def align(fastq_file, pair_file, ref_file, names, align_dir, data):
paired = True if pair_file else False
hisat2 = config_utils.get_program("hisat2", data)
num_cores = dd.get_num_cores(data)
quality_flag = _get_quality_flag(data)
stranded_flag = _get_stranded_flag(data, paired)
rg_flags = _get_rg_flags(names)
out_file = os.path.join(align_dir, dd.get_lane(data)) + ".bam"
if file_exists(out_file):
data = dd.set_work_bam(data, out_file)
return data
cmd = (
"{hisat2} -x {ref_file} -p {num_cores} {quality_flag} {stranded_flag} "
"{rg_flags} ")
if paired:
cmd += "-1 {fastq_file} -2 {pair_file} "
else:
cmd += "-U {fastq_file} "
if dd.get_analysis(data).lower() == "smallrna-seq":
cmd += "-k 1000 "
# if assembling transcripts, set flags that cufflinks/stringtie can use
if dd.get_transcript_assembler(data):
cmd += "--dta-cufflinks "
if dd.get_analysis(data).lower() == "rna-seq":
gtf_file = dd.get_gtf_file(data)
splicesites = os.path.join(os.path.dirname(gtf_file),
"ref-transcripts-splicesites.txt")
cmd += "--known-splicesite-infile {splicesites} "
message = "Aligning %s and %s with hisat2." % (fastq_file, pair_file)
with file_transaction(out_file) as tx_out_file:
cmd += " | " + postalign.sam_to_sortbam_cl(data, tx_out_file)
do.run(cmd.format(**locals()), message)
data = dd.set_work_bam(data, out_file)
return data
def dedup_bismark(data):
"""Remove alignments to the same position in the genome from the Bismark
mapping output using deduplicate_bismark
"""
config = data["config"]
input_file = datadict.get_work_bam(data)
# don't sort even by read names
# input_file = bam.sort(input_file, config, order="queryname")
sample_name = datadict.get_sample_name(data)
output_dir = os.path.join(datadict.get_work_dir(data), 'dedup',
sample_name)
output_dir = utils.safe_makedir(output_dir)
input_file_name, input_file_extension = os.path.splitext(os.path.basename(
input_file
))
output_file = os.path.join(
output_dir, f'{input_file_name}.deduplicated{input_file_extension}'
)
if utils.file_exists(output_file):
data = datadict.set_work_bam(data, output_file)
return [[data]]
deduplicate_bismark = config_utils.get_program('deduplicate_bismark', config)
command = f'{deduplicate_bismark} --output_dir {output_dir} {input_file}'
with transaction.file_transaction(output_dir):
do.run(command, 'remove deduplicate alignments')
data = datadict.set_work_bam(data, output_file)
data["deduplication_report"] = output_file.replace("deduplicated.bam", "deduplication_report.txt")
return [[data]]
def align(fastq_file, pair_file, ref_file, names, align_dir, data):
assert data["analysis"].lower().startswith("wgbs-seq"), "No comparible alignment"
config = data["config"]
sample = dd.get_sample_name(data)
out_prefix = os.path.join(align_dir, dd.get_lane(data))
ref_file = dd.get_sam_ref(data)
final_out = os.path.join(align_dir, "{0}.bam".format(sample))
if file_exists(final_out):
data = dd.set_work_bam(data, final_out)
return data
bsmap = config_utils.get_program("bsmap", config)
fastq_files = " -a %s" % fastq_file
num_cores = dd.get_num_cores(data)
num_cores = "-p %d" % num_cores
safe_makedir(align_dir)
cmd = "{bsmap} {num_cores} -w 100 -v 0.07 -m 10 -x 300 -o {tx_out_bam} -d {ref_file} {fastq_files}"
if pair_file:
fastq_files = "-a %s -b %s" % (fastq_file, pair_file)
if not final_out:
with file_transaction(final_out) as tx_out_bam:
run_message = "Running BSMAP aligner on %s and %s" % (fastq_file, ref_file)
do.run(cmd.format(**locals()), run_message, None)
data = dd.set_work_bam(data, final_out)
return data
def align(fastq_file, pair_file, ref_file, names, align_dir, data):
paired = True if pair_file else False
