def run(bam_file, data, out_dir):
"""Run qualimap to assess alignment quality metrics.
"""
# 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))
resources = config_utils.get_resources("qualimap", data["config"])
options = " ".join(resources.get("options", ""))
results_file = os.path.join(results_dir, "genome_results.txt")
report_file = os.path.join(results_dir, "qualimapReport.html")
utils.safe_makedir(results_dir)
pdf_file = "qualimapReport.pdf"
if not utils.file_exists(results_file) and not utils.file_exists(os.path.join(results_dir, pdf_file)):
if "qualimap_full" in tz.get_in(("config", "algorithm", "tools_on"), data, []):
logger.info("Full qualimap analysis for %s may be slow." % bam_file)
ds_bam = bam_file
else:
ds_bam = bam.downsample(bam_file, data, 1e7, work_dir=out_dir)
bam_file = ds_bam if ds_bam else bam_file
if options.find("PDF") > -1:
options = "%s -outfile %s" % (options, pdf_file)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
qualimap = config_utils.get_program("qualimap", data["config"])
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
num_cores)
with file_transaction(data, results_dir) as tx_results_dir:
utils.safe_makedir(tx_results_dir)
export = "%s%s export JAVA_OPTS='-Xms32m -Xmx%s -Djava.io.tmpdir=%s' && " % (
utils.java_freetype_fix(), utils.local_path_export(), max_mem, tx_results_dir)
cmd = ("unset DISPLAY && {export} {qualimap} bamqc -bam {bam_file} -outdir {tx_results_dir} "
"--skip-duplicated --skip-dup-mode 0 "
"-nt {num_cores} {options}")
species = None
if (tz.get_in(("genome_resources", "aliases", "human"), data, "")
or dd.get_genome_build(data).startswith(("hg", "GRCh"))):
species = "HUMAN"
elif dd.get_genome_build(data).startswith(("mm", "GRCm")):
species = "MOUSE"
if species in ["HUMAN", "MOUSE"]:
cmd += " -gd {species}"
regions = (dd.get_coverage(data) if dd.get_coverage(data) not in [None, False, "None"]
else dd.get_variant_regions_merged(data))
if regions:
regions = bedutils.merge_overlaps(bedutils.clean_file(regions, data), data)
bed6_regions = _bed_to_bed6(regions, out_dir)
cmd += " -gff {bed6_regions}"
bcbio_env = utils.get_bcbio_env()
do.run(cmd.format(**locals()), "Qualimap: %s" % dd.get_sample_name(data), env=bcbio_env)
tx_results_file = os.path.join(tx_results_dir, "genome_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)))
# 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)}
def align_pipe(fastq_file, pair_file, ref_file, names, align_dir, config):
"""Perform piped alignment of fastq input files, generating sorted output BAM.
"""
pair_file = pair_file if pair_file else ""
out_file = os.path.join(align_dir, "{0}-sort.bam".format(names["lane"]))
samtools = config_utils.get_program("samtools", config)
bwa = config_utils.get_program("bwa", config)
resources = config_utils.get_resources("samtools", config)
num_cores = config["algorithm"].get("num_cores", 1)
# adjust memory for samtools since used alongside alignment
max_mem = config_utils.adjust_memory(resources.get("memory", "2G"),
3, "decrease")
rg_info = novoalign.get_rg_info(names)
if not utils.file_exists(out_file):
novoalign.check_samtools_version(config)
with utils.curdir_tmpdir() as work_dir:
with file_transaction(out_file) as tx_out_file:
tx_out_prefix = os.path.splitext(tx_out_file)[0]
cmd = ("{bwa} mem -M -t {num_cores} -R '{rg_info}' -v 1 {ref_file} "
"{fastq_file} {pair_file} "
"| {samtools} view -b -S -u - "
"| {samtools} sort -@ {num_cores} -m {max_mem} - {tx_out_prefix}")
cmd = cmd.format(**locals())
do.run(cmd, "bwa mem alignment from fastq: %s" % names["sample"], None,
[do.file_nonempty(tx_out_file)])
return out_file
def align_bam(in_bam, ref_file, names, align_dir, data):
"""Perform direct alignment of an input BAM file with BWA using pipes.
This avoids disk IO by piping between processes:
- samtools sort of input BAM to queryname
- bedtools conversion to interleaved FASTQ
- bwa-mem alignment
- samtools conversion to BAM
- samtools sort to coordinate
"""
config = data["config"]
out_file = os.path.join(align_dir, "{0}-sort.bam".format(names["lane"]))
samtools = config_utils.get_program("samtools", config)
bedtools = config_utils.get_program("bedtools", config)
bwa = config_utils.get_program("bwa", config)
resources = config_utils.get_resources("samtools", config)
num_cores = config["algorithm"].get("num_cores", 1)
# adjust memory for samtools since used for input and output
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
3, "decrease")
rg_info = novoalign.get_rg_info(names)
if not utils.file_exists(out_file):
with utils.curdir_tmpdir() as work_dir:
with postalign.tobam_cl(data, out_file, bam.is_paired(in_bam)) as (tobam_cl, tx_out_file):
tx_out_prefix = os.path.splitext(tx_out_file)[0]
prefix1 = "%s-in1" % tx_out_prefix
cmd = ("{samtools} sort -n -o -l 0 -@ {num_cores} -m {max_mem} {in_bam} {prefix1} "
"| {bedtools} bamtofastq -i /dev/stdin -fq /dev/stdout -fq2 /dev/stdout "
"| {bwa} mem -p -M -t {num_cores} -R '{rg_info}' -v 1 {ref_file} - | ")
cmd = cmd.format(**locals()) + tobam_cl
do.run(cmd, "bwa mem alignment from BAM: %s" % names["sample"], None,
[do.file_nonempty(tx_out_file), do.file_reasonable_size(tx_out_file, in_bam)])
return out_file
def run(bam_file, data, out_dir):
"""Run qualimap to assess alignment quality metrics.
"""
# 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))
resources = config_utils.get_resources("qualimap", data["config"])
options = " ".join(resources.get("options", ""))
results_file = os.path.join(results_dir, "genome_results.txt")
report_file = os.path.join(results_dir, "qualimapReport.html")
utils.safe_makedir(results_dir)
pdf_file = "qualimapReport.pdf"
if not utils.file_exists(results_file) and not utils.file_exists(os.path.join(results_dir, pdf_file)):
if "qualimap_full" in tz.get_in(("config", "algorithm", "tools_on"), data, []):
logger.info("Full qualimap analysis for %s may be slow." % bam_file)
ds_bam = bam_file
else:
ds_bam = bam.downsample(bam_file, data, 1e7, work_dir=out_dir)
bam_file = ds_bam if ds_bam else bam_file
if options.find("PDF") > -1:
options = "%s -outfile %s" % (options, pdf_file)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
qualimap = config_utils.get_program("qualimap", data["config"])
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
num_cores)
with file_transaction(data, results_dir) as tx_results_dir:
utils.safe_makedir(tx_results_dir)
export = "%s%s export JAVA_OPTS='-Xms32m -Xmx%s -Djava.io.tmpdir=%s' && " % (
utils.java_freetype_fix(), utils.local_path_export(), max_mem, tx_results_dir)
cmd = ("unset DISPLAY && {export} {qualimap} bamqc -bam {bam_file} -outdir {tx_results_dir} "
"--skip-duplicated --skip-dup-mode 0 "
"-nt {num_cores} {options}")
species = None
if (tz.get_in(("genome_resources", "aliases", "human"), data, "")
or dd.get_genome_build(data).startswith(("hg", "GRCh"))):
species = "HUMAN"
elif dd.get_genome_build(data).startswith(("mm", "GRCm")):
species = "MOUSE"
if species in ["HUMAN", "MOUSE"]:
cmd += " -gd {species}"
regions = (dd.get_coverage(data) if dd.get_coverage(data) not in [None, False, "None"]
else dd.get_variant_regions_merged(data))
if regions:
regions = bedutils.merge_overlaps(bedutils.clean_file(regions, data), data)
bed6_regions = _bed_to_bed6(regions, out_dir)
cmd += " -gff {bed6_regions}"
bcbio_env = utils.get_bcbio_env()
do.run(cmd.format(**locals()), "Qualimap: %s" % dd.get_sample_name(data), env=bcbio_env)
tx_results_file = os.path.join(tx_results_dir, "genome_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)))
# 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)}
def _extract_split_and_discordants(in_bam, work_dir, data):
"""Retrieve split-read alignments from input BAM file.
