def filtervcf(args):
"""
%prog filtervcf NA12878.hg38.vcf.gz
Filter lobSTR VCF using script shipped in lobSTR. Input file can be a list
of vcf files.
"""
p = OptionParser(filtervcf.__doc__)
p.set_home("lobstr", default="/mnt/software/lobSTR")
p.set_aws_opts(store="hli-mv-data-science/htang/str")
p.set_cpus()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
samples, = args
lhome = opts.lobstr_home
store = opts.output_path
if samples.endswith((".vcf", ".vcf.gz")):
vcffiles = [samples]
else:
vcffiles = [x.strip() for x in must_open(samples)]
vcffiles = [x for x in vcffiles if ".filtered." not in x]
run_args = [(x, lhome, x.startswith("s3://") and store) for x in vcffiles]
cpus = min(opts.cpus, len(run_args))
p = Pool(processes=cpus)
for res in p.map_async(run_filter, run_args).get():
continue
def filtervcf(args):
"""
%prog filtervcf NA12878.hg38.vcf.gz
Filter lobSTR VCF using script shipped in lobSTR. Input file can be a list
of vcf files.
"""
p = OptionParser(filtervcf.__doc__)
p.set_home("lobstr", default="/mnt/software/lobSTR")
p.set_aws_opts(store="hli-mv-data-science/htang/str")
p.set_cpus()
opts, args = p.parse_args(args)
if len(args) != 1:
sys.exit(not p.print_help())
samples, = args
lhome = opts.lobstr_home
store = opts.output_path
if samples.endswith((".vcf", ".vcf.gz")):
vcffiles = [samples]
else:
vcffiles = [x.strip() for x in must_open(samples)]
vcffiles = [x for x in vcffiles if ".filtered." not in x]
run_args = [(x, lhome, x.startswith("s3://") and store) for x in vcffiles]
cpus = min(opts.cpus, len(run_args))
p = Pool(processes=cpus)
for res in p.map_async(run_filter, run_args).get():
continue
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 compilevcf(args):
"""
%prog compilevcf samples.csv
Compile vcf results into master spreadsheet.
"""
p = OptionParser(compilevcf.__doc__)
p.add_option("--db", default="hg38", help="Use these lobSTR db")
p.add_option(
"--nofilter",
default=False,
action="store_true",
help="Do not filter the variants",
)
p.set_home("lobstr")
p.set_cpus()
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())
(samples, ) = args
workdir = opts.workdir
store = opts.output_path
cleanup = not opts.nocleanup
filtered = not opts.nofilter
dbs = opts.db.split(",")
cwd = os.getcwd()
mkdir(workdir)
os.chdir(workdir)
samples = op.join(cwd, samples)
stridsfile = "STR.ids"
if samples.endswith((".vcf", ".vcf.gz")):
vcffiles = [samples]
else:
vcffiles = [x.strip() for x in must_open(samples)]
if not op.exists(stridsfile):
ids = []
for db in dbs:
ids.extend(STRFile(opts.lobstr_home, db=db).ids)
uids = uniqify(ids)
logging.debug("Combined: {} Unique: {}".format(len(ids), len(uids)))
fw = open(stridsfile, "w")
print("\n".join(uids), file=fw)
fw.close()
run_args = [(x, filtered, cleanup, store) for x in vcffiles]
cpus = min(opts.cpus, len(run_args))
p = Pool(processes=cpus)
for _ in p.map_async(run_compile, run_args).get():
continue
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 compile(args):
"""
%prog compile samples.csv
Compile vcf results into master spreadsheet.
"""
from multiprocessing import Pool
p = OptionParser(compile.__doc__)
p.add_option("--db", default="hg38,hg38-named",
help="Use these lobSTR db")
p.set_home("lobstr")
p.set_cpus()
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())
samples, = args
workdir = opts.workdir
dbs = opts.db.split(",")
mkdir(workdir)
os.chdir(workdir)
stridsfile = "STR.ids"
vcffiles = [x.strip() for x in must_open(samples)]
if not op.exists(stridsfile):
ids = []
for db in dbs:
ids.extend(STRFile(opts.lobstr_home, db=db).ids)
uids = uniqify(ids)
logging.debug("Combined: {} Unique: {}".format(len(ids), len(uids)))
fw = open(stridsfile, "w")
print >> fw, "\n".join(uids)
fw.close()
# Generate two alleles
dipuids = []
for uid in uids:
dipuids.extend([uid + ".1", uid + ".2"])
fw = open("header.ids", "w")
print >> fw, ",".join(dipuids)
fw.close()
p = Pool(processes=opts.cpus)
run_args = [(x, opts.store, opts.cleanup) for x in vcffiles]
#run(run_args[0])
for res in p.map_async(run, run_args).get():
continue
def compilevcf(args):
"""
%prog compilevcf samples.csv
Compile vcf results into master spreadsheet.
