def run_pipeline(args):
print("Identifying species and samples")
species_list = merge.select_species(args, dtype='genes')
for species in species_list:
print(" %s" % species.id)
print(" count genomes: %s" % species.info['count_genomes'])
print(" count samples: %s" % len(species.samples))
print("\nMerging genes")
for species in species_list:
print(" %s" % species.id)
species.dir = os.path.join(args['outdir'], species.id)
if not os.path.isdir(species.dir): os.mkdir(species.dir)
read_cluster_map(species, args['db'], args['cluster_pid'])
print(" building pangenome matrices")
build_gene_matrices(species, min_copy=args['min_copy'])
write_gene_matrices(species)
print(" writing summary statistics")
species.write_sample_info(dtype='genes', outdir=args['outdir'])
write_readme(args, species)
print(" done!")
def run_pipeline(args):
print("Identifying species and samples")
if 'db' in args:
args['iggdb'] = IGGdb(f"{args['db']}/metadata/species_info.tsv")
global species_list
species_list = merge.select_species(args, dtype='snps')
for species in species_list:
print(" %s" % species.id)
if 'genome_name' in species.genome_info:
print(" genome name: %s" % species.genome_info['genome_name'])
if 'length' in species.genome_info:
print(" genome length: %s" % species.genome_info['length'])
if 'contigs' in species.genome_info:
print(" count contigs: %s" %
max(1, int(species.genome_info['contigs'])))
print(" count samples: %s" % len(species.samples))
print("\nMerging snps")
global global_args
global_args = args
sem = multiprocessing.Semaphore(int(args['threads']))
procs = []
for index in range(0, len(species_list)):
sem.acquire()
procs.append(
multiprocessing.Process(target=psw_safe, args=[index, sem]))
procs[-1].start()
for p in procs:
p.join()
def run_pipeline(args):
print("Identifying species")
species = merge.select_species(args, type='snps')
print("Merging snps")
batches = []
for species in species:
batches.append({'args': args, 'species': species})
utility.parallel(merge_snps, batches, args['threads'])
def run_pipeline(args):
print("Identifying species")
species = merge.select_species(args, type='snps')
for sp in species:
print "Merging: %s (id:%s) for %s samples" % (sp.consensus_name, sp.id, len(sp.samples))
print(" merging per-sample statistics")
merge.write_summary_stats(sp.id, sp.samples, args, 'snps')
print(" merging per-site statistics")
build_snp_matrix(sp.id, sp.samples, args)
print(" extracting and annotating specified sites")
filter_snp_matrix(sp.id, sp.samples, args)
print(" removing temporary files")
shutil.rmtree('%s/%s/temp' % (args['outdir'], sp.id))
def run_pipeline(args):
print("Identifying species")
species = merge.select_species(args, type='genes')
for sp in species:
print "Merging: %s (id:%s) for %s samples" % (sp.consensus_name, sp.id, len(sp.samples))
outdir = os.path.join(args['outdir'], sp.id)
if not os.path.isdir(outdir): os.mkdir(outdir)
print(" building pangenome matrices")
build_gene_matrices(sp.id, sp.samples, args)
write_gene_matrices(sp.id, sp.samples, args)
print(" writing gene info file")
write_gene_info(sp.id, args)
print(" writing summary statistics")
merge.write_summary_stats(sp.id, sp.samples, args, 'genes')
print("")
def run_pipeline(args):
print("Identifying species")
species = merge.select_species(args, type='genes')
for sp in species:
print("Merging: %s for %s samples" % (sp.id, len(sp.samples)))
sp.dir = os.path.join(args['outdir'], sp.id)
if not os.path.isdir(sp.dir): os.mkdir(sp.dir)
read_cluster_map(sp, args['db'], args['cluster_pid'])
print(" building pangenome matrices")
build_gene_matrices(sp, min_copy=args['min_copy'])
write_gene_matrices(sp)
print(" writing summary statistics")
merge.write_summary_stats(sp.id, sp.samples, args, 'genes')
write_readme(args, sp)
print("")
def run_pipeline(args):
print("Identifying species and samples")
species_list = merge.select_species(args, dtype='snps')
for species in species_list:
print(" %s" % species.id)
if 'genome_name' in species.genome_info:
print(" genome name: %s" % species.genome_info['genome_name'])
if 'length' in species.genome_info:
print(" genome length: %s" % species.genome_info['length'])
if 'contigs' in species.genome_info:
print(" count contigs: %s" %
max(1, int(species.genome_info['contigs'])))
print(" count samples: %s" % len(species.samples))
print("\nMerging snps")
for species in species_list:
print(" %s" % species.id)
species.tempdir = '%s/%s/temp' % (args['outdir'], species.id)
if not os.path.isdir(species.tempdir): os.mkdir(species.tempdir)
species.sample_lists = utility.batch_samples(species.samples,
threads=args['threads'])
species.num_splits = len(species.sample_lists)
print(" merging count data")
parallel_build_temp_count_matrixes(species, args)
print(" calling SNPs")
parallel_build_sharded_tables(species, args)
print(" writing output files")
merge_sharded_tables(species, args)
print(" finishing")
write_snps_readme(args, species)
species.write_sample_info(dtype='snps', outdir=args['outdir'])
shutil.rmtree(species.tempdir)
def run_pipeline(args):
print("Identifying species")
species = merge.select_species(args, type='genes')
for sp in species:
print("Merging: %s (id:%s) for %s samples" %
(sp.consensus_name, sp.id, len(sp.samples)))
outdir = os.path.join(args['outdir'], sp.id)
if not os.path.isdir(outdir): os.mkdir(outdir)
print(" building pangenome matrices")
build_gene_matrices(sp.id, sp.samples, args)
write_gene_matrices(sp.id, sp.samples, args)
print(" writing gene info file")
write_gene_info(sp.id, args)
print(" writing summary statistics")
merge.write_summary_stats(sp.id, sp.samples, args, 'genes')
print("")