"""
dedup_file = os.path.join(work_dir, "%s-dedup.bam" % os.path.splitext(os.path.basename(in_bam))[0])
sr_file = os.path.join(work_dir, "%s-sr.bam" % os.path.splitext(os.path.basename(in_bam))[0])
disc_file = os.path.join(work_dir, "%s-disc.bam" % os.path.splitext(os.path.basename(in_bam))[0])
samtools = config_utils.get_program("samtools", data["config"])
cores = utils.get_in(data, ("config", "algorithm", "num_cores"), 1)
resources = config_utils.get_resources("samtools", data["config"])
mem = config_utils.adjust_memory(resources.get("memory", "2G"),
3, "decrease").upper()
if not utils.file_exists(sr_file) or not utils.file_exists(disc_file) or utils.file_exists(dedup_file):
with tx_tmpdir(data) as tmpdir:
with file_transaction(data, sr_file) as tx_sr_file:
with file_transaction(data, disc_file) as tx_disc_file:
with file_transaction(data, dedup_file) as tx_dedup_file:
samblaster_cl = postalign.samblaster_dedup_sort(data, tx_dedup_file,
tx_sr_file, tx_disc_file)
out_base = os.path.join(tmpdir,
"%s-namesort" % os.path.splitext(os.path.basename(in_bam))[0])
cmd = ("{samtools} sort -n -@ {cores} -m {mem} -O sam -T {out_base} {in_bam} | ")
cmd = cmd.format(**locals()) + samblaster_cl
do.run(cmd, "samblaster: split and discordant reads", data)
for fname in [sr_file, disc_file, dedup_file]:
bam.index(fname, data["config"])
return dedup_file, sr_file, disc_file
def align_bam(in_bam, ref_file, names, align_dir, config):
"""Perform direct alignment of an input BAM file with BWA using pipes.
This avoids disk IO by piping between processes:
- samtools sort of input BAM to queryname
- bedtools conversion to interleaved FASTQ
- bwa-mem alignment
- samtools conversion to BAM
- samtools sort to coordinate
"""
out_file = os.path.join(align_dir, "{0}-sort.bam".format(names["lane"]))
samtools = config_utils.get_program("samtools", config)
bedtools = config_utils.get_program("bedtools", config)
bwa = config_utils.get_program("bwa", config)
resources = config_utils.get_resources("samtools", config)
num_cores = config["algorithm"].get("num_cores", 1)
# adjust memory for samtools since used for input and output
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
3, "decrease")
rg_info = novoalign.get_rg_info(names)
if not utils.file_exists(out_file):
novoalign.check_samtools_version(config)
with utils.curdir_tmpdir() as work_dir:
with file_transaction(out_file) as tx_out_file:
tx_out_prefix = os.path.splitext(tx_out_file)[0]
prefix1 = "%s-in1" % tx_out_prefix
cmd = ("{samtools} sort -n -o -l 0 -@ {num_cores} -m {max_mem} {in_bam} {prefix1} "
"| {bedtools} bamtofastq -i /dev/stdin -fq /dev/stdout -fq2 /dev/stdout "
"| {bwa} mem -p -M -t {num_cores} -R '{rg_info}' -v 1 {ref_file} - "
"| {samtools} view -b -S -u - "
"| {samtools} sort -@ {num_cores} -m {max_mem} - {tx_out_prefix}")
cmd = cmd.format(**locals())
do.run(cmd, "bwa mem alignment from BAM: %s" % names["sample"], None,
[do.file_nonempty(tx_out_file)])
return out_file
def merge_bam_files(bam_files, work_dir, config, out_file=None, batch=None):
"""Merge multiple BAM files from a sample into a single BAM for processing.
Checks system open file limit and merges in batches if necessary to avoid
file handle limits.
"""
if len(bam_files) == 1 and bam.bam_already_sorted(bam_files[0], config,
"coordinate"):
shutil.copy(bam_files[0], out_file)
else:
if out_file is None:
out_file = os.path.join(work_dir,
os.path.basename(sorted(bam_files)[0]))
if batch is not None:
base, ext = os.path.splitext(out_file)
out_file = "%s-b%s%s" % (base, batch, ext)
if not utils.file_exists(out_file):
sambamba = config_utils.get_program("sambamba", config)
samtools = config_utils.get_program("samtools", config)
resources = config_utils.get_resources("samtools", config)
num_cores = config["algorithm"].get("num_cores", 1)
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
2, "decrease").upper()
# sambamba opens 4 handles per file, so try to guess a reasonable batch size
batch_size = (system.open_file_limit() // 4) - 100
if len(bam_files) > batch_size:
bam_files = [
merge_bam_files(xs, work_dir, config, out_file, i)
for i, xs in enumerate(
utils.partition_all(batch_size, bam_files))
]
with tx_tmpdir(config) as tmpdir:
with utils.chdir(tmpdir):
with file_transaction(config, out_file) as tx_out_file:
with file_transaction(
config,
"%s.list" % os.path.splitext(out_file)[0]
) as tx_bam_file_list:
with open(tx_bam_file_list, "w") as out_handle:
for f in sorted(bam_files):
out_handle.write("%s\n" % f)
if bam.bam_already_sorted(bam_files[0], config,
"coordinate"):
cmd = _sambamba_merge(bam_files)
else:
assert config.get("mark_duplicates", True)
cmd = _biobambam_merge_dedup()
do.run(
cmd.format(**locals()),
"Merge bam files to %s" %
os.path.basename(out_file), None)
# Ensure timestamps are up to date on output file and index
# Works around issues on systems with inconsistent times
for ext in ["", ".bai"]:
if os.path.exists(out_file + ext):
subprocess.check_call(["touch", out_file + ext])
for b in bam_files:
utils.save_diskspace(b, "BAM merged to %s" % out_file, config)
bam.index(out_file, config)
return out_file
def run(bam_file, data, out_dir):
"""Run qualimap to assess alignment quality metrics.
"""
resources = config_utils.get_resources("qualimap", data["config"])
options = " ".join(resources.get("options", ""))
report_file = os.path.join(out_dir, "qualimapReport.html")
pdf_file = "qualimapReport.pdf"
if not utils.file_exists(report_file) and not utils.file_exists(os.path.join(out_dir, pdf_file)):
if "qualimap_full" in tz.get_in(("config", "algorithm", "tools_on"), data, []):
logger.info("Full qualimap analysis for %s may be slow." % bam_file)
ds_bam = bam_file
else:
ds_bam = bam.downsample(bam_file, data, 1e7, work_dir=out_dir)
bam_file = ds_bam if ds_bam else bam_file
if options.find("PDF") > -1:
options = "%s -outfile %s" % (options, pdf_file)
utils.safe_makedir(out_dir)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
qualimap = config_utils.get_program("qualimap", data["config"])
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
num_cores)
export = utils.local_path_export()
cmd = ("unset DISPLAY && {export} {qualimap} bamqc -bam {bam_file} -outdir {out_dir} "
"-nt {num_cores} --java-mem-size={max_mem} {options}")
species = tz.get_in(("genome_resources", "aliases", "ensembl"), data, "")
if species in ["HUMAN", "MOUSE"]:
cmd += " -gd {species}"
regions = bedutils.merge_overlaps(dd.get_variant_regions(data), data)
if regions:
bed6_regions = _bed_to_bed6(regions, out_dir)
cmd += " -gff {bed6_regions}"
do.run(cmd.format(**locals()), "Qualimap: %s" % dd.get_sample_name(data))
return _parse_qualimap_metrics(report_file)
def align_bam(in_bam, ref_file, names, align_dir, data):
"""Perform direct alignment of an input BAM file with BWA using pipes.