"""
p = OptionParser(compilevcf.__doc__)
p.add_option("--db", default="hg38", help="Use these lobSTR db")
p.add_option("--nofilter", default=False, action="store_true",
help="Do not filter the variants")
p.set_home("lobstr")
p.set_cpus()
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())
samples, = args
workdir = opts.workdir
store = opts.output_path
cleanup = not opts.nocleanup
filtered = not opts.nofilter
dbs = opts.db.split(",")
cwd = os.getcwd()
mkdir(workdir)
os.chdir(workdir)
samples = op.join(cwd, samples)
stridsfile = "STR.ids"
if samples.endswith((".vcf", ".vcf.gz")):
vcffiles = [samples]
else:
vcffiles = [x.strip() for x in must_open(samples)]
if not op.exists(stridsfile):
ids = []
for db in dbs:
ids.extend(STRFile(opts.lobstr_home, db=db).ids)
uids = uniqify(ids)
logging.debug("Combined: {} Unique: {}".format(len(ids), len(uids)))
fw = open(stridsfile, "w")
print >> fw, "\n".join(uids)
fw.close()
run_args = [(x, filtered, cleanup, store) for x in vcffiles]
cpus = min(opts.cpus, len(run_args))
p = Pool(processes=cpus)
for res in p.map_async(run_compile, run_args).get():
continue
def compile(args):
"""
%prog compile samples.csv
Compile vcf results into master spreadsheet.
"""
p = OptionParser(compile.__doc__)
p.add_option("--db", default="hg38", help="Use these lobSTR db")
p.set_home("lobstr")
p.set_cpus()
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())
samples, = args
workdir = opts.workdir
store = opts.output_path
cleanup = not opts.nocleanup
dbs = opts.db.split(",")
cwd = os.getcwd()
mkdir(workdir)
os.chdir(workdir)
samples = op.join(cwd, samples)
stridsfile = "STR.ids"
vcffiles = [x.strip() for x in must_open(samples)]
if not op.exists(stridsfile):
ids = []
for db in dbs:
ids.extend(STRFile(opts.lobstr_home, db=db).ids)
uids = uniqify(ids)
logging.debug("Combined: {} Unique: {}".format(len(ids), len(uids)))
fw = open(stridsfile, "w")
print >> fw, "\n".join(uids)
fw.close()
p = Pool(processes=opts.cpus)
run_args = [(x, store, cleanup) for x in vcffiles]
for res in p.map_async(run, run_args).get():
continue
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)))
def lobstr(args):
"""
%prog lobstr lobstr_index1 lobstr_index2 ...
