def main():
from TAMO import MotifMetrics
if len(sys.argv) < 2:
print "Usage: %s <fasta_file>"%(re.sub('^.*/','',sys.argv[0]))
print ' [-w width (10)] Model Width (note AlignACE allows gaps)'
print ' [-iter (10)] Number of times to run AlignACE '
print ' [-genome fsafile] Genome (for computing background)'
print ' [-gcback (.38) GC background (use 0.44 for human, 0.38 for yeast)]'
sys.exit(1)
print "#" + ' '.join([x.replace(' ','\ ') for x in sys.argv])
fastafile = sys.argv[1]
width = 10
valid_tfs = []
iter = 10
genome = 'YEAST'
gcback = 0.38
for tok,i in zip(sys.argv,range(len(sys.argv))):
if tok == '-w' : width = int(sys.argv[i+1])
elif tok == '-valid' : valid_tfs.append(sys.argv[i+1])
elif tok == '-iter' : iter = int(sys.argv[i+1])
elif tok == '-gcback': gcback = float(sys.argv[i+1])
elif tok == '-genome' :
genome = sys.argv[i+1]
elif tok == '-H250' :
genome = 'HUMAN_250'
gcback = 0.44
elif tok == '-Ch22' :
genome = 'Ch22'
gcback = 0.44
theMeta = MetaAce(fastafile,width,iter,gcback)
Genome = MotifMetrics.ProbeSet(genome)
ids = Genome.ids_from_file(fastafile)
ids = Genome.filter(ids) #Only uses IDs that are actually in the Genome file
motifs = []
motifs.extend(theMeta.results)
for motif in motifs:
motif.pvalue = Genome.p_value(motif,ids,factor=0.7)
motif.church = Genome.church(motif,ids)
for valid_tf in valid_tfs:
motif.valid = Validate.validate(motif,valid_tf,'','Want Tuple')
motifs.sort(lambda x,y: cmp(x.church,y.church))
print_motifs(motifs,kmer_count=-1)
def main():
short_opts = 'f:'
long_opts = ['genome=', 'range=', 'top=', 'pcnt=', 'bgfile=']
try:
opts, args = getopt.getopt(sys.argv[1:], short_opts, long_opts)
except getopt.GetoptError:
print getopt.GetoptError.__dict__
usage()
if not opts: usage()
fastafile = ''
top_count = 10
top_pcnt = None
genome = 'YEAST'
w_start = 8
w_stop = 15
bgfile = MDSCAN_DIR + 'yeast_int.bg'
for opt, value in opts:
if opt == '-f': fastafile = value
if opt == '--genome': genome = value
if opt == '--top': top_count = int(value)
if opt == '--pcnt': top_pcnt = float(value)
if opt == '--range':
w_start, w_stop = [int(x) for x in value.split(',')]
print "#" + ' '.join(sys.argv)
probeids = Fasta.keys(fastafile)
Genome = MotifMetrics.ProbeSet(genome)
probeids = Genome.filter(probeids)
if top_pcnt:
top_count = max(top_count, int(top_pcnt / 100.0 * len(probeids)))
theMeta = metaMDscan(fastafile, w_start, w_stop, top_count)
for m in theMeta.motifs:
m.pvalue = Genome.p_value(m, probeids, 'v')
m.church = Genome.church(m, probeids, 'v')
sys.stdout.flush()
theMeta.motifs.sort(lambda x, y: cmp(x.pvalue, y.pvalue))
print_motifs(theMeta.motifs)
def main():
short_opts = 'f:'
long_opts = ['genome=', 'range=', 'top=', 'pcnt=', 'bgfile=']
try: opts, args = getopt.getopt(sys.argv[1:], short_opts, long_opts)
except getopt.GetoptError:
print getopt.GetoptError.__dict__
usage()
if not opts: usage()
fastafile = ''
top_count = 10
top_pcnt = None
genome = 'YEAST'
w_start = 8
w_stop = 15
bgfile = MDSCAN_DIR + 'yeast_int.bg'
for opt,value in opts:
if opt == '-f': fastafile = value
if opt == '--genome': genome = value
if opt == '--top': top_count = int(value)
if opt == '--pcnt': top_pcnt = float(value)
if opt == '--range': w_start,w_stop= [int(x) for x in value.split(',')]
print "#" + ' '.join(sys.argv)
probeids = Fasta.keys(fastafile)
Genome = MotifMetrics.ProbeSet(genome)
probeids = Genome.filter(probeids)
if top_pcnt: top_count = max(top_count,int(top_pcnt/100.0 * len(probeids)))
theMeta = metaMDscan(fastafile,w_start,w_stop,top_count)
for m in theMeta.motifs:
m.pvalue = Genome.p_value(m,probeids,'v')
m.church = Genome.church(m,probeids,'v')
sys.stdout.flush()
theMeta.motifs.sort(lambda x,y: cmp(x.pvalue,y.pvalue))
print_motifs(theMeta.motifs)