This avoids disk IO by piping between processes:
- samtools sort of input BAM to queryname
- bedtools conversion to interleaved FASTQ
- bwa-mem alignment
- samtools conversion to BAM
- samtools sort to coordinate
"""
config = data["config"]
out_file = os.path.join(align_dir, "{0}-sort.bam".format(names["lane"]))
samtools = config_utils.get_program("samtools", config)
bedtools = config_utils.get_program("bedtools", config)
resources = config_utils.get_resources("samtools", config)
num_cores = config["algorithm"].get("num_cores", 1)
# adjust memory for samtools since used for input and output
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
3, "decrease").upper()
if not utils.file_exists(out_file):
with tx_tmpdir(data) as work_dir:
with postalign.tobam_cl(data, out_file, bam.is_paired(in_bam)) as (tobam_cl, tx_out_file):
bwa_cmd = _get_bwa_mem_cmd(data, out_file, ref_file, "-")
tx_out_prefix = os.path.splitext(tx_out_file)[0]
prefix1 = "%s-in1" % tx_out_prefix
cmd = ("{samtools} sort -n -o -l 1 -@ {num_cores} -m {max_mem} {in_bam} {prefix1} "
"| {bedtools} bamtofastq -i /dev/stdin -fq /dev/stdout -fq2 /dev/stdout "
"| {bwa_cmd} | ")
cmd = cmd.format(**locals()) + tobam_cl
do.run(cmd, "bwa mem alignment from BAM: %s" % names["sample"], None,
[do.file_nonempty(tx_out_file), do.file_reasonable_size(tx_out_file, in_bam)])
return out_file
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_file = sort_stem + ".bam"
if not utils.file_exists(sort_file):
samtools = config_utils.get_program("samtools", config)
cores = config["algorithm"].get("num_cores", 1)
with file_transaction(config, sort_file) as tx_sort_file:
tx_sort_stem = os.path.splitext(tx_sort_file)[0]
tx_dir = utils.safe_makedir(os.path.dirname(tx_sort_file))
order_flag = "-n" if order == "queryname" else ""
resources = config_utils.get_resources("samtools", config)
# Slightly decrease memory and allow more accurate representation
# in Mb to ensure fits within systems like SLURM
mem = config_utils.adjust_memory(resources.get("memory", "2G"),
1.25, "decrease", out_modifier="M").upper()
cmd = ("{samtools} sort -@ {cores} -m {mem} -O BAM {order_flag} "
"-T {tx_sort_stem}-sort -o {tx_sort_file} {in_bam}")
do.run(cmd.format(**locals()), "Sort BAM file %s: %s to %s" %
(order, os.path.basename(in_bam), os.path.basename(sort_file)))
return sort_file
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_file = sort_stem + ".bam"
if not utils.file_exists(sort_file):
samtools = config_utils.get_program("samtools", config)
cores = config["algorithm"].get("num_cores", 1)
with file_transaction(config, sort_file) as tx_sort_file:
tx_sort_stem = os.path.splitext(tx_sort_file)[0]
tx_dir = utils.safe_makedir(os.path.dirname(tx_sort_file))
order_flag = "-n" if order == "queryname" else ""
resources = config_utils.get_resources("samtools", config)
# Slightly decrease memory and allow more accurate representation
# in Mb to ensure fits within systems like SLURM
mem = config_utils.adjust_memory(resources.get("memory", "2G"),
1.25, "decrease", out_modifier="M").upper()
cmd = ("{samtools} sort -@ {cores} -m {mem} -O BAM {order_flag} "
"-T {tx_sort_stem}-sort -o {tx_sort_file} {in_bam}")
do.run(cmd.format(**locals()), "Sort BAM file %s: %s to %s" %
(order, os.path.basename(in_bam), os.path.basename(sort_file)))
return sort_file
def run(bam_file, data, out_dir):
"""Run qualimap to assess alignment quality metrics.
"""
# 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))
resources = config_utils.get_resources("qualimap", data["config"])
options = " ".join(resources.get("options", ""))
report_file = os.path.join(results_dir, "qualimapReport.html")
utils.safe_makedir(results_dir)
pdf_file = "qualimapReport.pdf"
if not utils.file_exists(report_file) and not utils.file_exists(
os.path.join(results_dir, pdf_file)):
if "qualimap_full" in tz.get_in(("config", "algorithm", "tools_on"),
data, []):
logger.info("Full qualimap analysis for %s may be slow." %
bam_file)
ds_bam = bam_file
else:
ds_bam = bam.downsample(bam_file, data, 1e7, work_dir=out_dir)
bam_file = ds_bam if ds_bam else bam_file
if options.find("PDF") > -1:
options = "%s -outfile %s" % (options, pdf_file)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
qualimap = config_utils.get_program("qualimap", data["config"])
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
num_cores)
# Fixing the file name: MultiQC picks sample name from BAM file name.
fixed_bam_fname = os.path.join(out_dir,
dd.get_sample_name(data) + ".bam")
if not os.path.islink(fixed_bam_fname):
os.symlink(bam_file, fixed_bam_fname)
export = utils.local_path_export()
cmd = (
"unset DISPLAY && {export} {qualimap} bamqc -bam {fixed_bam_fname} -outdir {results_dir} "
"--skip-duplicated --skip-dup-mode 0 "
"-nt {num_cores} --java-mem-size={max_mem} {options}")
species = None
if tz.get_in(("genome_resources", "aliases", "human"), data, ""):
species = "HUMAN"
elif any(
tz.get_in("genome_build", data, "").startswith(k)
for k in ["mm", "GRCm"]):
species = "MOUSE"
if species in ["HUMAN", "MOUSE"]:
cmd += " -gd {species}"
regions = bedutils.merge_overlaps(
dd.get_coverage(data), data) or dd.get_variant_regions_merged(data)
if regions:
bed6_regions = _bed_to_bed6(regions, out_dir)
cmd += " -gff {bed6_regions}"
do.run(cmd.format(**locals()),
"Qualimap: %s" % dd.get_sample_name(data))
# return _parse_qualimap_metrics(report_file, data)
return dict()
def _rnaseq_qualimap_cmd(data,
bam_file,
out_dir,
gtf_file=None,
library="non-strand-specific"):
"""
Create command lines for qualimap
"""
config = data["config"]
qualimap = config_utils.get_program("qualimap", config)
resources = config_utils.get_resources("qualimap", config)
num_cores = resources.get("cores", dd.get_num_cores(data))
max_mem = config_utils.adjust_memory(resources.get("memory", "2G"),
num_cores)
export = "%s%s" % (utils.java_freetype_fix(), utils.local_path_export())
export = "%s%s export JAVA_OPTS='-Xms32m -Xmx%s -Djava.io.tmpdir=%s' && " % (
utils.java_freetype_fix(), utils.local_path_export(), max_mem, out_dir)
if library != "non-strand-specific":
logger.info(
"Qualimap can get the orientation wrong for stranded reads, so we run it in unstranded mode. This gives comparable results to unstranded for RNA-seq data (see https://groups.google.com/forum/#!topic/qualimap/ZGo-k8LGmHQ) for a further explanation."
)
library = "non-strand-specific"
paired = " --paired" if bam.is_paired(bam_file) else ""
cmd = ("unset DISPLAY && {export} {qualimap} rnaseq -outdir {out_dir} "
"-a proportional -bam {bam_file} -p {library}{paired} "
"-gtf {gtf_file}").format(**locals())
return cmd
def _run_qualimap(bam_file, data, out_dir):
"""Run qualimap to assess alignment quality metrics.