Run lobSTR on a big BAM file. There can be multiple lobSTR indices. In
addition, bamfile can be S3 location and --lobstr_home can be S3 location
(e.g. s3://hli-mv-data-science/htang/str-build/lobSTR/)
"""
p = OptionParser(lobstr.__doc__)
p.add_option("--haploid",
default="chrY,chrM",
help="Use haploid model for these chromosomes")
p.add_option("--chr", help="Run only this chromosome")
p.add_option("--simulation",
default=False,
action="store_true",
help="Simulation mode")
p.set_home("lobstr",
default="s3://hli-mv-data-science/htang/str-build/lobSTR/")
p.set_cpus()
p.set_aws_opts(store="hli-mv-data-science/htang/str-data")
opts, args = p.parse_args(args)
bamfile = opts.input_bam_path
if len(args) < 1 or bamfile is None:
sys.exit(not p.print_help())
lbindices = args
if opts.simulation: # Simulation mode
cmd, vcf_file = allelotype_on_chr(bamfile,
"chr4",
"/mnt/software/lobSTR/",
"TREDs",
haploid=opts.haploid)
stats_file = vcf_file.rsplit(".", 1)[0] + ".allelotype.stats"
results_dir = "lobstr_results"
mkdir(results_dir)
sh(cmd)
sh("mv {} {}/ && rm {}".format(vcf_file, results_dir, stats_file))
return
s3mode = bamfile.startswith("s3")
store = opts.output_path
cleanup = not opts.nocleanup
workdir = opts.workdir
mkdir(workdir)
os.chdir(workdir)
lhome = opts.lobstr_home
if lhome.startswith("s3://"):
lhome = pull_from_s3(lhome, overwrite=False)
exec_id, sample_id = opts.workflow_execution_id, opts.sample_id
prefix = [x for x in (exec_id, sample_id) if x]
if prefix:
pf = "_".join(prefix)
else:
pf = bamfile.split("/")[-1].split(".")[0]
if s3mode:
gzfile = pf + ".{0}.vcf.gz".format(lbindices[-1])
remotegzfile = "{0}/{1}".format(store, gzfile)
if check_exists_s3(remotegzfile):
logging.debug("Object `{0}` exists. Computation skipped."\
.format(remotegzfile))
return
localbamfile = pf + ".bam"
localbaifile = localbamfile + ".bai"
if op.exists(localbamfile):
logging.debug("BAM file already downloaded.")
else:
pull_from_s3(bamfile, localbamfile)
if op.exists(localbaifile):
logging.debug("BAM index file already downloaded.")
else:
remotebaifile = bamfile + ".bai"
if check_exists_s3(remotebaifile):
pull_from_s3(remotebaifile, localbaifile)
else:
remotebaifile = bamfile.rsplit(".")[0] + ".bai"
if check_exists_s3(remotebaifile):
pull_from_s3(remotebaifile, localbaifile)
else:
logging.debug("BAM index cannot be found in S3!")
sh("samtools index {0}".format(localbamfile))
bamfile = localbamfile
chrs = [opts.chr] if opts.chr else (range(1, 23) + ["X", "Y"])
for lbidx in lbindices:
makefile = "makefile.{0}".format(lbidx)
mm = MakeManager(filename=makefile)
vcffiles = []
for chr in chrs:
cmd, vcffile = allelotype_on_chr(bamfile,
chr,
lhome,
lbidx,
haploid=opts.haploid)
mm.add(bamfile, vcffile, cmd)
filteredvcffile = vcffile.replace(".vcf", ".filtered.vcf")
cmd = "python -m jcvi.variation.str filtervcf {}".format(vcffile)
cmd += " --lobstr_home {}".format(lhome)
mm.add(vcffile, filteredvcffile, cmd)
vcffiles.append(filteredvcffile)
gzfile = bamfile.split(".")[0] + ".{0}.vcf.gz".format(lbidx)
cmd = "vcf-concat {0} | vcf-sort".format(" ".join(vcffiles))
cmd += " | bgzip -c > {0}".format(gzfile)
mm.add(vcffiles, gzfile, cmd)
mm.run(cpus=opts.cpus)
if s3mode:
push_to_s3(store, gzfile)
if cleanup:
mm.clean()
sh("rm -f {} {} *.bai *.stats".format(bamfile, mm.makefile))
def lobstr(args):
"""
%prog lobstr lobstr_index1 lobstr_index2 ...
