def _run_kraken(data,ratio):
"""Run kraken, generating report in specified directory and parsing metrics.
Using only first paired reads.
"""
logger.info("Number of aligned reads < than 0.60 in %s: %s" % (str(data["name"]),ratio))
logger.info("Running kraken to determine contaminant: %s" % str(data["name"]))
qc_dir = utils.safe_makedir(os.path.join(data["dirs"]["work"], "qc", data["description"]))
kraken_out = os.path.join(qc_dir, "kraken")
stats = out = out_stats = None
db = data['config']["algorithm"]["kraken"]
if db == "minikraken":
db = os.path.join(_get_data_dir(),"genome","kraken","minikraken")
else:
if not os.path.exists(db):
logger.info("kraken: no database found %s, skipping" % db)
return {"kraken_report" : "null"}
if not os.path.exists(os.path.join(kraken_out,"kraken_out")):
work_dir = os.path.dirname(kraken_out)
utils.safe_makedir(work_dir)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
files = data["files"]
with utils.curdir_tmpdir(data, work_dir) as tx_tmp_dir:
with utils.chdir(tx_tmp_dir):
out = os.path.join(tx_tmp_dir,"kraken_out")
out_stats = os.path.join(tx_tmp_dir,"kraken_stats")
cl = (" ").join([config_utils.get_program("kraken", data["config"]),
"--db",db,"--quick",
"--preload","--min-hits","2","--threads",str(num_cores),
"--out", out, files[0]," 2>",out_stats])
do.run(cl,"kraken: %s" % data["name"][-1])
if os.path.exists(kraken_out):
shutil.rmtree(kraken_out)
shutil.move(tx_tmp_dir, kraken_out)
metrics = _parse_kraken_output(kraken_out,db,data)
return metrics
def _prepare_samples(args):
"""
create dict for each sample having all information
"""
if args.galaxy:
system_config = args.galaxy
else:
system_config = os.path.join(_get_data_dir(), "galaxy", "bcbio_system.yaml")
config = yaml.load(open(system_config))
config['algorithm'] = {}
data = []
vcf_files = [fn for fn in args.files if fn.endswith('vcf')]
bam_files = [fn for fn in args.files if fn.endswith('bam')]
fastq_files = [fn for fn in args.files if is_fastq(fn)]
if not fastq_files:
fastq_files = vcf_files
for sample in fastq_files:
dt = {}
dt['name'] = splitext_plus(op.basename(sample))[0]
dt['config'] = config
dt['fastq'] = op.abspath(sample)
if bam_files:
dt['bam'] = _find_bam(bam_files, sample)
data.append([dt])
return data
def _config(args):
if args.galaxy:
system_config = args.galaxy
else:
system_config = op.join(_get_data_dir(), "galaxy", "bcbio_system.yaml")
config = yaml.load(open(system_config))
config['algorithm'] = {}
return config
def update_samples(data, resources, args):
"""
Update algorithm dict with new cores set
"""
if args.galaxy:
system_config = args.galaxy
else:
system_config = os.path.join(_get_data_dir(), "galaxy", "bcbio_system.yaml")
config = yaml.load(open(system_config))
config['algorithm'] = {}
new_data = []
for sample in data:
sample['config'] = config
sample['config']['algorithm'] = resources
new_data.append([sample])
return new_data
def _prepare_samples(args):
"""
create dict for each sample having all information
"""
if args.galaxy:
system_config = args.galaxy
else:
system_config = os.path.join(_get_data_dir(), "galaxy", "bcbio_system.yaml")
config = yaml.load(open(system_config))
config['algorithm'] = {}
data = []
for sample in args.files:
dt = {}
dt['name'] = splitext_plus(op.basename(sample))[0]
dt['config'] = config
dt['bed'] = op.abspath(sample)
data.append([dt])
return data
def _run_kraken(data, ratio):
"""Run kraken, generating report in specified directory and parsing metrics.
Using only first paired reads.