"""
report_file = os.path.join(out_dir, "qualimapReport.html")
if not os.path.exists(report_file):
ds_bam = bam.downsample(bam_file, data, 1e7)
bam_file = ds_bam if ds_bam else bam_file
utils.safe_makedir(out_dir)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
qualimap = config_utils.get_program("qualimap", data["config"])
resources = config_utils.get_resources("qualimap", data["config"])
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
num_cores)
cmd = (
"unset DISPLAY && {qualimap} bamqc -bam {bam_file} -outdir {out_dir} "
"-nt {num_cores} --java-mem-size={max_mem}")
species = tz.get_in(("genome_resources", "aliases", "ensembl"), data,
"")
if species in ["HUMAN", "MOUSE"]:
cmd += " -gd {species}"
regions = bedutils.merge_overlaps(dd.get_variant_regions(data), data)
if regions:
bed6_regions = _bed_to_bed6(regions, out_dir)
cmd += " -gff {bed6_regions}"
do.run(cmd.format(**locals()), "Qualimap: %s" % data["name"][-1])
return _parse_qualimap_metrics(report_file)
def _extract_split_and_discordants(in_bam, work_dir, data):
"""Retrieve split-read alignments from input BAM file.
"""
dedup_file = os.path.join(work_dir, "%s-dedup.bam" % os.path.splitext(os.path.basename(in_bam))[0])
sr_file = os.path.join(work_dir, "%s-sr.bam" % os.path.splitext(os.path.basename(in_bam))[0])
disc_file = os.path.join(work_dir, "%s-disc.bam" % os.path.splitext(os.path.basename(in_bam))[0])
samtools = config_utils.get_program("samtools", data["config"])
cores = utils.get_in(data, ("config", "algorithm", "num_cores"), 1)
resources = config_utils.get_resources("sambamba", data["config"])
mem = config_utils.adjust_memory(resources.get("memory", "2G"),
3, "decrease")
if not utils.file_exists(sr_file) or not utils.file_exists(disc_file) or utils.file_exists(dedup_file):
with utils.curdir_tmpdir() as tmpdir:
with file_transaction(sr_file) as tx_sr_file:
with file_transaction(disc_file) as tx_disc_file:
with file_transaction(dedup_file) as tx_dedup_file:
samblaster_cl = postalign.samblaster_dedup_sort(data, tmpdir, tx_dedup_file,
tx_sr_file, tx_disc_file)
out_base = os.path.join(tmpdir, "%s-namesort" % os.path.splitext(in_bam)[0])
cmd = ("{samtools} sort -n -o -@ {cores} -m {mem} {in_bam} {out_base} | "
"{samtools} view -h - | ")
cmd = cmd.format(**locals()) + samblaster_cl
do.run(cmd, "samblaster: split and discordant reads", data)
for fname in [sr_file, disc_file, dedup_file]:
bam.index(fname, data["config"])
return dedup_file, sr_file, disc_file
def run(bam_file, data, out_dir):
"""Run qualimap to assess alignment quality metrics.
"""
resources = config_utils.get_resources("qualimap", data["config"])
options = " ".join(resources.get("options", ""))
report_file = os.path.join(out_dir, "qualimapReport.html")
pdf_file = "qualimapReport.pdf"
if not utils.file_exists(report_file) and not utils.file_exists(os.path.join(out_dir, pdf_file)):
if "qualimap_full" in tz.get_in(("config", "algorithm", "tools_on"), data, []):
logger.info("Full qualimap analysis for %s may be slow." % bam_file)
ds_bam = bam_file
else:
ds_bam = bam.downsample(bam_file, data, 1e7, work_dir=out_dir)
bam_file = ds_bam if ds_bam else bam_file
if options.find("PDF") > -1:
options = "%s -outfile %s" % (options, pdf_file)
utils.safe_makedir(out_dir)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
qualimap = config_utils.get_program("qualimap", data["config"])
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
num_cores)
cmd = ("unset DISPLAY && {qualimap} bamqc -bam {bam_file} -outdir {out_dir} "
"-nt {num_cores} --java-mem-size={max_mem} {options}")
species = tz.get_in(("genome_resources", "aliases", "ensembl"), data, "")
if species in ["HUMAN", "MOUSE"]:
cmd += " -gd {species}"
regions = bedutils.merge_overlaps(dd.get_variant_regions(data), data)
if regions:
bed6_regions = _bed_to_bed6(regions, out_dir)
cmd += " -gff {bed6_regions}"
do.run(cmd.format(**locals()), "Qualimap: %s" % dd.get_sample_name(data))
return _parse_qualimap_metrics(report_file)
def _extract_split_and_discordants(in_bam, work_dir, data):
"""Retrieve split-read alignments from input BAM file.
"""
sr_file = os.path.join(work_dir, "%s-sr.bam" % os.path.splitext(os.path.basename(in_bam))[0])
disc_file = os.path.join(work_dir, "%s-disc.bam" % os.path.splitext(os.path.basename(in_bam))[0])
samblaster = config_utils.get_program("samblaster", data["config"])
sambamba = config_utils.get_program("sambamba", data["config"])
cores = utils.get_in(data, ("config", "algorithm", "num_cores"), 1)
resources = config_utils.get_resources("sambamba", data["config"])
mem = config_utils.adjust_memory(resources.get("memory", "2G"),
3, "decrease")
if not utils.file_exists(sr_file) or not utils.file_exists(disc_file):
with file_transaction(sr_file) as tx_sr_file:
with file_transaction(disc_file) as tx_disc_file:
with utils.curdir_tmpdir() as tmpdir:
tobam_cmd = ("{sambamba} view -S -f bam -l 0 /dev/stdin | "
"{sambamba} sort -t {cores} -m {mem} --tmpdir {tmpdir} "
"-o {out_file} /dev/stdin")
splitter_cmd = tobam_cmd.format(out_file=tx_sr_file, **locals())
discordant_cmd = tobam_cmd.format(out_file=tx_disc_file, **locals())
cmd = ("{sambamba} sort -t {cores} -m {mem} --tmpdir={tmpdir} "
"-n -o /dev/stdout -l 0 {in_bam} | "
"{sambamba} view -h /dev/stdin | "
"{samblaster} --splitterFile >({splitter_cmd}) --discordantFile >({discordant_cmd}) "
"-o /dev/null")
do.run(cmd.format(**locals()), "samblaster: split and discordant reads", data)
return sr_file, disc_file
def sort(in_bam, config, order="coordinate"):
"""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)
sort_file = sort_stem + ".bam"
if not utils.file_exists(sort_file):
sambamba = _get_sambamba(config)
samtools = config_utils.get_program("samtools", config)
cores = config["algorithm"].get("num_cores", 1)
with file_transaction(config, sort_file) as tx_sort_file:
tx_sort_stem = os.path.splitext(tx_sort_file)[0]
tx_dir = utils.safe_makedir(os.path.dirname(tx_sort_file))
order_flag = "-n" if order == "queryname" else ""
resources = config_utils.get_resources("samtools", config)
mem = resources.get("memory", "2G")
samtools_cmd = ("{samtools} sort -@ {cores} -m {mem} {order_flag} "
"{in_bam} {tx_sort_stem}")
if sambamba:
if tz.get_in(["resources", "sambamba"], config):
sm_resources = config_utils.get_resources(
"sambamba", config)
mem = sm_resources.get("memory", "2G")
# sambamba uses total memory, not memory per core
mem = config_utils.adjust_memory(mem, cores,
"increase").upper()
# Use samtools compatible natural sorting
# https://github.com/lomereiter/sambamba/issues/132
order_flag = "--natural-sort" if order == "queryname" else ""
cmd = ("{sambamba} sort -t {cores} -m {mem} {order_flag} "
"-o {tx_sort_file} --tmpdir={tx_dir} {in_bam}")
else:
cmd = samtools_cmd
# sambamba has intermittent multicore failures. Allow
# retries with single core
try:
do.run(
cmd.format(**locals()),
"Sort BAM file (multi core, %s): %s to %s" %
(order, os.path.basename(in_bam),
os.path.basename(sort_file)))
except:
logger.exception(
"Multi-core sorting failed, reverting to single core")
resources = config_utils.get_resources("samtools", config)
mem = resources.get("memory", "2G")
cores = 1
order_flag = "-n" if order == "queryname" else ""
do.run(
samtools_cmd.format(**locals()),
"Sort BAM file (single core, %s): %s to %s" %
(order, os.path.basename(in_bam),
os.path.basename(sort_file)))
return sort_file
def _get_cores_memory(data, downscale=2):
"""Retrieve cores and memory, using samtools as baseline.