Run lobSTR on a big BAM file. There can be multiple lobSTR indices. In
addition, bamfile can be S3 location and --lobstr_home can be S3 location
(e.g. s3://hli-mv-data-science/htang/str-build/lobSTR/)
"""
p = OptionParser(lobstr.__doc__)
p.add_option("--chr", help="Run only this chromosome")
p.set_home("lobstr", default="s3://hli-mv-data-science/htang/str-build/lobSTR/")
p.set_cpus()
p.set_aws_opts(store="hli-mv-data-science/htang/str-data")
opts, args = p.parse_args(args)
bamfile = opts.input_bam_path
if len(args) < 1 or bamfile is None:
sys.exit(not p.print_help())
lbindices = args
s3mode = bamfile.startswith("s3")
store = opts.output_path
cleanup = not opts.nocleanup
workdir = opts.workdir
mkdir(workdir)
os.chdir(workdir)
lhome = opts.lobstr_home
if lhome.startswith("s3://"):
lhome = pull_from_s3(lhome, overwrite=False)
exec_id, sample_id = opts.workflow_execution_id, opts.sample_id
prefix = [x for x in (exec_id, sample_id) if x]
if prefix:
pf = "_".join(prefix)
else:
pf = bamfile.split("/")[-1].split(".")[0]
if s3mode:
gzfile = pf + ".{0}.vcf.gz".format(lbindices[-1])
remotegzfile = "{0}/{1}".format(store, gzfile)
if check_exists_s3(remotegzfile):
logging.debug("Object `{0}` exists. Computation skipped."\
.format(remotegzfile))
return
localbamfile = pf + ".bam"
localbaifile = localbamfile + ".bai"
if op.exists(localbamfile):
logging.debug("BAM file already downloaded.")
else:
pull_from_s3(bamfile, localbamfile)
if op.exists(localbaifile):
logging.debug("BAM index file already downloaded.")
else:
remotebaifile = bamfile + ".bai"
if check_exists_s3(remotebaifile):
pull_from_s3(remotebaifile, localbaifile)
else:
remotebaifile = bamfile.rsplit(".")[0] + ".bai"
if check_exists_s3(remotebaifile):
pull_from_s3(remotebaifile, localbaifile)
else:
logging.debug("BAM index cannot be found in S3!")
sh("samtools index {0}".format(localbamfile))
bamfile = localbamfile
chrs = [opts.chr] if opts.chr else (range(1, 23) + ["X", "Y"])
for lbidx in lbindices:
makefile = "makefile.{0}".format(lbidx)
mm = MakeManager(filename=makefile)
vcffiles = []
for chr in chrs:
cmd, vcffile = allelotype_on_chr(bamfile, chr, lhome, lbidx)
mm.add(bamfile, vcffile, cmd)
filteredvcffile = vcffile.replace(".vcf", ".filtered.vcf")
cmd = "python -m jcvi.variation.str filtervcf {}".format(vcffile)
cmd += " --lobstr_home {}".format(lhome)
mm.add(vcffile, filteredvcffile, cmd)
vcffiles.append(filteredvcffile)
gzfile = bamfile.split(".")[0] + ".{0}.vcf.gz".format(lbidx)
cmd = "vcf-concat {0} | vcf-sort".format(" ".join(vcffiles))
cmd += " | bgzip -c > {0}".format(gzfile)
mm.add(vcffiles, gzfile, cmd)
mm.run(cpus=opts.cpus)
if s3mode:
push_to_s3(store, gzfile)
if cleanup:
mm.clean()
sh("rm -f {} {} *.bai *.stats".format(bamfile, mm.makefile))
def lobstr(args):
"""
%prog lobstr bamfile lobstr_index1 lobstr_index2 ...
Run lobSTR on a big BAM file. There can be multiple lobSTR indices.
"""
p = OptionParser(lobstr.__doc__)
p.add_option("--chr", help="Run only this chromosome")
p.add_option("--prefix", help="Use prefix file name")
p.set_home("lobstr")
p.set_cpus()
p.set_aws_opts(store="hli-mv-data-science/htang/str")
opts, args = p.parse_args(args)
if len(args) < 2:
sys.exit(not p.print_help())
bamfile = args[0]
lbindices = args[1:]
s3mode = bamfile.startswith("s3")
store = opts.store
workdir = opts.workdir
mkdir(workdir)
os.chdir(workdir)
pf = opts.prefix or bamfile.split("/")[-1].split(".")[0]
if s3mode:
gzfile = pf + ".{0}.vcf.gz".format(lbindices[-1])
remotegzfile = "s3://{0}/{1}".format(store, gzfile)
if check_exists_s3(remotegzfile):
logging.debug("Object `{0}` exists. Computation skipped."\
.format(remotegzfile))
return
localbamfile = pf + ".bam"
localbaifile = localbamfile + ".bai"
if op.exists(localbamfile):
logging.debug("BAM file already downloaded.")
else:
pull_from_s3(bamfile, localbamfile)
if op.exists(localbaifile):
logging.debug("BAM index file already downloaded.")