"""
# logger.info("Number of aligned reads < than 0.60 in %s: %s" % (str(data["name"]), ratio))
logger.info("Running kraken to determine contaminant: %s" %
str(data["name"]))
qc_dir = utils.safe_makedir(
os.path.join(data["dirs"]["work"], "qc", data["description"]))
kraken_out = os.path.join(qc_dir, "kraken")
out = out_stats = None
db = data['config']["algorithm"]["kraken"]
kraken_cmd = config_utils.get_program("kraken", data["config"])
if db == "minikraken":
db = os.path.join(_get_data_dir(), "genomes", "kraken", "minikraken")
if not os.path.exists(db):
logger.info("kraken: no database found %s, skipping" % db)
return {"kraken_report": "null"}
if not os.path.exists(os.path.join(kraken_out, "kraken_out")):
work_dir = os.path.dirname(kraken_out)
utils.safe_makedir(work_dir)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
fn_file = data["files"][0]
if fn_file.endswith("bam"):
logger.info("kraken: need fasta files as input")
return {"kraken_report": "null"}
with tx_tmpdir(data, work_dir) as tx_tmp_dir:
with utils.chdir(tx_tmp_dir):
out = os.path.join(tx_tmp_dir, "kraken_out")
out_stats = os.path.join(tx_tmp_dir, "kraken_stats")
cat = "zcat" if fn_file.endswith(".gz") else "cat"
cl = ("{cat} {fn_file} | {kraken_cmd} --db {db} --quick "
"--preload --min-hits 2 "
"--threads {num_cores} "
"--out {out} --fastq-input /dev/stdin 2> {out_stats}"
).format(**locals())
do.run(cl, "kraken: %s" % data["name"][-1])
if os.path.exists(kraken_out):
shutil.rmtree(kraken_out)
shutil.move(tx_tmp_dir, kraken_out)
metrics = _parse_kraken_output(kraken_out, db, data)
return metrics
def run(_, data, out_dir):
"""Run kraken, generating report in specified directory and parsing metrics.
Using only first paired reads.
"""
# logger.info("Number of aligned reads < than 0.60 in %s: %s" % (dd.get_sample_name(data), ratio))
logger.info("Running kraken to determine contaminant: %s" %
dd.get_sample_name(data))
# ratio = bam.get_aligned_reads(bam_file, data)
out = out_stats = None
db = tz.get_in(["config", "algorithm", "kraken"], data)
kraken_cmd = config_utils.get_program("kraken", data["config"])
if db == "minikraken":
db = os.path.join(install._get_data_dir(), "genomes", "kraken",
"minikraken")
if not os.path.exists(db):
logger.info("kraken: no database found %s, skipping" % db)
return {"kraken_report": "null"}
if not os.path.exists(os.path.join(out_dir, "kraken_out")):
work_dir = os.path.dirname(out_dir)
utils.safe_makedir(work_dir)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
fn_file = data["files_orig"][0] if dd.get_save_diskspace(
data) else data["files"][0]
if fn_file.endswith("bam"):
logger.info("kraken: need fastq files as input")
return {"kraken_report": "null"}
with tx_tmpdir(data) as tx_tmp_dir:
with utils.chdir(tx_tmp_dir):
out = os.path.join(tx_tmp_dir, "kraken_out")
out_stats = os.path.join(tx_tmp_dir, "kraken_stats")
cat = "zcat" if fn_file.endswith(".gz") else "cat"
cl = ("{cat} {fn_file} | {kraken_cmd} --db {db} --quick "
"--preload --min-hits 2 "
"--threads {num_cores} "
"--output {out} --fastq-input /dev/stdin 2> {out_stats}"
).format(**locals())
do.run(cl, "kraken: %s" % dd.get_sample_name(data))
if os.path.exists(out_dir):
shutil.rmtree(out_dir)
shutil.move(tx_tmp_dir, out_dir)
metrics = _parse_kraken_output(out_dir, db, data)
return metrics
def run(_, data, out_dir):
"""Run kraken, generating report in specified directory and parsing metrics.
Using only first paired reads.