For memory, scaling down because we share with alignment and de-duplication.
"""
resources = config_utils.get_resources("samtools", data["config"])
num_cores = data["config"]["algorithm"].get("num_cores", 1)
max_mem = config_utils.adjust_memory(resources.get("memory", "2G"), downscale, "decrease").upper()
return num_cores, max_mem
def merge_bam_files(bam_files, work_dir, config, out_file=None, batch=None):
"""Merge multiple BAM files from a sample into a single BAM for processing.
Checks system open file limit and merges in batches if necessary to avoid
file handle limits.
"""
out_file = _merge_outfile_fname(out_file, bam_files, work_dir, batch)
if not utils.file_exists(out_file):
if len(bam_files) == 1 and bam.bam_already_sorted(
bam_files[0], config, "coordinate"):
with file_transaction(config, out_file) as tx_out_file:
_create_merge_filelist(bam_files, tx_out_file, config)
shutil.copy(bam_files[0], tx_out_file)
samtools = config_utils.get_program("samtools", config)
do.run('{} quickcheck -v {}'.format(samtools, out_file),
"Check for valid merged BAM after transfer")
else:
# sambamba opens 4 handles per file, so try to guess a reasonable batch size
batch_size = (system.open_file_limit() // 4) - 100
if len(bam_files) > batch_size:
bam_files = [
merge_bam_files(xs, work_dir, config, out_file, i)
for i, xs in enumerate(
utils.partition_all(batch_size, bam_files))
]
with tx_tmpdir(config) as tmpdir:
with utils.chdir(tmpdir):
with file_transaction(config, out_file) as tx_out_file:
tx_bam_file_list = _create_merge_filelist(
bam_files, tx_out_file, config)
sambamba = config_utils.get_program("sambamba", config)
samtools = config_utils.get_program("samtools", config)
resources = config_utils.get_resources(
"samtools", config)
num_cores = config["algorithm"].get("num_cores", 1)
max_mem = config_utils.adjust_memory(
resources.get("memory", "1G"), 2,
"decrease").upper()
if bam.bam_already_sorted(bam_files[0], config,
"coordinate"):
cmd = _sambamba_merge(bam_files)
else:
assert config.get("mark_duplicates", True)
cmd = _biobambam_merge_dedup()
do.run(
cmd.format(**locals()), "Merge bam files to %s" %
os.path.basename(out_file), None)
do.run(
'{} quickcheck -v {}'.format(
samtools, tx_out_file),
"Check for valid merged BAM")
do.run('{} quickcheck -v {}'.format(samtools, out_file),
"Check for valid merged BAM after transfer")
_finalize_merge(out_file, bam_files, config)
bam.index(out_file, config)
return out_file
def _get_cores_memory(data, downscale=2):
"""Retrieve cores and memory, using samtools as baseline.
For memory, scaling down because we share with alignment and de-duplication.
"""
resources = config_utils.get_resources("samtools", data["config"])
num_cores = data["config"]["algorithm"].get("num_cores", 1)
max_mem = config_utils.adjust_memory(resources.get("memory", "2G"),
downscale, "decrease").upper()
return num_cores, max_mem
def sort_cmd(config, tmp_dir, named_pipe=None, order="coordinate"):
""" Get a sort command, suitable for piping
"""
sambamba = _get_sambamba(config)
pipe = named_pipe if named_pipe else "/dev/stdin"
order_flag = "-n" if order == "queryname" else ""
resources = config_utils.get_resources("samtools", config)
num_cores = config["algorithm"].get("num_cores", 1)
mem = config_utils.adjust_memory(resources.get("memory", "2G"), 1, "decrease").upper()
cmd = ("{sambamba} sort -m {mem} --tmpdir {tmp_dir} -t {num_cores} {order_flag} -o /dev/stdout {pipe}")
return cmd.format(**locals())
def sort_cmd(config, tmp_dir, named_pipe=None, order="coordinate"):
""" Get a sort command, suitable for piping
"""
sambamba = _get_sambamba(config)
pipe = named_pipe if named_pipe else "/dev/stdin"
order_flag = "-n" if order == "queryname" else ""
resources = config_utils.get_resources("samtools", config)
num_cores = config["algorithm"].get("num_cores", 1)
mem = config_utils.adjust_memory(resources.get("memory", "2G"), 1, "decrease").upper()
cmd = ("{sambamba} sort -m {mem} --tmpdir {tmp_dir} -t {num_cores} {order_flag} -o /dev/stdout {pipe}")
return cmd.format(**locals())
def _rnaseq_qualimap_cmd(config, bam_file, out_dir, gtf_file=None, single_end=None):
"""
Create command lines for qualimap
"""
qualimap = config_utils.get_program("qualimap", config)
resources = config_utils.get_resources("qualimap", config)
num_cores = resources.get("cores", 1)
max_mem = config_utils.adjust_memory(resources.get("memory", "4G"),
num_cores)
cmd = ("unset DISPLAY && {qualimap} rnaseq -outdir {out_dir} -a proportional -bam {bam_file} "
"-gtf {gtf_file} --java-mem-size={max_mem}").format(**locals())
return cmd
def merge_bam_files(bam_files, work_dir, config, out_file=None, batch=None):
"""Merge multiple BAM files from a sample into a single BAM for processing.
Checks system open file limit and merges in batches if necessary to avoid
file handle limits.
"""
if len(bam_files) == 1:
return bam_files[0]
else:
if out_file is None:
out_file = os.path.join(work_dir,
os.path.basename(sorted(bam_files)[0]))
if batch is not None:
base, ext = os.path.splitext(out_file)
out_file = "%s-b%s%s" % (base, batch, ext)
if not utils.file_exists(out_file) or not utils.file_exists(out_file +
".bai"):
bamtools = config_utils.get_program("bamtools", config)
samtools = config_utils.get_program("samtools", config)
resources = config_utils.get_resources("samtools", config)
num_cores = config["algorithm"].get("num_cores", 1)
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
2, "decrease").upper()
batch_size = system.open_file_limit() - 100
if len(bam_files) > batch_size:
bam_files = [
merge_bam_files(xs, work_dir, config, out_file, i)
for i, xs in enumerate(
utils.partition_all(batch_size, bam_files))
]
with utils.curdir_tmpdir({"config": config}) as tmpdir:
with utils.chdir(tmpdir):
merge_cl = _bamtools_merge(bam_files)
with file_transaction(out_file) as tx_out_file:
with file_transaction("%s.list" %
os.path.splitext(out_file)[0]
) as tx_bam_file_list:
tx_out_prefix = os.path.splitext(tx_out_file)[0]
with open(tx_bam_file_list, "w") as out_handle:
for f in sorted(bam_files):
out_handle.write("%s\n" % f)
cmd = (
merge_cl + " | "
"{samtools} sort -@ {num_cores} -m {max_mem} - {tx_out_prefix}"
)
do.run(
cmd.format(**locals()),
"Merge bam files to %s" %
os.path.basename(out_file), None)
for b in bam_files:
utils.save_diskspace(b, "BAM merged to %s" % out_file, config)
bam.index(out_file, config)
return out_file
def _rnaseq_qualimap_cmd(config, bam_file, out_dir, gtf_file=None, single_end=None):
"""
Create command lines for qualimap
"""
qualimap = config_utils.get_program("qualimap", config)
resources = config_utils.get_resources("qualimap", config)
num_cores = resources.get("cores", 1)
max_mem = config_utils.adjust_memory(resources.get("memory", "4G"),
num_cores)
cmd = ("unset DISPLAY && {qualimap} rnaseq -outdir {out_dir} -a proportional -bam {bam_file} "
"-gtf {gtf_file} --java-mem-size={max_mem}").format(**locals())
return cmd
def align_pipe(fastq_file, pair_file, ref_file, names, align_dir, data):
"""Perform piped alignment of fastq input files, generating sorted output BAM.
