def main():
parser = OptionParser()
parser.add_option('-r', dest='readsf', help='Fasta file of reads')
parser.add_option('-n',
dest='numreads',
type='int',
help='Number of reads to sample for MCMC')
parser.add_option('-k',
dest='clusters',
type='int',
help='Number of clusters')
parser.add_option('-m', dest='mers', type='int', help='Mers to count')
parser.add_option('-p',
dest='proc',
type='int',
help='Number of processes to run')
parser.add_option('--em',
dest='soft_assign',
action='store_true',
default=False,
help='Use a soft assignment of reads to clusters')
(options, args) = parser.parse_args()
if options.soft_assign:
em = '--em'
else:
em = ''
# randomly sample reads
total_reads = 0
for line in open(options.readsf):
if line[0] == '>':
total_reads += 1
if options.numreads and options.numreads < total_reads:
dna.fasta_rand_big(options.numreads, options.readsf, 'sample.fa')
else:
if os.path.isfile('sample.fa') or os.path.islink('sample.fa'):
os.remvoe('sample.fa')
os.symlink(options.readsf, 'sample.fa')
# CompostBin
p = subprocess.Popen(
'%s/compostbin.py -r sample.fa -c %d -k %d &> cb.log' %
(bin_dir, options.clusters, options.mers),
shell=True)
os.waitpid(p.pid, 0)
# initialize clusters
init_clusters(options.readsf, options.clusters, options.soft_assign)
# run seed_only
p = subprocess.Popen(
'%s/imm_cluster.py -k %d -r %s -p %d -s --seed_only %s >> cb.log' %
(bin_dir, options.clusters, options.readsf, options.proc, em),
shell=True)
os.waitpid(p.pid, 0)
def main():
parser = OptionParser()
parser.add_option('-r', dest='readsf', help='Fasta file of reads')
parser.add_option('-n', dest='numreads', type='int', help='Number of reads to sample for MCMC')
parser.add_option('-k', dest='k', type='int', help='Number of clusters')
parser.add_option('-o', dest='order', type='int', help='Order of Markov model')
parser.add_option('-p', dest='proc', type='int', help='Number of processes to run')
parser.add_option('--em', dest='soft_assign', action='store_true', default=False, help='Use a soft assignment of reads to clusters')
parser.add_option('--outfile', dest='outfile', help='Output file')
(options, args) = parser.parse_args()
if options.soft_assign:
em = '--em'
else:
em = ''
# randomly sample reads
total_reads = 0
for line in open(options.readsf):
if line[0] == '>':
total_reads += 1
if options.numreads and options.numreads < total_reads:
dna.fasta_rand_big(options.numreads, options.readsf, 'sample.fa')
else:
if os.path.isfile('sample.fa') or os.path.islink('sample.fa'):
os.remove('sample.fa')
os.symlink(options.readsf, 'sample.fa')
# LikelyBin
p = subprocess.Popen('%s/../likelybin-0.1/mcmc.pl sample.fa -outfile %s -num_sources %d -chain_order %d -num_threads %d &> lb.log' % (bin_dir, options.outfile, options.k, options.order, options.proc), shell=True)
os.waitpid(p.pid, 0)
if os.path.isfile('sample.fa.binning.allprobs') and os.path.getsize('sample.fa.binning.allprobs') > 0:
# initialize clusters
init_clusters(options.readsf, options.soft_assign)
# check for k clusters
new_k = drop_empty(options.k, options.soft_assign)
# run seed_only
p = subprocess.Popen('%s/imm_cluster.py -k %d -r %s -p %d -s --seed_only %s >> lb.log' % (bin_dir, new_k, options.readsf, options.proc, em), shell=True)
os.waitpid(p.pid, 0)
def main():
parser = OptionParser()
parser.add_option('-r', dest='readsf', help='Fasta file of reads')
parser.add_option('-n', dest='numreads', type='int', help='Number of reads to sample for MCMC')
parser.add_option('-k', dest='k', type='int', help='Number of clusters')
parser.add_option('-o', dest='order', type='int', help='Order of Markov model')
