def main():
# parse options and arguments
parser = argparse.ArgumentParser(
prog='referenceseeker',
formatter_class=argparse.RawDescriptionHelpFormatter,
description='Rapid determination of appropriate reference genomes.',
epilog=
"Citation:\n%s\n\nGitHub:\nhttps://github.com/oschwengers/referenceseeker"
% rc.CITATION,
add_help=False)
parser.add_argument('db',
metavar='<database>',
help='ReferenceSeeker database path')
group_workflow = parser.add_argument_group(
'Filter options / thresholds',
'These options control the filtering and alignment workflow.')
group_workflow.add_argument(
'--crg',
'-r',
action='store',
type=int,
default=100,
help=
'Max number of candidate reference genomes to pass kmer prefilter (default = 100)'
)
group_workflow.add_argument('--ani',
'-a',
action='store',
type=float,
default=0.95,
help='ANI threshold (default = 0.95)')
group_workflow.add_argument(
'--conserved-dna',
'-c',
action='store',
dest='conserved_dna',
type=float,
default=0.69,
help='Conserved DNA threshold (default = 0.69)')
group_workflow.add_argument(
'--unfiltered',
'-u',
action='store_true',
help=
'Set kmer prefilter to extremely conservative values and skip species level ANI cutoffs (ANI >= 0.95 and conserved DNA >= 0.69'
)
group_workflow.add_argument(
'--bidirectional',
'-b',
action='store_true',
help='Compute bidirectional ANI/conserved DNA values (default = False)'
)
group_runtime = parser.add_argument_group('Runtime & auxiliary options')
group_runtime.add_argument('--help',
'-h',
action='help',
help='Show this help message and exit')
group_runtime.add_argument('--version',
'-V',
action='version',
version='%(prog)s ' +
referenceseeker.__version__)
group_runtime.add_argument('--verbose',
'-v',
action='store_true',
help='Print verbose information')
group_runtime.add_argument(
'--threads',
'-t',
action='store',
type=int,
default=mp.cpu_count(),
help='Number of used threads (default = number of available CPU cores)'
)
subparsers = parser.add_subparsers(dest='subcommand',
help='sub-command help')
# add "single" sub-command option
parser_single = subparsers.add_parser(
'single', help='start reference genome search for single genome')
parser_single.add_argument('--genome',
"-g",
metavar='<genome>',
action='store',
help='target draft genome in fasta format')
parser_single.add_argument(
'--n_mash_results',
'-n',
action='store',
default=100,
help=
"Define the number of mash results that will be used as reference-candidates"
)
# add "cohort" sub-command option
parser_cohort = subparsers.add_parser(
'cohort', help='start reference genome search for genome cohort')
parser_cohort.add_argument(
'--cohort_genomes',
'-cg',
metavar='<genome>',
action='store',
nargs="*",
help=
'Target draft genomes or directory with all draft genomes in fasta format'
)
parser_cohort.add_argument(
'--algorithm',
'-a',
action='store',
default="product",
help='Choose algorithm to calculate best fitting reference genome.')
parser_cohort.add_argument(
'--n_mash_results',
'-n',
action='store',
default=100,
help=
"Define the number of mash results that will be used as reference-candidates"
)
args = parser.parse_args()
# setup global configuration
config = util.setup_configuration(args)
util.test_binaries(config)
# check database parameters
try:
config['db_path'] = util.check_path(args.db)
except FileNotFoundError:
sys.exit('ERROR: database directory is not readable!')
except PermissionError:
sys.exit('ERROR (permission): database directory is not accessible')
except OSError:
sys.exit('ERROR: database directory is empty')
# print verbose information
if args.verbose:
print("ReferenceSeeker v%s" % referenceseeker.__version__)
print('Options, parameters and arguments:')
print("\tuse bundled binaries: %s" % str(config['bundled-binaries']))
print("\tdb path: %s" % str(config['db_path']))
print("\tgenome path: %s" % str(config['genome_path']))
print("\ttmp path: %s" % str(config['tmp']))
print("\tunfiltered: %s" % str(config['unfiltered']))
print("\tbidirectional: %s" % str(config['bidirectional']))
print("\tANI: %0.2f" % config['ani'])
print("\tconserved DNA: %0.2f" % config['conserved_dna'])
print("\t# CRG: %d" % config['crg'])
print("\t# threads: %d" % config['threads'])
if args.subcommand == 'single':
single.single(args, config)
elif args.subcommand == 'cohort':
cohort.cohort(args, config)
else:
parser.print_help()
sys.exit("Error: no subcommand provided!")