"""
pair_file = pair_file if pair_file else ""
out_file = os.path.join(align_dir, "{0}-sort.bam".format(names["lane"]))
qual_format = data["config"]["algorithm"].get("quality_format", "").lower()
if data.get("align_split"):
final_file = out_file
out_file, data = alignprep.setup_combine(final_file, data)
fastq_file = alignprep.split_namedpipe_cl(fastq_file, data)
if pair_file:
pair_file = alignprep.split_namedpipe_cl(pair_file, data)
else:
final_file = None
if qual_format == "illumina":
fastq_file = alignprep.fastq_convert_pipe_cl(fastq_file, data)
if pair_file:
pair_file = alignprep.fastq_convert_pipe_cl(pair_file, data)
samtools = config_utils.get_program("samtools", data["config"])
bwa = config_utils.get_program("bwa", data["config"])
resources = config_utils.get_resources("samtools", data["config"])
num_cores = data["config"]["algorithm"].get("num_cores", 1)
# adjust memory for samtools since used alongside alignment
max_mem = config_utils.adjust_memory(resources.get("memory", "2G"), 3,
"decrease")
rg_info = novoalign.get_rg_info(names)
if not utils.file_exists(out_file) and (final_file is None or
not utils.file_exists(final_file)):
# If we cannot do piping, use older bwa aln approach
if not can_pipe(fastq_file, data):
return align(fastq_file, pair_file, ref_file, names, align_dir,
data)
else:
with utils.curdir_tmpdir() as work_dir:
with file_transaction(out_file) as tx_out_file:
tx_out_prefix = os.path.splitext(tx_out_file)[0]
cmd = (
"{bwa} mem -M -t {num_cores} -R '{rg_info}' -v 1 {ref_file} "
"{fastq_file} {pair_file} "
"| {samtools} view -b -S -u - "
"| {samtools} sort -@ {num_cores} -m {max_mem} - {tx_out_prefix}"
)
cmd = cmd.format(**locals())
do.run(
cmd,
"bwa mem alignment from fastq: %s" % names["sample"],
None, [
do.file_nonempty(tx_out_file),
do.file_reasonable_size(tx_out_file, fastq_file)
])
data["work_bam"] = out_file
return data
def sort(in_bam, config, order="coordinate"):
"""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)
sort_file = sort_stem + ".bam"
if not utils.file_exists(sort_file):
sambamba = _get_sambamba(config)
samtools = config_utils.get_program("samtools", config)
cores = config["algorithm"].get("num_cores", 1)
with file_transaction(config, sort_file) as tx_sort_file:
tx_sort_stem = os.path.splitext(tx_sort_file)[0]
tx_dir = utils.safe_makedir(os.path.dirname(tx_sort_file))
order_flag = "-n" if order == "queryname" else ""
resources = config_utils.get_resources("samtools", config)
mem = resources.get("memory", "2G")
samtools_cmd = ("{samtools} sort -@ {cores} -m {mem} {order_flag} "
"{in_bam} {tx_sort_stem}")
if sambamba:
if tz.get_in(["resources", "sambamba"], config):
sm_resources = config_utils.get_resources("sambamba", config)
mem = sm_resources.get("memory", "2G")
# sambamba uses total memory, not memory per core
mem = config_utils.adjust_memory(mem, cores, "increase").upper()
# Use samtools compatible natural sorting
# https://github.com/lomereiter/sambamba/issues/132
order_flag = "--natural-sort" if order == "queryname" else ""
cmd = ("{sambamba} sort -t {cores} -m {mem} {order_flag} "
"-o {tx_sort_file} --tmpdir={tx_dir} {in_bam}")
else:
cmd = samtools_cmd
# sambamba has intermittent multicore failures. Allow
# retries with single core
try:
do.run(cmd.format(**locals()),
"Sort BAM file (multi core, %s): %s to %s" %
(order, os.path.basename(in_bam),
os.path.basename(sort_file)))
except:
logger.exception("Multi-core sorting failed, reverting to single core")
resources = config_utils.get_resources("samtools", config)
mem = resources.get("memory", "2G")
cores = 1
order_flag = "-n" if order == "queryname" else ""
do.run(samtools_cmd.format(**locals()),
"Sort BAM file (single core, %s): %s to %s" %
(order, os.path.basename(in_bam),
os.path.basename(sort_file)))
return sort_file
def _rnaseq_qualimap_cmd(data, bam_file, out_dir, gtf_file=None, single_end=None, library="non-strand-specific"):
"""
Create command lines for qualimap
"""
config = data["config"]
qualimap = config_utils.get_program("qualimap", config)
resources = config_utils.get_resources("qualimap", config)
num_cores = resources.get("cores", dd.get_num_cores(data))
max_mem = config_utils.adjust_memory(resources.get("memory", "2G"),
num_cores)
cmd = ("unset DISPLAY && {qualimap} rnaseq -outdir {out_dir} -a proportional -bam {bam_file} -p {library} "
"-gtf {gtf_file} --java-mem-size={max_mem}").format(**locals())
return cmd
def run(bam_file, data, out_dir):
"""Run qualimap to assess alignment quality metrics.
"""
# 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))
resources = config_utils.get_resources("qualimap", data["config"])
options = " ".join(resources.get("options", ""))
report_file = os.path.join(results_dir, "qualimapReport.html")
utils.safe_makedir(results_dir)
pdf_file = "qualimapReport.pdf"
if not utils.file_exists(report_file) and not utils.file_exists(os.path.join(results_dir, pdf_file)):
if "qualimap_full" in tz.get_in(("config", "algorithm", "tools_on"), data, []):
logger.info("Full qualimap analysis for %s may be slow." % bam_file)
ds_bam = bam_file
else:
ds_bam = bam.downsample(bam_file, data, 1e7, work_dir=out_dir)
bam_file = ds_bam if ds_bam else bam_file
if options.find("PDF") > -1:
options = "%s -outfile %s" % (options, pdf_file)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
qualimap = config_utils.get_program("qualimap", data["config"])
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
num_cores)
# Fixing the file name: MultiQC picks sample name from BAM file name.
fixed_bam_fname = os.path.join(out_dir, dd.get_sample_name(data) + ".bam")
if not os.path.islink(fixed_bam_fname):
os.symlink(bam_file, fixed_bam_fname)
export = utils.local_path_export()
cmd = ("unset DISPLAY && {export} {qualimap} bamqc -bam {fixed_bam_fname} -outdir {results_dir} "
"--skip-duplicated --skip-dup-mode 0 "
"-nt {num_cores} --java-mem-size={max_mem} {options}")
species = None
if tz.get_in(("genome_resources", "aliases", "human"), data, ""):
species = "HUMAN"
elif any(tz.get_in("genome_build", data, "").startswith(k) for k in ["mm", "GRCm"]):
species = "MOUSE"
if species in ["HUMAN", "MOUSE"]:
cmd += " -gd {species}"
regions = bedutils.merge_overlaps(dd.get_coverage(data), data) or dd.get_variant_regions_merged(data)
if regions:
bed6_regions = _bed_to_bed6(regions, out_dir)
cmd += " -gff {bed6_regions}"
do.run(cmd.format(**locals()), "Qualimap: %s" % dd.get_sample_name(data))
# return _parse_qualimap_metrics(report_file, data)
return dict()
def merge_bam_files(bam_files, work_dir, data, out_file=None, batch=None):
"""Merge multiple BAM files from a sample into a single BAM for processing.
Checks system open file limit and merges in batches if necessary to avoid
file handle limits.