"""
# logger.info("Number of aligned reads < than 0.60 in %s: %s" % (dd.get_sample_name(data), ratio))
logger.info("Running kraken to determine contaminant: %s" % dd.get_sample_name(data))
# ratio = bam.get_aligned_reads(bam_file, data)
out = out_stats = None
db = tz.get_in(["config", "algorithm", "kraken"], data)
if db and isinstance(db, (list, tuple)):
db = db[0]
kraken_cmd = config_utils.get_program("kraken", data["config"])
if db == "minikraken":
db = os.path.join(install._get_data_dir(), "genomes", "kraken", "minikraken")
if not os.path.exists(db):
logger.info("kraken: no database found %s, skipping" % db)
return {"kraken_report": "null"}
if not os.path.exists(os.path.join(out_dir, "kraken_out")):
work_dir = os.path.dirname(out_dir)
utils.safe_makedir(work_dir)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
fn_file = data["files_orig"][0] if dd.get_save_diskspace(data) else data["files"][0]
if fn_file.endswith("bam"):
logger.info("kraken: need fastq files as input")
return {"kraken_report": "null"}
with tx_tmpdir(data) as tx_tmp_dir:
with utils.chdir(tx_tmp_dir):
out = os.path.join(tx_tmp_dir, "kraken_out")
out_stats = os.path.join(tx_tmp_dir, "kraken_stats")
cat = "zcat" if fn_file.endswith(".gz") else "cat"
cl = ("{cat} {fn_file} | {kraken_cmd} --db {db} --quick "
"--preload --min-hits 2 "
"--threads {num_cores} "
"--output {out} --fastq-input /dev/stdin 2> {out_stats}").format(**locals())
do.run(cl, "kraken: %s" % dd.get_sample_name(data))
if os.path.exists(out_dir):
shutil.rmtree(out_dir)
shutil.move(tx_tmp_dir, out_dir)
metrics = _parse_kraken_output(out_dir, db, data)
return metrics
def _run_kraken(data, ratio):
"""Run kraken, generating report in specified directory and parsing metrics.
Using only first paired reads.
"""
logger.info("Number of aligned reads < than 0.60 in %s: %s" %
(str(data["name"]), ratio))
logger.info("Running kraken to determine contaminant: %s" %
str(data["name"]))
qc_dir = utils.safe_makedir(
os.path.join(data["dirs"]["work"], "qc", data["description"]))
kraken_out = os.path.join(qc_dir, "kraken")
out = out_stats = None
db = data['config']["algorithm"]["kraken"]
if db == "minikraken":
db = os.path.join(_get_data_dir(), "genomes", "kraken", "minikraken")
else:
if not os.path.exists(db):
logger.info("kraken: no database found %s, skipping" % db)
return {"kraken_report": "null"}
if not os.path.exists(os.path.join(kraken_out, "kraken_out")):
work_dir = os.path.dirname(kraken_out)
utils.safe_makedir(work_dir)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
files = data["files"]
if files[0].endswith("bam"):
logger.info("kraken: need fasta files as input")
return {"kraken_report": "null"}
with tx_tmpdir(data, work_dir) as tx_tmp_dir:
with utils.chdir(tx_tmp_dir):
out = os.path.join(tx_tmp_dir, "kraken_out")
out_stats = os.path.join(tx_tmp_dir, "kraken_stats")
cl = (" ").join([
config_utils.get_program("kraken", data["config"]), "--db",
db, "--quick", "--preload", "--min-hits", "2", "--threads",
str(num_cores), "--out", out, files[0], " 2>", out_stats
])
do.run(cl, "kraken: %s" % data["name"][-1])
if os.path.exists(kraken_out):
shutil.rmtree(kraken_out)
shutil.move(tx_tmp_dir, kraken_out)
metrics = _parse_kraken_output(kraken_out, db, data)
return metrics
def _run_kraken(data, ratio):
"""Run kraken, generating report in specified directory and parsing metrics.
Using only first paired reads.