hisat2 = config_utils.get_program("hisat2", data)
num_cores = dd.get_num_cores(data)
quality_flag = _get_quality_flag(data)
stranded_flag = _get_stranded_flag(data, paired)
rg_flags = _get_rg_flags(names)
out_file = os.path.join(align_dir, dd.get_lane(data)) + ".bam"
if file_exists(out_file):
data = dd.set_work_bam(data, out_file)
return data
cmd = ("{hisat2} -x {ref_file} -p {num_cores} {quality_flag} {stranded_flag} "
"{rg_flags} ")
if paired:
cmd += "-1 {fastq_file} -2 {pair_file} "
else:
cmd += "-U {fastq_file} "
if dd.get_analysis(data).lower() == "smallrna-seq":
cmd += "-k 1000 "
# if assembling transcripts, set flags that cufflinks can use
if dd.get_assemble_transcripts(data):
cmd += "--dta-cufflinks "
if dd.get_analysis(data) == "rna-seq":
splicesites = os.path.join(os.path.dirname(gtf_file),
"ref-transcripts-splicesites.txt")
cmd += "--known-splicesite-infile {splicesites} "
message = "Aligning %s and %s with hisat2." %(fastq_file, pair_file)
with file_transaction(out_file) as tx_out_file:
cmd += " | " + postalign.sam_to_sortbam_cl(data, tx_out_file)
do.run(cmd.format(**locals()), message)
data = dd.set_work_bam(data, out_file)
return data
def align(fastq_file, pair_file, ref_file, names, align_dir, data):
assert data["analysis"].lower().startswith("wgbs-seq"), "No comparible alignment."
config = data["config"]
sample = dd.get_sample_name(data)
out_prefix = os.path.join(align_dir, dd.get_lane(data))
out_dir = os.path.join(align_dir, "%s_bismark" % dd.get_lane(data))
if not ref_file:
logger.error("bismark index not found. You can install "
"the index for your genome with: bcbio_nextgen.py upgrade "
"--aligners bismark --genomes genome-build-name --data")
sys.exit(1)
final_out = os.path.join(align_dir, "{0}.bam".format(sample))
if file_exists(final_out):
data = dd.set_work_bam(data, final_out)
data["bam_report"] = glob.glob(os.path.join(out_dir, "*report.txt"))[0]
data = dd.update_summary_qc(data, "bismark", base=data["bam_report"])
return data
bismark = config_utils.get_program("bismark", config)
# bismark uses 5 threads/sample and ~12GB RAM/sample (hg38)
resources = config_utils.get_resources("bismark", data["config"])
max_cores = dd.get_num_cores(data)
max_mem = config_utils.convert_to_bytes(resources.get("memory", "1G")) / (1024.0 * 1024.0)
instances = calculate_bismark_instances(max_cores, max_mem * max_cores)
# override instances if specified in the config
if resources and resources.get("bismark_threads"):
instances = resources.get("bismark_threads")
logger.info(f"Using {instances} bismark instances - overriden by resources")
bowtie_threads = 1
if resources and resources.get("bowtie_threads"):
bowtie_threads = resources.get("bowtie_threads")
logger.info(f"Using {bowtie_threads} bowtie threads per bismark instance")
kit = kits.KITS.get(dd.get_kit(data), None)
directional = "--non_directional" if kit and not kit.is_directional else ""
other_opts = resources.get("options", [])
other_opts = " ".join([str(x) for x in other_opts]).strip()
fastq_files = " ".join([fastq_file, pair_file]) if pair_file else fastq_file
safe_makedir(align_dir)
cmd = "{bismark} {other_opts} {directional} --bowtie2 --temp_dir {tx_out_dir} --gzip --parallel {instances} -p {bowtie_threads} -o {tx_out_dir} --unmapped {ref_file} {fastq_file} "
if pair_file:
fastq_file = "-1 %s -2 %s" % (fastq_file, pair_file)
raw_bam = glob.glob(out_dir + "/*bismark*bt2*bam")
if not raw_bam:
with tx_tmpdir() as tx_out_dir:
run_message = "Running Bismark aligner on %s and %s" % (fastq_file, ref_file)
do.run(cmd.format(**locals()), run_message, None)
shutil.move(tx_out_dir, out_dir)
raw_bam = glob.glob(out_dir + "/*bismark*bt2*bam")