"""
out_file = _merge_outfile_fname(out_file, bam_files, work_dir, batch)
if not utils.file_exists(out_file):
if len(bam_files) == 1 and bam.bam_already_sorted(
bam_files[0], data["config"], "coordinate"):
with file_transaction(data, out_file) as tx_out_file:
_create_merge_filelist(bam_files, tx_out_file, data["config"])
out_file = bam_files[0]
samtools = config_utils.get_program("samtools", data["config"])
do.run('{} quickcheck -v {}'.format(samtools, out_file),
"Check for valid merged BAM after transfer")
else:
with tx_tmpdir(data) as tmpdir:
with utils.chdir(tmpdir):
with file_transaction(data, out_file) as tx_out_file:
tx_bam_file_list = _create_merge_filelist(
bam_files, tx_out_file, data["config"])
sambamba = config_utils.get_program(
"sambamba", data["config"])
samtools = config_utils.get_program(
"samtools", data["config"])
resources = config_utils.get_resources(
"samtools", data["config"])
num_cores = dd.get_num_cores(data)
# Aim for 3.5Gb/core memory for BAM merging
num_cores = config_utils.adjust_cores_to_mb_target(
3500, resources.get("memory", "2G"), num_cores)
max_mem = config_utils.adjust_memory(
resources.get("memory", "1G"), 2,
"decrease").upper()
if dd.get_mark_duplicates(data):
cmd = _biobambam_merge_dedup_maxcov(data)
else:
cmd = _biobambam_merge_maxcov(data)
do.run(
cmd.format(**locals()), "Merge bam files to %s" %
os.path.basename(out_file), None)
do.run(
'{} quickcheck -v {}'.format(
samtools, tx_out_file),
"Check for valid merged BAM")
do.run('{} quickcheck -v {}'.format(samtools, out_file),
"Check for valid merged BAM after transfer")
_finalize_merge(out_file, bam_files, data["config"])
bam.index(out_file, data["config"])
return out_file
def merge_bam_files(bam_files, work_dir, config, out_file=None, batch=None):
"""Merge multiple BAM files from a sample into a single BAM for processing.
Checks system open file limit and merges in batches if necessary to avoid
file handle limits.
"""
if len(bam_files) == 1:
bam.index(bam_files[0], config)
return bam_files[0]
else:
if out_file is None:
out_file = os.path.join(work_dir, os.path.basename(sorted(bam_files)[0]))
if batch is not None:
base, ext = os.path.splitext(out_file)
out_file = "%s-b%s%s" % (base, batch, ext)
if not utils.file_exists(out_file):
sambamba = config_utils.get_program("sambamba", config)
samtools = config_utils.get_program("samtools", config)
samblaster = config_utils.get_program("samblaster", config)
resources = config_utils.get_resources("samtools", config)
num_cores = config["algorithm"].get("num_cores", 1)
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
2, "decrease").upper()
# sambamba opens 4 handles per file, so try to guess a reasonable batch size
batch_size = (system.open_file_limit() // 4) - 100
if len(bam_files) > batch_size:
bam_files = [merge_bam_files(xs, work_dir, config, out_file, i)
for i, xs in enumerate(utils.partition_all(batch_size, bam_files))]
with tx_tmpdir(config) as tmpdir:
with utils.chdir(tmpdir):
with file_transaction(config, out_file) as tx_out_file:
with file_transaction(config, "%s.list" % os.path.splitext(out_file)[0]) as tx_bam_file_list:
with open(tx_bam_file_list, "w") as out_handle:
for f in sorted(bam_files):
out_handle.write("%s\n" % f)
if bam.bam_already_sorted(bam_files[0], config, "coordinate"):
cmd = _sambamba_merge(bam_files)
else:
assert config.get("mark_duplicates", True)
cmd = _biobambam_merge_dedup()
do.run(cmd.format(**locals()), "Merge bam files to %s" % os.path.basename(out_file),
None)
# Ensure timestamps are up to date on output file and index
# Works around issues on systems with inconsistent times
for ext in ["", ".bai"]:
if os.path.exists(out_file + ext):
subprocess.check_call(["touch", out_file + ext])
for b in bam_files:
utils.save_diskspace(b, "BAM merged to %s" % out_file, config)
bam.index(out_file, config)
return out_file
def _rnaseq_qualimap_cmd(data, bam_file, out_dir, gtf_file=None, single_end=None, library="non-strand-specific"):
"""
Create command lines for qualimap
"""
config = data["config"]
qualimap = config_utils.get_program("qualimap", config)
resources = config_utils.get_resources("qualimap", config)
num_cores = resources.get("cores", dd.get_num_cores(data))
max_mem = config_utils.adjust_memory(resources.get("memory", "2G"),
num_cores)
export = "%s%s" % (utils.java_freetype_fix(), utils.local_path_export())
cmd = ("unset DISPLAY && {export} {qualimap} rnaseq -outdir {out_dir} "
"-a proportional -bam {bam_file} -p {library} "
"-gtf {gtf_file} --java-mem-size={max_mem}").format(**locals())
return cmd
def merge_bam_files(bam_files, work_dir, config, out_file=None, batch=None):
"""Merge multiple BAM files from a sample into a single BAM for processing.
Checks system open file limit and merges in batches if necessary to avoid
file handle limits.
"""
out_file = _merge_outfile_fname(out_file, bam_files, work_dir, batch)
if not utils.file_exists(out_file):
if len(bam_files) == 1 and bam.bam_already_sorted(bam_files[0], config, "coordinate"):
with file_transaction(config, out_file) as tx_out_file:
_create_merge_filelist(bam_files, tx_out_file, config)
shutil.copy(bam_files[0], tx_out_file)
samtools = config_utils.get_program("samtools", config)
do.run('{} quickcheck -v {}'.format(samtools, out_file),
"Check for valid merged BAM after transfer")
else:
# sambamba opens 4 handles per file, so try to guess a reasonable batch size
batch_size = (system.open_file_limit() // 4) - 100
if len(bam_files) > batch_size:
bam_files = [merge_bam_files(xs, work_dir, config, out_file, i)
for i, xs in enumerate(utils.partition_all(batch_size, bam_files))]
with tx_tmpdir(config) as tmpdir:
with utils.chdir(tmpdir):
with file_transaction(config, out_file) as tx_out_file:
tx_bam_file_list = _create_merge_filelist(bam_files, tx_out_file, config)
sambamba = config_utils.get_program("sambamba", config)
samtools = config_utils.get_program("samtools", config)
resources = config_utils.get_resources("samtools", config)
num_cores = config["algorithm"].get("num_cores", 1)
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
2, "decrease").upper()
if bam.bam_already_sorted(bam_files[0], config, "coordinate"):
cmd = _sambamba_merge(bam_files)
else:
# Aim for 3.5Gb/core memory for BAM merging
num_cores = config_utils.adjust_cores_to_mb_target(
3500, resources.get("memory", "2G"), num_cores)
assert config.get("mark_duplicates", True)
cmd = _biobambam_merge_dedup()
do.run(cmd.format(**locals()), "Merge bam files to %s" % os.path.basename(out_file),
None)
do.run('{} quickcheck -v {}'.format(samtools, tx_out_file),
"Check for valid merged BAM")
do.run('{} quickcheck -v {}'.format(samtools, out_file),
"Check for valid merged BAM after transfer")
_finalize_merge(out_file, bam_files, config)
bam.index(out_file, config)
return out_file
def _rnaseq_qualimap_cmd(data, bam_file, out_dir, gtf_file=None, library="non-strand-specific"):
"""
Create command lines for qualimap
"""
config = data["config"]
qualimap = config_utils.get_program("qualimap", config)
resources = config_utils.get_resources("qualimap", config)
num_cores = resources.get("cores", dd.get_num_cores(data))
max_mem = config_utils.adjust_memory(resources.get("memory", "2G"),
num_cores)
export = "%s%s" % (utils.java_freetype_fix(), utils.local_path_export())
export = "%s%s export JAVA_OPTS='-Xms32m -Xmx%s -Djava.io.tmpdir=%s' && " % (
utils.java_freetype_fix(), utils.local_path_export(), max_mem, out_dir)
paired = " --paired" if bam.is_paired(bam_file) else ""
cmd = ("unset DISPLAY && {export} {qualimap} rnaseq -outdir {out_dir} "
"-a proportional -bam {bam_file} -p {library}{paired} "
"-gtf {gtf_file}").format(**locals())
return cmd
def align_pipe(fastq_file, pair_file, ref_file, names, align_dir, data):
"""Perform piped alignment of fastq input files, generating sorted output BAM.
