def match(args):
sample = dict([(m.id, m) for m in read_motifs(args.pfmfile)])
db = dict([(m.id, m) for m in read_motifs(args.dbpfmfile)])
mc = MotifComparer()
result = mc.get_best_matches(
sample.values(), args.nmatches, db.values(), "partial", "seqcor", "mean"
)
plotdata = []
print("Motif\tMatch\tScore\tP-value")
for motif_name, matches in result.items():
for match in matches:
pval, pos, orient = mc.compare_motifs(
sample[motif_name], db[match[0]], "partial", "seqcor", "mean", pval=True
)
print("%s\t%s\t%0.2f\t%0.3e" % (motif_name, match[0], match[1][0], pval))
motif = sample[motif_name]
dbmotif = db[match[0]]
if args.img:
if orient == -1:
tmp = dbmotif.id
dbmotif = dbmotif.rc()
dbmotif.id = tmp
if pos < 0:
tmp = motif.id
motif = Motif([[0.25, 0.25, 0.25, 0.25]] * -pos + motif.pwm)
motif.id = tmp
elif pos > 0:
tmp = dbmotif.id
dbmotif = Motif([[0.25, 0.25, 0.25, 0.25]] * pos + dbmotif.pwm)
dbmotif.id = tmp
diff = len(motif) - len(dbmotif)
if diff > 0:
dbmotif = Motif(dbmotif.pwm + [[0.25, 0.25, 0.25, 0.25]] * diff)
else:
motif = Motif(motif.pwm + [[0.25, 0.25, 0.25, 0.25]] * -diff)
plotdata.append((motif, dbmotif, pval))
if args.img:
match_plot(plotdata, args.img)