# don't process bam in the bismark pipeline!
utils.symlink_plus(raw_bam[0], final_out)
data = dd.set_work_bam(data, final_out)
data["bam_report"] = glob.glob(os.path.join(out_dir, "*report.txt"))[0]
data = dd.update_summary_qc(data, "bismark", base=data["bam_report"])
return data
def align(fastq_file, pair_file, ref_file, names, align_dir, data):
assert data["analysis"].lower().startswith(
"wgbs-seq"), "No comparible alignment."
config = data["config"]
sample = dd.get_sample_name(data)
out_prefix = os.path.join(align_dir, dd.get_lane(data))
out_dir = os.path.join(align_dir, "%s_bismark" % dd.get_lane(data))
if not ref_file:
logger.error(
"bismark index not found. We don't provide the STAR indexes "
"by default because they are very large. You can install "
"the index for your genome with: bcbio_nextgen.py upgrade "
"--aligners bismark --genomes genome-build-name --data")
sys.exit(1)
final_out = os.path.join(align_dir, "{0}.bam".format(sample))
if file_exists(final_out):
data = dd.set_work_bam(data, final_out)
data["bam_report"] = glob.glob(os.path.join(out_dir, "*report.txt"))[0]
return data
bismark = config_utils.get_program("bismark", config)
# bismark uses 5 threads/sample and ~12GB RAM/sample (hg38)
resources = config_utils.get_resources("bismark", data["config"])
max_cores = resources.get("cores", 1)
max_mem = config_utils.convert_to_bytes(resources.get("memory", "1G"))
n = min(max(int(max_cores / 5), 1),
max(int(max_mem / config_utils.convert_to_bytes("12G")), 1))
kit = kits.KITS.get(dd.get_kit(data), None)
directional = "--non_directional" if kit and not kit.is_directional else ""
other_opts = resources.get("options", [])
other_opts = " ".join([str(x) for x in other_opts]).strip()
fastq_files = " ".join([fastq_file, pair_file
]) if pair_file else fastq_file
safe_makedir(align_dir)
cmd = "{bismark} {other_opts} {directional} --bowtie2 --temp_dir {tx_out_dir} --gzip --multicore {n} -o {tx_out_dir} --unmapped {ref_file} {fastq_file}"
if pair_file:
fastq_file = "-1 %s -2 %s" % (fastq_file, pair_file)
raw_bam = glob.glob(out_dir + "/*bismark*bt2*bam")
if not raw_bam:
with tx_tmpdir() as tx_out_dir:
run_message = "Running Bismark aligner on %s and %s" % (fastq_file,
ref_file)
do.run(cmd.format(**locals()), run_message, None)
shutil.move(tx_out_dir, out_dir)
raw_bam = glob.glob(out_dir + "/*bismark*bt2*bam")
process_bam = _process_bam(raw_bam[0], fastq_files, sample,
dd.get_sam_ref(data), config)
utils.symlink_plus(process_bam, final_out)
data = dd.set_work_bam(data, final_out)
data["bam_report"] = glob.glob(os.path.join(out_dir, "*report.txt"))[0]
return data
def _update_data(align_file, out_dir, names, data):
data = dd.set_work_bam(data, align_file)
data = dd.set_align_bam(data, align_file)
if dd.get_transcriptome_align(data) and not is_transcriptome_broken():
transcriptome_file = _move_transcriptome_file(out_dir, names)
data = dd.set_transcriptome_bam(data, transcriptome_file)
return data
def _update_data(align_file, out_dir, names, data):
data = dd.set_work_bam(data, align_file)
data = dd.set_align_bam(data, align_file)
if dd.get_transcriptome_align(data) and not is_transcriptome_broken(data):
transcriptome_file = _move_transcriptome_file(out_dir, names)
data = dd.set_transcriptome_bam(data, transcriptome_file)
return data
def pipeline_summary(data):
"""Provide summary information on processing sample.
Handles standard and CWL (single QC output) cases.
