def parse_arguments():
import argparse
parser = argparse.ArgumentParser(
description='Simulate a SELEX experiment.')
parser.add_argument( '--energy-model', type=file,
help='An energy model to simulate from.')
parser.add_argument( '--pwm', type=file,
help='A pwm to simulate from.')
parser.add_argument( '--sim-sizes', type=int, nargs='+',
help='Number of reads to simulate for each round.')
parser.add_argument( '--prot-conc', type=float, default=7.75e-10,
help='The protein concentration.')
parser.add_argument( '--dna-conc', type=float, default=2e-8,
help='The DNA concentration.')
parser.add_argument( '--random-seed', type=int,
help='Set the random number generator seed.')
parser.add_argument( '--random-seq-pool-size', type=float, default=1e5,
help='The random pool size for the bootstrap.')
parser.add_argument( '--verbose', default=False, action='store_true',
help='Print extra status information.')
args = parser.parse_args()
pyTFbindtools.VERBOSE = args.verbose
if args.random_seed != None:
np.random.seed(args.random_seed)
if args.pwm != None:
pyTFbindtools.log("Loading PWM starting location", 'VERBOSE')
motifs = load_motifs(args.pwm.name)
assert len(motifs) == 1, "Motif file contains multiple motifs"
motif = motifs.values()[0][0]
args.pwm.close()
else:
assert args.energy_model != None, \
"Either --energy-model or --pwm must be specified"
pyTFbindtools.log("Loading energy data", 'VERBOSE')
motif = load_energy_data(args.energy_model.name)
args.starting_energy_model.close()
return ( motif, args.prot_conc, args.dna_conc,
args.sim_sizes,
int(args.random_seq_pool_size) )
def parse_arguments():
import argparse
parser = argparse.ArgumentParser(
description='Estimate energy models from a SELEX experiment.')
parser.add_argument( '--selex-files', nargs='+', type=file, required=True,
help='Files containing SELEX reads.')
parser.add_argument( '--background-sequence', type=file,
help='File containing reads sequenced from round 0.')
parser.add_argument( '--starting-pwm', type=file,
help='A PWM to start from.')
parser.add_argument( '--starting-energy-model', type=file,
help='An energy model to start from.')
parser.add_argument( '--initial-binding-site-len', type=int, default=6,
help='The starting length of the binding site (this will grow)')
parser.add_argument( '--lhd-convergence-eps', type=float, default=1e-8,
help='Convergence tolerance for lhd change.')
parser.add_argument( '--max-iter', type=float, default=1e5,
help='Maximum number of optimization iterations.')
parser.add_argument( '--momentum', type=float, default=0.1,
help='Optimization tuning param (between 0 and 1).')
parser.add_argument( '--random-seed', type=int,
help='Set the random number generator seed.')
parser.add_argument( '--random-seq-pool-size', type=float, default=1e6,
help='The random pool size for the bootstrap.')
parser.add_argument( '--verbose', default=False, action='store_true',
help='Print extra status information.')
parser.add_argument( '--debug-verbose', default=False, action='store_true',
help='Print debug information.')
args = parser.parse_args()
assert not (args.starting_pwm and args.starting_energy_model), \
"Can not set both --starting-pwm and --starting-energy_model"
pyTFbindtools.VERBOSE = args.verbose or args.debug_verbose
pyTFbindtools.DEBUG = args.debug_verbose
pyTFbindtools.selex.CONVERGENCE_MAX_LHD_CHANGE = args.lhd_convergence_eps
pyTFbindtools.selex.MAX_NUM_ITER = int(args.max_iter)
assert args.momentum < 1 and args.momentum >= 0
pyTFbindtools.selex.MOMENTUM = args.momentum
if args.random_seed != None:
np.random.seed(args.random_seed)
pyTFbindtools.log("Loading sequences", 'VERBOSE')
rnds_and_seqs = load_sequences(x.name for x in args.selex_files)
if args.starting_pwm != None:
pyTFbindtools.log("Loading PWM starting location", 'VERBOSE')
motifs = load_motifs(args.starting_pwm)
assert len(motifs) == 1, "Motif file contains multiple motifs"
motif = motifs.values()[0]
args.starting_pwm.close()
elif args.starting_energy_model != None:
pyTFbindtools.log("Loading energy data", 'VERBOSE')
motif = load_energy_data(args.starting_energy_model.name)
args.starting_energy_model.close()
else:
pyTFbindtools.log(
"Initializing starting location from %imer search" % args.initial_binding_site_len,
'VERBOSE')
factor_name = 'TEST'
bs_len = args.initial_binding_site_len
pwm = find_pwm(rnds_and_seqs, args.initial_binding_site_len)
motif = Motif("aligned_%imer" % args.initial_binding_site_len,
factor_name, pwm)
return motif, rnds_and_seqs, int(args.random_seq_pool_size)