"""
# logger.info("Number of aligned reads < than 0.60 in %s: %s" % (str(data["name"]), ratio))
logger.info("Running kraken to determine contaminant: %s" % str(data["name"]))
qc_dir = utils.safe_makedir(os.path.join(data["dirs"]["work"], "qc", data["description"]))
kraken_out = os.path.join(qc_dir, "kraken")
out = out_stats = None
db = data['config']["algorithm"]["kraken"]
kraken_cmd = config_utils.get_program("kraken", data["config"])
if db == "minikraken":
db = os.path.join(_get_data_dir(), "genomes", "kraken", "minikraken")
if not os.path.exists(db):
logger.info("kraken: no database found %s, skipping" % db)
return {"kraken_report": "null"}
if not os.path.exists(os.path.join(kraken_out, "kraken_out")):
work_dir = os.path.dirname(kraken_out)
utils.safe_makedir(work_dir)
num_cores = data["config"]["algorithm"].get("num_cores", 1)
fn_file = data["files"][0]
if fn_file.endswith("bam"):
logger.info("kraken: need fasta files as input")
return {"kraken_report": "null"}
with tx_tmpdir(data, work_dir) as tx_tmp_dir:
with utils.chdir(tx_tmp_dir):
out = os.path.join(tx_tmp_dir, "kraken_out")
out_stats = os.path.join(tx_tmp_dir, "kraken_stats")
cat = "zcat" if fn_file.endswith(".gz") else "cat"
cl = ("{cat} {fn_file} | {kraken_cmd} --db {db} --quick "
"--preload --min-hits 2 "
"--threads {num_cores} "
"--out {out} --fastq-input /dev/stdin 2> {out_stats}").format(**locals())
do.run(cl, "kraken: %s" % data["name"][-1])
if os.path.exists(kraken_out):
shutil.rmtree(kraken_out)
shutil.move(tx_tmp_dir, kraken_out)
metrics = _parse_kraken_output(kraken_out, db, data)
return metrics
parser.add_argument("-q", "--queue", help="Queue to submit jobs to.")
parser.add_argument("-p",
"--tag",
help="Tag name to label jobs on the cluster",
default="bcb-prep")
parser.add_argument("-t",
"--paralleltype",
choices=["local", "ipython"],
default="local",
help="Run with iptyhon")
args = parser.parse_args()
out_dir = os.path.abspath(args.out)
utils.safe_makedir(out_dir)
try:
system_config = os.path.join(_get_data_dir(), "galaxy",
"bcbio_system.yaml")
except ValueError as err:
print(err)
print(
"WARNING: Attempting to read bcbio_system.yaml in the current directory."
)
system_config = "bcbio_system.yaml"
with open(system_config) as in_handle:
config = yaml.load(in_handle)
res = {'cores': args.cores_per_job}
config["algorithm"] = {"num_cores": args.cores_per_job}
config["resources"].update({'sambamba': res, 'samtools': res})
config["log_dir"] = os.path.join(os.path.abspath(os.getcwd()), "log")
parallel = clargs.to_parallel(args)
parser.add_argument("--timeout", default=15, help="Time to wait before giving up starting.")
parser.add_argument("--retries", default=0, type=int,
help=("Number of retries of failed tasks during "
"distributed processing. Default 0 "
"(no retries)"))
parser.add_argument("-s", "--scheduler", help="Type of scheduler to use.",
choices=["lsf", "slurm", "torque", "sge", "pbspro"])
parser.add_argument("-r", "--resources", help="Extra scheduler resource flags.", default=[], action="append")
parser.add_argument("-q", "--queue", help="Queue to submit jobs to.")
parser.add_argument("-p", "--tag", help="Tag name to label jobs on the cluster", default="bcb-prep")
parser.add_argument("-t", "--paralleltype",
choices=["local", "ipython"],
default="local", help="Run with iptyhon")
args = parser.parse_args()
system_config = os.path.join(_get_data_dir(), "galaxy", "bcbio_system.yaml")
if args.galaxy:
system_config = args.galaxy
with open(system_config) as in_handle:
config = yaml.load(in_handle)
parallel = clargs.to_parallel(args)
parallel.update({'progs': args.progs})
dirs = {'work': os.path.abspath(os.getcwd())}
if args.sys_info.find(";") > -1:
info = args.sys_info.split(";")
sysinfo = {'cores': int(info[0]), 'memory': float(info[1])}
else:
if utils.file_exists(args.sys_info):
sysinfo = yaml.load(open(args.sys_info))[0]
print "system info %s" % sysinfo
raise ValueError("--mirbase and --srna_gtf both need a value.")