"""
data = utils.to_single_data(data)
if data["analysis"].startswith("wgbs-seq"):
bismark_bam = dd.get_align_bam(data)
sorted_bam = bam.sort(bismark_bam, data["config"])
data = dd.set_align_bam(data, sorted_bam)
data = dd.set_work_bam(data, bismark_bam)
work_bam = dd.get_align_bam(data) or dd.get_work_bam(data)
if not work_bam or not work_bam.endswith(".bam"):
work_bam = None
if dd.get_ref_file(data):
if work_bam or (tz.get_in(["config", "algorithm", "kraken"],
data)): # kraken doesn't need bam
logger.info("QC: %s %s" % (dd.get_sample_name(data), ", ".join(
dd.get_algorithm_qc(data))))
work_data = cwlutils.unpack_tarballs(utils.deepish_copy(data),
data)
data["summary"] = _run_qc_tools(work_bam, work_data)
if (len(dd.get_algorithm_qc(data)) == 1
and "output_cwl_keys" in data):
data["summary"]["qc"] = data["summary"]["qc"].get(
dd.get_algorithm_qc(data)[0])
return [[data]]
def test_bcbio_dexseq(self):
data = dd.set_sample_name({}, "test")
data = dd.set_work_bam(data, test_data.BAM_FILE)
data = dd.set_work_dir(data, self.out_dir)
data = dd.set_dexseq_gff(data, test_data.DEXSEQ_GFF)
data = dd.set_strandedness(data, "unstranded")
out_file = dexseq.bcbio_run(data)
self.assertTrue(file_exists(out_file))
def test_bcbio_dexseq(self):
data = dd.set_sample_name({}, "test")
data = dd.set_work_bam(data, test_data.BAM_FILE)
data = dd.set_work_dir(data, self.out_dir)
data = dd.set_dexseq_gff(data, test_data.DEXSEQ_GFF)
data = dd.set_strandedness(data, "unstranded")
out_file = dexseq.bcbio_run(data)
self.assertTrue(file_exists(out_file))
def align(fastq_file, pair_file, ref_file, names, align_dir, data):
assert data["analysis"].lower().startswith(
"wgbs-seq"), "No comparible alignment."
config = data["config"]
sample = dd.get_sample_name(data)
out_prefix = os.path.join(align_dir, dd.get_lane(data))
out_dir = os.path.join(align_dir, "%s_bismark" % dd.get_lane(data))
if not ref_file:
logger.error(
"bismark index not found. We don't provide the STAR indexes "
"by default because they are very large. You can install "
"the index for your genome with: bcbio_nextgen.py upgrade "
"--aligners bismark --genomes genome-build-name --data")
sys.exit(1)
final_out = os.path.join(align_dir, "{0}.bam".format(sample))
if file_exists(final_out):
data = dd.set_work_bam(data, final_out)
data["bam_report"] = glob.glob(os.path.join(out_dir, "*report.txt"))[0]
return data
bismark = config_utils.get_program("bismark", config)
fastq_files = " ".join([fastq_file, pair_file
]) if pair_file else fastq_file
num_cores = dd.get_num_cores(data)
n = 1 if num_cores < 5 else 2
safe_makedir(align_dir)
cmd = "{bismark} --bowtie2 --temp_dir {tx_out_dir} --gzip --multicore {n} -o {tx_out_dir} --unmapped {ref_file} {fastq_file}"
if pair_file:
fastq_file = "-1 %s -2 %s" % (fastq_file, pair_file)
raw_bam = glob.glob(out_dir + "/*bismark*bt2*bam")
if not raw_bam:
with tx_tmpdir() as tx_out_dir:
run_message = "Running Bismark aligner on %s and %s" % (fastq_file,
ref_file)
do.run(cmd.format(**locals()), run_message, None)
shutil.move(tx_out_dir, out_dir)
raw_bam = glob.glob(out_dir + "/*bismark*bt2*bam")
process_bam = _process_bam(raw_bam[0], fastq_files, sample,
dd.get_sam_ref(data), config)
utils.symlink_plus(process_bam, final_out)
data = dd.set_work_bam(data, final_out)
data["bam_report"] = glob.glob(os.path.join(out_dir, "*report.txt"))[0]
return data
def _update_data(align_file, out_dir, names, data):
data = dd.set_work_bam(data, align_file)