else:
remotebaifile = bamfile + ".bai"
if check_exists_s3(remotebaifile):
pull_from_s3(remotebaifile, localbaifile)
else:
remotebaifile = bamfile.rsplit(".")[0] + ".bai"
if check_exists_s3(remotebaifile):
pull_from_s3(remotebaifile, localbaifile)
else:
logging.debug("BAM index cannot be found in S3!")
sh("samtools index {0}".format(localbamfile))
bamfile = localbamfile
lhome = opts.lobstr_home
chrs = [opts.chr] if opts.chr else (range(1, 23) + ["X", "Y"])
for lbidx in lbindices:
mm = MakeManager(filename="makefile.{0}".format(lbidx))
vcffiles = []
for chr in chrs:
cmd, vcffile = allelotype_on_chr(bamfile, chr, lhome, lbidx)
mm.add(bamfile, vcffile, cmd)
vcffiles.append(vcffile)
gzfile = bamfile.split(".")[0] + ".{0}.vcf.gz".format(lbidx)
cmd = "vcf-concat {0} | vcf-sort".format(" ".join(vcffiles))
cmd += " | bgzip -c > {0}".format(gzfile)
mm.add(vcffiles, gzfile, cmd)
mm.run(cpus=opts.cpus)
if s3mode:
push_to_s3(store, gzfile)
if opts.cleanup:
sh("rm -f *")
def lobstr(args):
"""
%prog lobstr bamfile lobstr_index1 lobstr_index2 ...
Run lobSTR on a big BAM file. There can be multiple lobSTR indices.
"""
p = OptionParser(lobstr.__doc__)
p.add_option("--chr", help="Run only this chromosome")
p.add_option("--prefix", help="Use prefix file name")
p.set_home("lobstr")
p.set_cpus()
p.set_aws_opts(store="hli-mv-data-science/htang/str")
opts, args = p.parse_args(args)
if len(args) < 2:
sys.exit(not p.print_help())
bamfile = args[0]
lbindices = args[1:]
s3mode = bamfile.startswith("s3")
store = opts.store
workdir = opts.workdir
mkdir(workdir)
os.chdir(workdir)
pf = opts.prefix or bamfile.split("/")[-1].split(".")[0]
if s3mode:
gzfile = pf + ".{0}.vcf.gz".format(lbindices[-1])
remotegzfile = "s3://{0}/{1}".format(store, gzfile)
if check_exists_s3(remotegzfile):
logging.debug("Object `{0}` exists. Computation skipped."\
.format(remotegzfile))
return
localbamfile = pf + ".bam"
localbaifile = localbamfile + ".bai"
if op.exists(localbamfile):
logging.debug("BAM file already downloaded.")
else:
pull_from_s3(bamfile, localbamfile)
if op.exists(localbaifile):
logging.debug("BAM index file already downloaded.")
else:
remotebaifile = bamfile + ".bai"
if check_exists_s3(remotebaifile):
pull_from_s3(remotebaifile, localbaifile)
else:
remotebaifile = bamfile.rsplit(".")[0] + ".bai"
if check_exists_s3(remotebaifile):
pull_from_s3(remotebaifile, localbaifile)
else:
logging.debug("BAM index cannot be found in S3!")
sh("samtools index {0}".format(localbamfile))
bamfile = localbamfile
lhome = opts.lobstr_home
chrs = [opts.chr] if opts.chr else (range(1, 23) + ["X", "Y"])
for lbidx in lbindices:
mm = MakeManager(filename="makefile.{0}".format(lbidx))
vcffiles = []
for chr in chrs:
cmd, vcffile = allelotype_on_chr(bamfile, chr, lhome, lbidx)
mm.add(bamfile, vcffile, cmd)
vcffiles.append(vcffile)
gzfile = bamfile.split(".")[0] + ".{0}.vcf.gz".format(lbidx)
cmd = "vcf-concat {0} | vcf-sort".format(" ".join(vcffiles))
cmd += " | bgzip -c > {0}".format(gzfile)
mm.add(vcffiles, gzfile, cmd)
mm.run(cpus=opts.cpus)
if s3mode:
push_to_s3(store, gzfile)
if opts.cleanup:
sh("rm -f *")