def main():
args = docopt(__doc__)
names_f = args['--names']
nodes_f = args['--nodes']
# Parse names.dmp, nodes.dmp
nodesDB_default = join(dirname(abspath(__file__)), "../data/nodesDB.txt")
nodesDB, nodesDB_f = BtIO.parseNodesDB(nodes=nodes_f,
names=names_f,
nodesDB=None,
nodesDBdefault=nodesDB_default)
def main():
args = docopt(__doc__)
names_f = args['--names']
nodes_f = args['--nodes']
# Parse names.dmp, nodes.dmp
nodesDB_default = join(blobtools.DATADIR, "nodesDB.txt")
nodesDB, nodesDB_f = BtIO.parseNodesDB(nodes=nodes_f,
names=names_f,
nodesDB=None,
nodesDBdefault=nodesDB_default)
def main():
#main_dir = dirname(__file__)
args = docopt(__doc__)
fasta_f = args['--infile']
fasta_type = args['--type']
bam_fs = args['--bam']
cov_fs = args['--cov']
cas_fs = args['--cas']
hit_fs = args['--hitsfile']
prefix = args['--out']
nodesDB_f = args['--db']
names_f = args['--names']
estimate_cov_flag = True if not args['--calculate_cov'] else False
nodes_f = args['--nodes']
taxrules = args['--taxrule']
try:
min_bitscore_diff = float(args['--min_diff'])
min_score = float(args['--min_score'])
except ValueError():
BtLog.error('45')
tax_collision_random = args['--tax_collision_random']
title = args['--title']
# outfile
out_f = BtIO.getOutFile("blobDB", prefix, "json")
if not (title):
title = out_f
# coverage
if not (fasta_type) and not bam_fs and not cov_fs and not cas_fs:
BtLog.error('1')
cov_libs = [BtCore.CovLibObj('bam' + str(idx), 'bam', lib_f) for idx, lib_f in enumerate(bam_fs)] + \
[BtCore.CovLibObj('cas' + str(idx), 'cas', lib_f) for idx, lib_f in enumerate(cas_fs)] + \
[BtCore.CovLibObj('cov' + str(idx), 'cov', lib_f) for idx, lib_f in enumerate(cov_fs)]
# taxonomy
hit_libs = [
BtCore.HitLibObj('tax' + str(idx), 'tax', lib_f)
for idx, lib_f in enumerate(hit_fs)
]
# Create BlobDB object
blobDb = BtCore.BlobDb(title)
blobDb.version = interface.__version__
# Parse FASTA
blobDb.parseFasta(fasta_f, fasta_type)
# Parse nodesDB OR names.dmp, nodes.dmp
nodesDB_default = join(dirname(abspath(__file__)), "../data/nodesDB.txt")
nodesDB, nodesDB_f = BtIO.parseNodesDB(nodes=nodes_f,
names=names_f,
nodesDB=nodesDB_f,
nodesDBdefault=nodesDB_default)
blobDb.nodesDB_f = nodesDB_f
# Parse similarity hits
if (hit_libs):
blobDb.parseHits(hit_libs)
if not taxrules:
if len(hit_libs) > 1:
taxrules = ['bestsum', 'bestsumorder']
else:
taxrules = ['bestsum']
blobDb.computeTaxonomy(taxrules, nodesDB, min_score, min_bitscore_diff,
tax_collision_random)
else:
print(BtLog.warn_d['0'])
# Parse coverage
blobDb.parseCoverage(covLibObjs=cov_libs,
estimate_cov=estimate_cov_flag,
prefix=prefix)
# Generating BlobDB and writing to file
print(BtLog.status_d['7'] % out_f)
BtIO.writeJson(blobDb.dump(), out_f)