam/' %s" % (
dd.get_sample_name(data), raw_file)
do.run(cmd,
"Fix Name Qualimap for {}".format(dd.get_sample_name(data)))
metrics = _parse_rnaseq_qualimap_metrics(report_file)
metrics.update(_detect_duplicates(bam_file, results_dir, data))
metrics.update(_detect_rRNA(data))
metrics.update(
{"Average_insert_size": bam.estimate_fragment_size(bam_file)})
metrics = _parse_metrics(metrics)
return metrics