env.hosts = ["localhost"]
env.cores = args.cores
os.environ["PATH"] += os.pathsep + os.path.dirname(sys.executable)
cbl = get_cloudbiolinux(REMOTES)
sys.path.insert(0, cbl["dir"])
genomemod = __import__("cloudbio.biodata", fromlist=["genomes"])
# monkey patch cloudbiolinux to use this indexing command instead
genomes = getattr(genomemod, 'genomes')
genomes._index_w_command = _index_w_command
fabmod = __import__("cloudbio", fromlist=["fabutils"])
fabutils = getattr(fabmod, 'fabutils')
fabutils.configure_runsudo(env)
system_config = os.path.join(_get_data_dir(), "galaxy",
"bcbio_system.yaml")
with open(system_config) as in_handle:
config = yaml.load(in_handle)
env.picard_home = config_utils.get_program("picard", config, ptype="dir")
genome_dir = os.path.abspath(os.path.join(_get_data_dir(), "genomes"))
args.fasta = os.path.abspath(args.fasta)
args.gtf = os.path.abspath(args.gtf) if args.gtf else None
if args.gff3:
args.gtf = gff3_to_gtf(args.gtf)
# always make a sequence dictionary
if "seq" not in args.indexes:
args.indexes.append("seq")
def error(self, message):
self.print_help()
galaxy_base = os.path.join(_get_data_dir(), "galaxy")
print("\nCurrent genomes\n")
print(open(loc.get_loc_file(galaxy_base, "samtools")).read())
sys.exit(0)
parser.add_argument("--mirbase", help="species in mirbase for smallRNAseq data.")
parser.add_argument("--srna_gtf", help="gtf to use for smallRNAseq data.")
args = parser.parse_args()
# if not all([args.mirbase, args.srna_gtf]) and any([args.mirbase, args.srna_gtf]):
# raise ValueError("--mirbase and --srna_gtf both need a value.")
os.environ["PATH"] += os.pathsep + os.path.dirname(sys.executable)
cbl = get_cloudbiolinux(REMOTES)
sys.path.insert(0, cbl["dir"])
genomemod = __import__("cloudbio.biodata", fromlist=["genomes"])
# monkey patch cloudbiolinux to use this indexing command instead
genomes = getattr(genomemod, 'genomes')
genomes._index_w_command = _index_w_command
genome_dir = os.path.abspath(os.path.join(_get_data_dir(), "genomes"))
args.fasta = os.path.abspath(args.fasta)
if not file_exists(args.fasta):
print("%s does not exist, exiting." % args.fasta)
sys.exit(1)
args.gtf = os.path.abspath(args.gtf) if args.gtf else None
if args.gtf and not file_exists(args.gtf):
print("%s does not exist, exiting." % args.gtf)
sys.exit(1)
args.srna_gtf = os.path.abspath(args.srna_gtf) if args.srna_gtf else None
gtf_file = args.gtf
if args.gff3:
gtf_file = extract_if_gzipped(gtf_file)
gtf_file = gff3_to_gtf(gtf_file)
def error(self, message):
self.print_help()
galaxy_base = os.path.join(_get_data_dir(), "galaxy")
print("\nCurrent genomes\n")
print(open(loc.get_loc_file(galaxy_base, "samtools")).read())
sys.exit(0)
raise ValueError("--mirbase and --srna_gtf both need a value.")
env.hosts = ["localhost"]
env.cores = args.cores
os.environ["PATH"] += os.pathsep + os.path.dirname(sys.executable)
cbl = get_cloudbiolinux(REMOTES)
sys.path.insert(0, cbl["dir"])
genomemod = __import__("cloudbio.biodata", fromlist=["genomes"])
# monkey patch cloudbiolinux to use this indexing command instead
genomes = getattr(genomemod, 'genomes')
genomes._index_w_command = _index_w_command
fabmod = __import__("cloudbio", fromlist=["fabutils"])
fabutils = getattr(fabmod, 'fabutils')
fabutils.configure_runsudo(env)
system_config = os.path.join(_get_data_dir(), "galaxy", "bcbio_system.yaml")
with open(system_config) as in_handle:
config = yaml.load(in_handle)
env.picard_home = config_utils.get_program("picard", config, ptype="dir")
genome_dir = os.path.abspath(os.path.join(_get_data_dir(), "genomes"))
args.fasta = os.path.abspath(args.fasta)
args.gtf = os.path.abspath(args.gtf) if args.gtf else None
if args.gff3:
args.gtf = gff3_to_gtf(args.gtf)
# always make a sequence dictionary
if "seq" not in args.indexes:
args.indexes.append("seq")
env.system_install = genome_dir