data = dd.set_align_bam(data, align_file)
transcriptome_file = _move_transcriptome_file(out_dir, names)
data = dd.set_transcriptome_bam(data, transcriptome_file)
sjfile = get_splicejunction_file(out_dir, data)
sjbed = junction2bed(sjfile)
data = dd.set_junction_bed(data, sjbed)
return data
def _update_data(align_file, out_dir, names, data):
data = dd.set_work_bam(data, align_file)
data = dd.set_align_bam(data, align_file)
transcriptome_file = _move_transcriptome_file(out_dir, names)
data = dd.set_transcriptome_bam(data, transcriptome_file)
sjfile = get_splicejunction_file(out_dir, data)
if sjfile:
sjbed = junction2bed(sjfile)
data = dd.set_junction_bed(data, sjbed)
return data
def fix_umi_dragen_bam(data, bam=None):
"""
fixes the UMI BAM from DRAGEN. Accepts a pre UMI collapsed BAM file and
adds several missing tags needed to use fgbio's UMI tools
"""
if not bam:
bam = dd.get_work_bam(data)
base, ext = os.path.splitext(bam)
sample_name = dd.get_sample_name(data)
out_bam = os.path.join(dd.get_work_dir(data), "align", sample_name,
sample_name + "-fgbio" + ext)
out_bam = add_fgbio_tags(bam, out_bam, data)
data = dd.set_work_bam(data, out_bam)
return data
def align(fastq_file, pair_file, ref_file, names, align_dir, data):
paired = True if pair_file else False
hisat2 = config_utils.get_program("hisat2", data)
num_cores = dd.get_num_cores(data)
quality_flag = _get_quality_flag(data)
stranded_flag = _get_stranded_flag(data, paired)
rg_flags = _get_rg_flags(names)
out_file = os.path.join(align_dir,
"{0}-sort.bam".format(dd.get_sample_name(data)))
if data.get("align_split"):
final_file = out_file
out_file, data = alignprep.setup_combine(final_file, data)
fastq_file, pair_file = alignprep.split_namedpipe_cls(
fastq_file, pair_file, data)
else:
final_file = None
if not file_exists(out_file) and (final_file is None
or not file_exists(final_file)):
cmd = (
"{hisat2} --new-summary -x {ref_file} -p {num_cores} {quality_flag} {stranded_flag} "
"{rg_flags} ")
if paired:
cmd += "-1 {fastq_file} -2 {pair_file} "
else:
cmd += "-U {fastq_file} "
if dd.get_analysis(data).lower() == "smallrna-seq":
cmd += "-k 1000 "
# if assembling transcripts, set flags that cufflinks/stringtie can use
if dd.get_transcript_assembler(data):
cmd += "--dta-cufflinks "
if dd.get_analysis(data).lower() == "rna-seq":
splicesites = get_known_splicesites_file(align_dir, data)
if file_exists(splicesites):
cmd += "--known-splicesite-infile {splicesites} "
novel_splicesite_file = os.path.join(
align_dir,
"{0}-novelsplicesites.bed".format(dd.get_sample_name(data)))
cmd += "--novel-splicesite-outfile {novel_splicesite_file} "
# apply additional hisat2 options
cmd += " ".join(_get_options_from_config(data))
message = "Aligning %s and %s with hisat2." % (fastq_file, pair_file)
with postalign.tobam_cl(data, out_file, pair_file
is not None) as (tobam_cl, tx_out_file):
cmd += " | " + tobam_cl
do.run(cmd.format(**locals()), message)
data = dd.set_work_bam(data, out_file)
junctionbed = get_splicejunction_file(align_dir, data)
data = dd.set_junction_bed(data, junctionbed)
return data
def run_rapmap_pseudoalign(data):
samplename = dd.get_sample_name(data)
files = dd.get_input_sequence_files(data)
work_dir = dd.get_work_dir(data)
if len(files) == 2:
fq1, fq2 = files
else:
fq1, fq2 = files[0], None
rapmap_dir = os.path.join(work_dir, "rapmap", samplename)
gtf_file = dd.get_gtf_file(data)