parser.add_option('-p', dest='proc', type='int', help='Number of processes to run')
parser.add_option('--em', dest='soft_assign', action='store_true', default=False, help='Use a soft assignment of reads to clusters')
(options, args) = parser.parse_args()
if options.soft_assign:
em = '--em'
else:
em = ''
# randomly sample reads
total_reads = 0
for line in open(options.readsf):
if line[0] == '>':
total_reads += 1
if options.numreads and options.numreads < total_reads:
dna.fasta_rand_big(options.numreads, options.readsf, 'sample.fa')
else:
if os.path.isfile('sample.fa') or os.path.islink('sample.fa'):
os.remove('sample.fa')
os.symlink(options.readsf, 'sample.fa')
# LikelyBin
p = subprocess.Popen('%s/mcmc.pl sample.fa -num_sources %d -chain_order %d -num_threads %d &> lb.log' % (bin_dir,options.k, options.order, options.proc), shell=True)
os.waitpid(p.pid, 0)
if os.path.isfile('sample.fa.binning.allprobs') and os.path.getsize('sample.fa.binning.allprobs') > 0:
# initialize clusters
init_clusters(options.readsf, options.soft_assign)
# check for k clusters
new_k = drop_empty(options.k, options.soft_assign)
# run seed_only
p = subprocess.Popen('%s/imm_cluster.py -k %d -r %s -p %d -s --seed_only %s >> lb.log' % (bin_dir, new_k, options.readsf, options.proc, em), shell=True)
os.waitpid(p.pid, 0)
def main():
parser = OptionParser()
parser.add_option('-r', dest='readsf', help='Fasta file of reads')
parser.add_option('-n', dest='numreads', type='int', help='Number of reads to sample for MCMC')
parser.add_option('-k', dest='clusters', type='int', help='Number of clusters')
parser.add_option('-m', dest='mers', type='int', help='Mers to count')
parser.add_option('-p', dest='proc', type='int', help='Number of processes to run')
parser.add_option('--em', dest='soft_assign', action='store_true', default=False, help='Use a soft assignment of reads to clusters')
(options, args) = parser.parse_args()
if options.soft_assign:
em = '--em'
else:
em = ''
# randomly sample reads
total_reads = 0
for line in open(options.readsf):
if line[0] == '>':
total_reads += 1
if options.numreads and options.numreads < total_reads:
dna.fasta_rand_big(options.numreads, options.readsf, 'sample.fa')
else:
if os.path.isfile('sample.fa') or os.path.islink('sample.fa'):
os.remvoe('sample.fa')
os.symlink(options.readsf, 'sample.fa')
# CompostBin
p = subprocess.Popen('%s/compostbin.py -r sample.fa -c %d -k %d &> cb.log' % (bin_dir, options.clusters, options.mers), shell=True)
os.waitpid(p.pid, 0)
# initialize clusters
init_clusters(options.readsf, options.clusters, options.soft_assign)
# run seed_only
p = subprocess.Popen('%s/imm_cluster.py -k %d -r %s -p %d -s --seed_only %s >> cb.log' % (bin_dir, options.clusters, options.readsf, options.proc, em), shell=True)
os.waitpid(p.pid, 0)
def main():
parser = OptionParser()
# generic options
parser.add_option('-s', dest='readsf', help='Fasta file of sequences')
parser.add_option('-p',
dest='proc',
type='int',
default=2,
help='Number of processes to run')
# phymm options
parser.add_option(
'--taxlevel',
dest='taxlevel',
default='family',
help=
'Taxonomic level at which to cluster reads with Phymm [Default=%default]'
)
parser.add_option(
'--minbp_pct',
dest='minbp_pct',
type='float',
default=.01,
help=
'Minimum proportion of bp assigned to a class to become a cluster [Default=%default]'
)
parser.add_option(
'-n',
'--numreads',
dest='numreads',
type='int',
default=3000,
help=
'Number of reads to sample from the data set to classify with Phymm [Default=%default]'
)
parser.add_option(
'-r',
'--phymm_results',
dest='phymm_results_file',
help=
'Phymm results file to be used rather than running Phymm from scratch.'