def main():
# setup path and test if necessary 3rd party executables are available
config = {}
util.set_path(config)
util.test_binaries(config)
# parse options and arguments
parser = argparse.ArgumentParser(
prog='referenceseeker_db',
formatter_class=argparse.RawDescriptionHelpFormatter,
description='Rapid determination of appropriate reference genomes.',
epilog=
"Citation:\n%s\n\nGitHub:\nhttps://github.com/oschwengers/referenceseeker"
% rc.CITATION,
add_help=False)
# add common options
group_runtime = parser.add_argument_group('Runtime & auxiliary options')
group_runtime.add_argument('--help',
'-h',
action='help',
help='Show this help message and exit')
group_runtime.add_argument('--version',
'-V',
action='version',
version='%(prog)s ' +
referenceseeker.__version__)
subparsers = parser.add_subparsers(dest='subcommand',
help='sub-command help')
# add init sub-command options
parser_init = subparsers.add_parser('init',
help='Initialize a new database')
parser_init.add_argument(
'--output',
'-o',
action='store',
default=Path.cwd(),
help='output directory (default = current working directory)')
parser_init.add_argument('--db',
'-d',
action='store',
required=True,
help='Name of the new ReferenceSeeker database')
# add import sub-command options
parser_import = subparsers.add_parser('import',
help='Add a new genome to database')
parser_import.add_argument('--db',
'-d',
action='store',
required=True,
help='ReferenceSeeker database path')
parser_import.add_argument('--genome',
'-g',
action='store',
required=True,
help='Genome path [Fasta, GenBank, EMBL]')
parser_import.add_argument(
'--id',
'-i',
action='store',
default=None,
help='Unique genome identifier (default sequence id of first record)')
parser_import.add_argument(
'--taxonomy',
'-t',
action='store',
type=int,
default=12908,
help='Taxonomy ID (default = 12908 [unclassified sequences])')
parser_import.add_argument(
'--status',
'-s',
action='store',
choices=['complete', 'chromosome', 'scaffold', 'contig'],
default='contig',
help='Assembly level (default = contig)')
parser_import.add_argument('--organism',
'-o',
action='store',
default='',
help='Organism name (default = "")')
args = parser.parse_args()
if (args.subcommand == 'init'):
init(args)
elif (args.subcommand == 'import'):
import_genome(config, args)
else:
parser.print_help()
sys.exit("Error: no subcommand provided!")
def main():
# parse options and arguments
parser = argparse.ArgumentParser(
prog='referenceseeker',
formatter_class=argparse.RawDescriptionHelpFormatter,
description='Rapid determination of appropriate reference genomes.',
epilog=
"Citation:\n%s\n\nGitHub:\nhttps://github.com/oschwengers/referenceseeker"
% rc.CITATION,
add_help=False)
parser.add_argument('db',
metavar='<database>',
help='ReferenceSeeker database path')
parser.add_argument('genome',
metavar='<genome>',
help='target draft genome in fasta format')
group_workflow = parser.add_argument_group(
'Filter options / thresholds',
'These options control the filtering and alignment workflow.')
group_workflow.add_argument(
'--crg',
'-r',
action='store',
type=int,
default=100,
help=
'Max number of candidate reference genomes to pass kmer prefilter (default = 100)'
)
group_workflow.add_argument('--ani',
'-a',
action='store',
type=float,
default=0.95,
help='ANI threshold (default = 0.95)')
group_workflow.add_argument(
'--conserved-dna',
'-c',
action='store',
dest='conserved_dna',
type=float,
default=0.69,
help='Conserved DNA threshold (default = 0.69)')
group_workflow.add_argument(
'--unfiltered',
'-u',
action='store_true',
help=
'Set kmer prefilter to extremely conservative values and skip species level ANI cutoffs (ANI >= 0.95 and conserved DNA >= 0.69'
)
group_workflow.add_argument(
'--bidirectional',
'-b',
action='store_true',
help='Compute bidirectional ANI/conserved DNA values (default = False)'
)
group_runtime = parser.add_argument_group('Runtime & auxiliary options')
group_runtime.add_argument('--help',
'-h',
action='help',
help='Show this help message and exit')
group_runtime.add_argument('--version',
'-V',
action='version',
version='%(prog)s ' +
referenceseeker.__version__)
group_runtime.add_argument('--verbose',
'-v',
action='store_true',
help='Print verbose information')
group_runtime.add_argument(
'--threads',
'-t',
action='store',
type=int,
default=mp.cpu_count(),
help='Number of used threads (default = number of available CPU cores)'
)
args = parser.parse_args()
# setup global configuration
config = util.setup_configuration(args)
util.test_binaries(config)
# check parameters
db_path = Path(args.db)
if (not os.access(str(db_path), os.R_OK)):
sys.exit('ERROR: database directory not readable!')
db_path = db_path.resolve()
config['db_path'] = db_path
genome_path = Path(args.genome)
if (not os.access(str(genome_path), os.R_OK)):
sys.exit('ERROR: genome file not readable!')
if (genome_path.stat().st_size == 0):
sys.exit('ERROR: genome file (%s) is empty!' % genome_path)
genome_path = genome_path.resolve()
config['genome_path'] = genome_path
# print verbose information
if (args.verbose):
print("ReferenceSeeker v%s" % referenceseeker.__version__)
print('Options, parameters and arguments:')
print("\tuse bundled binaries: %s" % str(config['bundled-binaries']))
print("\tdb path: %s" % str(config['db_path']))
print("\tgenome path: %s" % str(config['genome_path']))
print("\ttmp path: %s" % str(config['tmp']))
print("\tunfiltered: %s" % str(config['unfiltered']))
print("\tbidirectional: %s" % str(config['bidirectional']))
print("\tANI: %0.2f" % config['ani'])
print("\tconserved DNA: %0.2f" % config['conserved_dna'])
print("\t# CRG: %d" % config['crg'])
print("\t# threads: %d" % config['threads'])
# calculate genome distances via Mash
if (args.verbose):
print('\nEstimate genome distances...')