assert file_exists(gtf_file), "%s was not found, exiting." % gtf_file
fasta_file = dd.get_ref_file(data)
assert file_exists(fasta_file), "%s was not found, exiting." % fasta_file
out_file = rapmap_pseudoalign(fq1, fq2, rapmap_dir, gtf_file, fasta_file,
data)
data = dd.set_work_bam(data, out_file)
data = dd.set_transcriptome_bam(data, out_file)
return data
def run_rapmap_pseudoalign(data):
samplename = dd.get_sample_name(data)
files = dd.get_input_sequence_files(data)
work_dir = dd.get_work_dir(data)
if len(files) == 2:
fq1, fq2 = files
else:
fq1, fq2 = files[0], None
rapmap_dir = os.path.join(work_dir, "rapmap", samplename)
gtf_file = dd.get_gtf_file(data)
assert file_exists(gtf_file), "%s was not found, exiting." % gtf_file
fasta_file = dd.get_ref_file(data)
assert file_exists(fasta_file), "%s was not found, exiting." % fasta_file
out_file = rapmap_pseudoalign(fq1, fq2, rapmap_dir, gtf_file, fasta_file,
data)
data = dd.set_work_bam(data, out_file)
data = dd.set_transcriptome_bam(data, out_file)
return data
def align(fastq_file, pair_file, ref_file, names, align_dir, data):
paired = True if pair_file else False
hisat2 = config_utils.get_program("hisat2", data)
num_cores = dd.get_num_cores(data)
quality_flag = _get_quality_flag(data)
stranded_flag = _get_stranded_flag(data, paired)
rg_flags = _get_rg_flags(names)
out_file = os.path.join(align_dir, "{0}-sort.bam".format(dd.get_sample_name(data)))
if data.get("align_split"):
final_file = out_file
out_file, data = alignprep.setup_combine(final_file, data)
fastq_file, pair_file = alignprep.split_namedpipe_cls(fastq_file, pair_file, data)
else:
final_file = None
if not file_exists(out_file) and (final_file is None or not file_exists(final_file)):
cmd = ("{hisat2} --new-summary -x {ref_file} -p {num_cores} {quality_flag} {stranded_flag} "
"{rg_flags} ")
if paired:
cmd += "-1 {fastq_file} -2 {pair_file} "
else:
cmd += "-U {fastq_file} "
if dd.get_analysis(data).lower() == "smallrna-seq":
cmd += "-k 1000 "
# if assembling transcripts, set flags that cufflinks/stringtie can use
if dd.get_transcript_assembler(data):
cmd += "--dta-cufflinks "
if dd.get_analysis(data).lower() == "rna-seq":
splicesites = get_known_splicesites_file(align_dir, data)
if file_exists(splicesites):
cmd += "--known-splicesite-infile {splicesites} "
novel_splicesite_file = os.path.join(align_dir, "{0}-novelsplicesites.bed".format(dd.get_sample_name(data)))
cmd += "--novel-splicesite-outfile {novel_splicesite_file} "
# apply additional hisat2 options
cmd += " ".join(_get_options_from_config(data))
message = "Aligning %s and %s with hisat2." % (fastq_file, pair_file)
with postalign.tobam_cl(data, out_file, pair_file is not None) as (tobam_cl, tx_out_file):
cmd += " | " + tobam_cl
do.run(cmd.format(**locals()), message)
data = dd.set_work_bam(data, out_file)
junctionbed = get_splicejunction_file(align_dir, data)
data = dd.set_junction_bed(data, junctionbed)
return data
def _update_data(align_file, out_dir, names, data):
data = dd.set_work_bam(data, align_file)
data = dd.set_align_bam(data, align_file)
transcriptome_file = _move_transcriptome_file(out_dir, names)
data = dd.set_transcriptome_bam(data, transcriptome_file)
return data
def _update_data(align_file, out_dir, names, data):
data = dd.set_work_bam(data, align_file)
data = dd.set_align_bam(data, align_file)
transcriptome_file = _move_transcriptome_file(out_dir, names)
data = dd.set_transcriptome_bam(data, transcriptome_file)
return data