"""
pair_file = pair_file if pair_file else ""
out_file = os.path.join(align_dir, "{0}-sort.bam".format(names["lane"]))
qual_format = data["config"]["algorithm"].get("quality_format", "").lower()
if data.get("align_split"):
final_file = out_file
out_file, data = alignprep.setup_combine(final_file, data)
fastq_file = alignprep.split_namedpipe_cl(fastq_file, data)
if pair_file:
pair_file = alignprep.split_namedpipe_cl(pair_file, data)
else:
final_file = None
if qual_format == "illumina":
fastq_file = alignprep.fastq_convert_pipe_cl(fastq_file, data)
if pair_file:
pair_file = alignprep.fastq_convert_pipe_cl(pair_file, data)
samtools = config_utils.get_program("samtools", data["config"])
bwa = config_utils.get_program("bwa", data["config"])
resources = config_utils.get_resources("samtools", data["config"])
num_cores = data["config"]["algorithm"].get("num_cores", 1)
# adjust memory for samtools since used alongside alignment
max_mem = config_utils.adjust_memory(resources.get("memory", "2G"),
3, "decrease")
rg_info = novoalign.get_rg_info(names)
if not utils.file_exists(out_file) and (final_file is None or not utils.file_exists(final_file)):
# If we cannot do piping, use older bwa aln approach
if not can_pipe(fastq_file, data):
return align(fastq_file, pair_file, ref_file, names, align_dir, data)
else:
with utils.curdir_tmpdir() as work_dir:
with file_transaction(out_file) as tx_out_file:
tx_out_prefix = os.path.splitext(tx_out_file)[0]
cmd = ("{bwa} mem -M -t {num_cores} -R '{rg_info}' -v 1 {ref_file} "
"{fastq_file} {pair_file} "
"| {samtools} view -b -S -u - "
"| {samtools} sort -@ {num_cores} -m {max_mem} - {tx_out_prefix}")
cmd = cmd.format(**locals())
do.run(cmd, "bwa mem alignment from fastq: %s" % names["sample"], None,
[do.file_nonempty(tx_out_file), do.file_reasonable_size(tx_out_file, fastq_file)])
data["work_bam"] = out_file
return data
def merge_bam_files(bam_files, work_dir, config, out_file=None, batch=None):
"""Merge multiple BAM files from a sample into a single BAM for processing.
Checks system open file limit and merges in batches if necessary to avoid
file handle limits.
"""
if len(bam_files) == 1:
return bam_files[0]
else:
if out_file is None:
out_file = os.path.join(work_dir, os.path.basename(sorted(bam_files)[0]))
if batch is not None:
base, ext = os.path.splitext(out_file)
out_file = "%s-b%s%s" % (base, batch, ext)
if not utils.file_exists(out_file) or not utils.file_exists(out_file + ".bai"):
bamtools = config_utils.get_program("bamtools", config)
samtools = config_utils.get_program("samtools", config)
resources = config_utils.get_resources("samtools", config)
num_cores = config["algorithm"].get("num_cores", 1)
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
2, "decrease")
batch_size = system.open_file_limit() - 100
if len(bam_files) > batch_size:
bam_files = [merge_bam_files(xs, work_dir, config, out_file, i)
for i, xs in enumerate(utils.partition_all(batch_size, bam_files))]
with utils.curdir_tmpdir({"config": config}) as tmpdir:
with utils.chdir(tmpdir):
merge_cl = _bamtools_merge(bam_files)
with file_transaction(out_file) as tx_out_file:
with file_transaction("%s.list" % os.path.splitext(out_file)[0]) as tx_bam_file_list:
tx_out_prefix = os.path.splitext(tx_out_file)[0]
with open(tx_bam_file_list, "w") as out_handle:
for f in sorted(bam_files):
out_handle.write("%s\n" % f)
cmd = (merge_cl + " | "
"{samtools} sort -@ {num_cores} -m {max_mem} - {tx_out_prefix}")
do.run(cmd.format(**locals()), "Merge bam files to %s" % os.path.basename(out_file),
None)
for b in bam_files:
utils.save_diskspace(b, "BAM merged to %s" % out_file, config)
bam.index(out_file, config)
return out_file
def merge_bam_files(bam_files, work_dir, data, out_file=None, batch=None):
"""Merge multiple BAM files from a sample into a single BAM for processing.
Checks system open file limit and merges in batches if necessary to avoid
file handle limits.
"""
out_file = _merge_outfile_fname(out_file, bam_files, work_dir, batch)
if not utils.file_exists(out_file):
if len(bam_files) == 1 and bam.bam_already_sorted(bam_files[0], data["config"], "coordinate"):
with file_transaction(data, out_file) as tx_out_file:
_create_merge_filelist(bam_files, tx_out_file, data["config"])
out_file = bam_files[0]
samtools = config_utils.get_program("samtools", data["config"])
do.run('{} quickcheck -v {}'.format(samtools, out_file),
"Check for valid merged BAM after transfer")
else:
with tx_tmpdir(data) as tmpdir:
with utils.chdir(tmpdir):
with file_transaction(data, out_file) as tx_out_file:
tx_bam_file_list = _create_merge_filelist(bam_files, tx_out_file, data["config"])
samtools = config_utils.get_program("samtools", data["config"])
resources = config_utils.get_resources("samtools", data["config"])
num_cores = dd.get_num_cores(data)
# Aim for 3.5Gb/core memory for BAM merging
num_cores = config_utils.adjust_cores_to_mb_target(
3500, resources.get("memory", "2G"), num_cores)
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
2, "decrease").upper()
if dd.get_mark_duplicates(data):
cmd = _biobambam_merge_dedup_maxcov(data)
else:
cmd = _biobambam_merge_maxcov(data)
do.run(cmd.format(**locals()), "Merge bam files to %s" % os.path.basename(out_file),
None)
do.run('{} quickcheck -v {}'.format(samtools, tx_out_file),
"Check for valid merged BAM")
do.run('{} quickcheck -v {}'.format(samtools, out_file),
"Check for valid merged BAM after transfer")
_finalize_merge(out_file, bam_files, data["config"])
bam.index(out_file, data["config"])
return out_file
def _run_qualimap(bam_file, data, out_dir):
"""Run qualimap to assess alignment quality metrics.
"""
report_file = os.path.join(out_dir, "qualimapReport.html")
if not os.path.exists(report_file):
utils.safe_makedir(out_dir)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
qualimap = config_utils.get_program("qualimap", data["config"])
resources = config_utils.get_resources("qualimap", data["config"])
max_mem = config_utils.adjust_memory(resources.get("memory", "1G"),
num_cores)
cmd = ("unset DISPLAY && {qualimap} bamqc -bam {bam_file} -outdir {out_dir} "
"-nt {num_cores} --java-mem-size={max_mem}")
species = data["genome_resources"]["aliases"].get("ensembl", "").upper()
if species in ["HUMAN", "MOUSE"]:
cmd += " -gd {species}"
regions = data["config"]["algorithm"].get("variant_regions")
if regions:
bed6_regions = _bed_to_bed6(regions, out_dir)
cmd += " -gff {bed6_regions}"
do.run(cmd.format(**locals()), "Qualimap: %s" % data["name"][-1])
return _parse_qualimap_metrics(report_file)
