def mito(args):
"""
%prog mito chrM.fa input.bam
Identify mitochondrial deletions.
"""
p = OptionParser(mito.__doc__)
p.set_aws_opts(store="hli-mv-data-science/htang/mito-deletions")
p.add_option("--realignonly", default=False, action="store_true",
help="Realign only")
p.add_option("--svonly", default=False, action="store_true",
help="Run Realign => SV calls only")
p.add_option("--support", default=1, type="int",
help="Minimum number of supporting reads")
p.set_home("speedseq", default="/mnt/software/speedseq/bin")
p.set_cpus()
opts, args = p.parse_args(args)
if len(args) != 2:
sys.exit(not p.print_help())
chrMfa, bamfile = args
store = opts.output_path
cleanup = not opts.nocleanup
if not op.exists(chrMfa):
logging.debug("File `{}` missing. Exiting.".format(chrMfa))
return
chrMfai = chrMfa + ".fai"
if not op.exists(chrMfai):
cmd = "samtools index {}".format(chrMfa)
sh(cmd)
if not bamfile.endswith(".bam"):
bamfiles = [x.strip() for x in open(bamfile)]
else:
bamfiles = [bamfile]
if store:
computed = ls_s3(store)
computed = [op.basename(x).split('.')[0] for x in computed if \
x.endswith(".depth")]
remaining_samples = [x for x in bamfiles \
if op.basename(x).split(".")[0] not in computed]
logging.debug("Already computed on `{}`: {}".\
format(store, len(bamfiles) - len(remaining_samples)))
bamfiles = remaining_samples
logging.debug("Total samples: {}".format(len(bamfiles)))
for bamfile in bamfiles:
run_mito(chrMfa, bamfile, opts,
realignonly=opts.realignonly,
svonly=opts.svonly,
store=store, cleanup=cleanup)
def batchlobstr(args):
"""
%prog batchlobstr samples.csv
Run lobSTR sequentially on list of samples. Each line contains:
sample-name,s3-location
"""
p = OptionParser(batchlobstr.__doc__)
p.add_option("--sep", default=",", help="Separator for building commandline")
p.set_home("lobstr", default="s3://hli-mv-data-science/htang/str-build/lobSTR/")
p.set_aws_opts(store="hli-mv-data-science/htang/str-data")
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
(samplesfile,) = args
store = opts.output_path
computed = ls_s3(store)
fp = open(samplesfile)
skipped = total = 0
for row in fp:
total += 1
sample, s3file = row.strip().split(",")[:2]
exec_id, sample_id = sample.split("_")
bamfile = s3file.replace(".gz", "").replace(".vcf", ".bam")
gzfile = sample + ".{0}.vcf.gz".format("hg38")
if gzfile in computed:
skipped += 1
continue
print(
opts.sep.join(
"python -m jcvi.variation.str lobstr".split()
+ [
"hg38",
"--input_bam_path",
bamfile,
"--output_path",
store,
"--sample_id",
sample_id,
"--workflow_execution_id",
exec_id,
"--lobstr_home",
opts.lobstr_home,
"--workdir",
opts.workdir,
]
)
)
fp.close()
logging.debug("Total skipped: {0}".format(percentage(skipped, total)))
def batchlobstr(args):
"""
%prog batchlobstr samples.csv
Run lobSTR sequentially on list of samples. Each line contains:
sample-name,s3-location
"""
p = OptionParser(batchlobstr.__doc__)
p.add_option("--sep", default=",", help="Separator for building commandline")
p.set_home("lobstr", default="s3://hli-mv-data-science/htang/str-build/lobSTR/")
p.set_aws_opts(store="hli-mv-data-science/htang/str-data")
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
samplesfile, = args
store = opts.output_path
computed = ls_s3(store)
fp = open(samplesfile)
skipped = total = 0
for row in fp:
total += 1
sample, s3file = row.strip().split(",")[:2]
exec_id, sample_id = sample.split("_")
bamfile = s3file.replace(".gz", "").replace(".vcf", ".bam")
gzfile = sample + ".{0}.vcf.gz".format("hg38")
if gzfile in computed:
skipped += 1
continue
print opts.sep.join(
"python -m jcvi.variation.str lobstr".split()
+ [
"hg38",
"--input_bam_path",
bamfile,
"--output_path",
store,
"--sample_id",
sample_id,
"--workflow_execution_id",
exec_id,
"--lobstr_home",
opts.lobstr_home,
"--workdir",
opts.workdir,
]
)
fp.close()
logging.debug("Total skipped: {0}".format(percentage(skipped, total)))
def batchlobstr(args):
"""
%prog batchlobstr samples.csv
Run lobSTR sequentially on list of samples. Each line contains:
sample-name,s3-location
"""
p = OptionParser(batchlobstr.__doc__)
p.add_option("--sep",
default=",",
help="Separator for building commandline")
p.set_aws_opts(store="hli-mv-data-science/htang/str")
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
samplesfile, = args
store = opts.store
computed = ls_s3(store)
fp = open(samplesfile)
skipped = total = 0
for row in fp:
total += 1
sample, s3file = row.strip().split(",")[:2]
bamfile = s3file.replace(".gz", "").replace(".vcf", ".bam")
gzfile = sample + ".{0}.vcf.gz".format("hg38")
if gzfile in computed:
skipped += 1
continue
print opts.sep.join("python -m jcvi.variation.str lobstr".split() + \
[bamfile, "hg38", "--prefix", sample,
"--workdir", opts.workdir, "--cleanup",
"--store", opts.store])
fp.close()
logging.debug("Total skipped: {0}".format(percentage(skipped, total)))