)
# my testing options
# help='Use a soft assignment of reads to clusters [Default=%default]'
parser.add_option('--em',
dest='soft_assign',
action='store_true',
default=False,
help=SUPPRESS_HELP)
# help='Ask Phymm to ignore the IMMs in the given file'
parser.add_option('-i', dest='ignore', help=SUPPRESS_HELP)
# help='Run Phymm and initialize clusters only'
parser.add_option('--init',
dest='init',
action='store_true',
default=False,
help=SUPPRESS_HELP)
# help='Run my version of Phymm w/o Blast and w/ chromosomes only'
parser.add_option('--bc',
dest='bc',
action='store_true',
default=False,
help=SUPPRESS_HELP)
(options, args) = parser.parse_args()
# check data
data_integrity(options.readsf)
# make robust to directory changes
options.readsf = os.path.abspath(options.readsf)
if options.ignore:
options.ignore = os.path.abspath(options.ignore)
if options.soft_assign:
em = '--em'
else:
em = ''
if options.phymm_results_file:
if not os.path.isfile('sample.fa') and not os.path.islink('sample.fa'):
print >> sys.stderr, 'Assuming Phymm results file includes all reads'
os.symlink(options.readsf, 'sample.fa')
phymm_results_file = options.phymm_results_file
else:
# randomly sample reads
total_reads = 0
for line in open(options.readsf):
if line[0] == '>':
total_reads += 1
if options.numreads and options.numreads < total_reads:
dna.fasta_rand_big(options.numreads, options.readsf, 'sample.fa')
else:
os.symlink(options.readsf, 'sample.fa')
# classify
if options.bc:
bc_str = '-b -c'
phymm_results_file = 'results.01.phymm_sample_fa.txt'
else:
bc_str = ''
phymm_results_file = 'results.03.phymmBL_sample_fa.txt'
p = subprocess.Popen('%s/phymm_par.py -p %d %s sample.fa' %
(bin_dir, options.proc, bc_str),
shell=True)
os.waitpid(p.pid, 0)
# determine minimum bp for cluster
total_bp = 0
for line in open('sample.fa'):
if line[0] != '>':
total_bp += len(line.rstrip())
minbp = options.minbp_pct * total_bp
# initialize clusters
class_k = init_clusters(options.readsf, phymm_results_file,
options.taxlevel, minbp, options.soft_assign)
# run IMM clustering
if not options.init:
p = subprocess.Popen(
'%s/imm_cluster.py -k %d -r %s -p %d -s %s &> immc.log' %
(bin_dir, class_k, options.readsf, options.proc, em),
shell=True)
os.waitpid(p.pid, 0)
def main():
parser = OptionParser()
# generic options
parser.add_option('-s', dest='readsf', help='Fasta file of sequences')
parser.add_option('-p', dest='proc', type='int', default=2, help='Number of processes to run')
# phymm options
parser.add_option('--taxlevel', dest='taxlevel', default='family', help='Taxonomic level at which to cluster reads with Phymm [Default=%default]')
parser.add_option('--minbp_pct', dest='minbp_pct', type='float', default=.01, help='Minimum proportion of bp assigned to a class to become a cluster [Default=%default]')
parser.add_option('-n','--numreads', dest='numreads', type='int', default=3000, help='Number of reads to sample from the data set to classify with Phymm [Default=%default]')
parser.add_option('-r','--phymm_results', dest='phymm_results_file', help='Phymm results file to be used rather than running Phymm from scratch.')
# my testing options
# help='Use a soft assignment of reads to clusters [Default=%default]'
parser.add_option('--em',dest='soft_assign', action='store_true', default=False, help=SUPPRESS_HELP)
# help='Ask Phymm to ignore the IMMs in the given file'
parser.add_option('-i', dest='ignore', help=SUPPRESS_HELP)
# help='Run Phymm and initialize clusters only'
parser.add_option('--init', dest='init', action='store_true', default=False, help=SUPPRESS_HELP)
# help='Run my version of Phymm w/o Blast and w/ chromosomes only'
parser.add_option('--bc', dest='bc', action='store_true', default=False, help=SUPPRESS_HELP)
(options, args) = parser.parse_args()
# check data
data_integrity(options.readsf)
# make robust to directory changes
options.readsf = os.path.abspath(options.readsf)
if options.ignore:
options.ignore = os.path.abspath(options.ignore)
if options.soft_assign:
em = '--em'
else:
em = ''
if options.phymm_results_file:
if not os.path.isfile('sample.fa') and not os.path.islink('sample.fa'):
print >> sys.stderr, 'Assuming Phymm results file includes all reads'
os.symlink(options.readsf, 'sample.fa')
phymm_results_file = options.phymm_results_file
else:
# randomly sample reads
total_reads = 0
for line in open(options.readsf):
if line[0] == '>':
total_reads += 1
if options.numreads and options.numreads < total_reads:
dna.fasta_rand_big(options.numreads, options.readsf, 'sample.fa')
else:
os.symlink(options.readsf, 'sample.fa')
# classify
if options.bc:
bc_str = '-b -c'
phymm_results_file = 'results.01.phymm_sample_fa.txt'
else:
bc_str = ''
phymm_results_file = 'results.03.phymmBL_sample_fa.txt'
p = subprocess.Popen('%s/phymm_par.py -p %d %s sample.fa' % (bin_dir, options.proc,bc_str), shell=True)
os.waitpid(p.pid, 0)
# determine minimum bp for cluster
total_bp = 0
for line in open('sample.fa'):
if line[0] != '>':
total_bp += len(line.rstrip())
minbp = options.minbp_pct*total_bp
# initialize clusters
class_k = init_clusters(options.readsf, phymm_results_file, options.taxlevel, minbp, options.soft_assign)
# run IMM clustering
if not options.init:
p = subprocess.Popen('%s/imm_cluster.py -k %d -r %s -p %d -s %s &> immc.log' % (bin_dir, class_k, options.readsf, options.proc, em), shell=True)
os.waitpid(p.pid, 0)
