def HMMToPeaks(hmmStates,treatbins,Binsize):
''' Parse HMM result to Peaks. '''
# parse HMM and generate peak files.
print >>sys.stderr, printTime(), "Parse Peaks from HMM result."
peaks=[]
pval=[]
cnt=1
for chrom,start,stop in BamBins.parseHMM(hmmStates,Binsize):
tpeak=Peak([chrom,start,stop,histmark+"_"+str(cnt)])
bins=treatBins[chrom][start/Binsize:stop/Binsize]
tpeak.score=max(bins)
tpeak.signalvalue=numpy.mean(bins)
tpeak.pvalue = -10*numpy.log10(lprob.poisson_cdf(tpeak.score*100,lams[chrom],False))
tpeak.peak=bins.argmax()*Binsize+Binsize/2
# append to peaks
peaks.append(tpeak)
#pval.append(tpeak.pvalue)
cnt+=1
#qval=storey_qvalues(pval)
#for i in xrange(len(peaks)):
#peaks[i].pvalue=-10*numpy.log10(pval[i])
#peaks[i].qvalue=-10*numpy.log10(qval[i])
print >>sys.stderr, printTime(), "Parse Peaks finished."
print >>sys.stderr
return peaks
def callPeakFromBins(Bins,pvalue=1e-5):
''' Call peak with poisson distribution. Return the hmmStates, lamda and threshold for each chromosome.'''
print >>sys.stderr, printTime(), "Call peak for each chromosome."
hmmStates={}
lams={}
for chrom in Bins:
# All bin values are multiplied by 100, because the threshold is usually integers.
lam = sum(Bins[chrom])/len(Bins[chrom])*100
# find the optimal threshold by binary search
lthre=0.0
hthre=max(Bins[chrom])*100.0 #
while hthre-lthre>0.01:
pval = lprob.poisson_cdf((hthre+lthre)/2,lam,False)
if pval > pvalue:
lthre=(hthre+lthre)/2
else:
hthre=(hthre+lthre)/2
# Print threshold
print >>sys.stderr, printTime(), chrom, "lambda=",lam,"threshold=",hthre
# convert to binary value
hmmStates[chrom]=(numpy.greater_equal(Bins[chrom],hthre/100)-0).tolist()
lams[chrom]=lam
print >>sys.stderr, printTime(), "Call peak finished."
print >>sys.stderr
return (hmmStates,lams)