mash_output_path = config['tmp'].joinpath('mash.out')
mash.run_mash(config, mash_output_path)
# extract hits and store dist
screened_ref_genome_ids, mash_distances = mash.parse_mash_results(
config, mash_output_path)
if (args.verbose):
print("\tscreened %d potential reference genome(s)" %
len(screened_ref_genome_ids))
# reduce Mash output to best hits (args.crg)
if (len(screened_ref_genome_ids) > args.crg):
if (args.verbose):
print("\treduce to best %d hits..." % args.crg)
tmp_screened_ref_genome_ids = sorted(screened_ref_genome_ids,
key=lambda k: mash_distances[k])
screened_ref_genome_ids = tmp_screened_ref_genome_ids[:args.crg]
# get genomes from RefSeq by accessions
ref_genomes = util.read_reference_genomes(config)
screened_ref_genomes = {
k: v
for k, v in ref_genomes.items() if k in screened_ref_genome_ids
}
# build dna fragments
dna_fragments_path = config['tmp'].joinpath('dna-fragments.fasta')
dna_fragments = util.build_dna_fragments(genome_path, dna_fragments_path)
# align query fragments to reference genomes and compute ANI/conserved DNA
results = {}
if (args.verbose):
print('\nCompute ANIs...')
with cf.ThreadPoolExecutor(max_workers=args.threads) as tpe:
futures = []
for id, ref_genome in screened_ref_genomes.items():
futures.append(
tpe.submit(rani.align_query_genome, config, dna_fragments_path,
dna_fragments, id))
for f in futures:
ref_genome_id, ani, conserved_dna = f.result()
results[ref_genome_id] = [(ani, conserved_dna)]
# align reference genomes fragments to query genome and compute ANI/conserved DNA
if (args.bidirectional):
if (args.verbose):
print('\nCompute reverse ANIs...')
with cf.ProcessPoolExecutor(args.threads) as ppe:
futures = []
for id, ref_genome in screened_ref_genomes.items():
futures.append(
ppe.submit(rani.align_reference_genome, config,
genome_path, id))
for f in futures:
ref_genome_id, ani, conserved_dna = f.result()
result = results[ref_genome_id]
result.append((ani, conserved_dna))
# remove tmp dir
shutil.rmtree(str(config['tmp']))
# filter and sort results
filtered_reference_ids = []
for ref_genome_id, result in results.items():
if (args.unfiltered):
filtered_reference_ids.append(ref_genome_id)
else:
if (args.bidirectional):
query_ref = result[0]
ref_query = result[1]
if ((query_ref[0] >= config['ani'])
and (query_ref[1] >= config['conserved_dna'])
and (ref_query[0] >= config['ani'])
and (ref_query[1] >= config['conserved_dna'])):
filtered_reference_ids.append(ref_genome_id)
else:
(ani, conserved_dna) = result[0]
if ((conserved_dna >= config['conserved_dna'])
and (ani >= config['ani'])):
filtered_reference_ids.append(ref_genome_id)
# sort and print results according to ANI * conserved DNA values
if (args.bidirectional):
filtered_reference_ids = sorted(filtered_reference_ids,
key=lambda k:
(results[k][0][0] * results[k][0][1] *
results[k][1][0] * results[k][1][1]),
reverse=True)
if (args.verbose):
print('')
print(
'#ID\tMash Distance\tQR ANI\tQR Con. DNA\tRQ ANI\tRQ Con. DNA\tTaxonomy ID\tAssembly Status\tOrganism'
)
for id in filtered_reference_ids: # print results to STDOUT
ref_genome = ref_genomes[id]
result = results[id]
print(
'%s\t%1.5f\t%2.2f\t%2.2f\t%2.2f\t%2.2f\t%s\t%s\t%s' %
(id, mash_distances[id], result[0][0] * 100,
result[0][1] * 100, result[1][0] * 100, result[1][1] * 100,
ref_genome['tax'], ref_genome['status'], ref_genome['name']))
else:
filtered_reference_ids = sorted(filtered_reference_ids,
key=lambda k:
(results[k][0][0] * results[k][0][1]),
reverse=True)
if (args.verbose):
print('')
print(
'#ID\tMash Distance\tANI\tCon. DNA\tTaxonomy ID\tAssembly Status\tOrganism'
)
for id in filtered_reference_ids: # print results to STDOUT
ref_genome = ref_genomes[id]
result = results[id][0]
print(
'%s\t%1.5f\t%2.2f\t%2.2f\t%s\t%s\t%s' %
(id, mash_distances[id], result[0] * 100, result[1] * 100,
ref_genome['tax'], ref_genome['status'], ref_genome['name']))