/usr/share/pyshared/MACS2/PeakModel.py is in macs 2.0.9.1-1.
This file is owned by root:root, with mode 0o644.
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"""Module Description
Copyright (c) 2008,2009 Yong Zhang, Tao Liu <taoliu@jimmy.harvard.edu>
Copyright (c) 2010,2011 Tao Liu <taoliu@jimmy.harvard.edu>
This code is free software; you can redistribute it and/or modify it
under the terms of the Artistic License (see the file COPYING included
with the distribution).
@status: experimental
@version: $Revision$
@author: Yong Zhang, Tao Liu
@contact: taoliu@jimmy.harvard.edu
"""
import sys, time, random
def median (nums):
"""Calculate Median.
Parameters:
nums: list of numbers
Return Value:
median value
"""
p = sorted(nums)
l = len(p)
if l%2 == 0:
return (p[l/2]+p[l/2-1])/2
else:
return p[l/2]
class NotEnoughPairsException(Exception):
def __init__ (self,value):
self.value = value
def __str__ (self):
return repr(self.value)
class PeakModel:
"""Peak Model class.
"""
def __init__ (self, opt=None, treatment=None, max_pairnum=500, gz = 0, umfold=30, lmfold=10, bw=200, ts = 25, bg=0, quiet=False):
self.treatment = treatment
if opt:
self.gz = opt.gsize
self.umfold = opt.umfold
self.lmfold = opt.lmfold
self.tsize = opt.tsize
self.bw = opt.bw
self.info = opt.info
self.debug = opt.debug
self.warn = opt.warn
self.error = opt.warn
else:
self.gz = gz
self.umfold = umfold
self.lmfold = lmfold
self.tsize = ts
self.bg = bg
self.bw = bw
self.info = lambda x: sys.stderr.write(x+"\n")
self.debug = lambda x: sys.stderr.write(x+"\n")
self.warn = lambda x: sys.stderr.write(x+"\n")
self.error = lambda x: sys.stderr.write(x+"\n")
if quiet:
self.info = lambda x: None
self.debug = lambda x: None
self.warn = lambda x: None
self.error = lambda x: None
self.max_pairnum = max_pairnum
self.summary = ""
self.plus_line = None
self.minus_line = None
self.shifted_line = None
self.d = None
self.scan_window = None
self.min_tags = None
self.peaksize = None
self.build()
def build (self):
"""Build the model.
prepare self.d, self.scan_window, self.plus_line,
self.minus_line and self.shifted_line to use.
"""
self.peaksize = 2*self.bw
self.min_tags = float(self.treatment.total) * self.lmfold * self.peaksize / self.gz /2 # mininum unique hits on single strand
self.max_tags = float(self.treatment.total) * self.umfold * self.peaksize / self.gz /2 # maximum unique hits on single strand
#print self.min_tags
#print self.max_tags
# use treatment data to build model
paired_peakpos = self.__paired_peaks ()
# select up to 1000 pairs of peaks to build model
num_paired_peakpos = 0
num_paired_peakpos_remained = self.max_pairnum
num_paired_peakpos_picked = 0
for c in paired_peakpos.keys():
num_paired_peakpos +=len(paired_peakpos[c])
if num_paired_peakpos_remained == 0:
paired_peakpos.pop(c)
else:
paired_peakpos[c] = paired_peakpos[c][:num_paired_peakpos_remained]
num_paired_peakpos_remained -= len(paired_peakpos[c])
num_paired_peakpos_picked += len(paired_peakpos[c])
self.info("#2 number of paired peaks: %d" % (num_paired_peakpos))
if num_paired_peakpos < 100:
self.error("Too few paired peaks (%d) so I can not build the model! Broader your MFOLD range parameter may erase this error. If it still can't build the model, please use --nomodel and --shiftsize 100 instead." % (num_paired_peakpos))
self.error("Process for pairing-model is terminated!")
raise NotEnoughPairsException("No enough pairs to build model")
elif num_paired_peakpos < self.max_pairnum:
self.warn("Fewer paired peaks (%d) than %d! Model may not be build well! Lower your MFOLD parameter may erase this warning. Now I will use %d pairs to build model!" % (num_paired_peakpos,self.max_pairnum,num_paired_peakpos_picked))
self.debug("Use %d pairs to build the model." % (num_paired_peakpos_picked))
self.__paired_peak_model(paired_peakpos)
def __str__ (self):
"""For debug...
"""
return """
Summary of Peak Model:
Baseline: %d
Upperline: %d
Fragment size: %d
Scan window size: %d
""" % (self.min_tags,self.max_tags,self.d,self.scan_window)
def __paired_peak_model (self, paired_peakpos):
"""Use paired peak positions and treatment tag positions to build the model.
Modify self.(d, model_shift size and scan_window size. and extra, plus_line, minus_line and shifted_line for plotting).
"""
window_size = 1+2*self.peaksize
self.plus_line = [0]*window_size
self.minus_line = [0]*window_size
for chrom in paired_peakpos.keys():
paired_peakpos_chrom = paired_peakpos[chrom]
tags = self.treatment.get_locations_by_chr(chrom)
tags_plus = tags[0]
tags_minus = tags[1]
# every paired peak has plus line and minus line
# add plus_line
self.plus_line = self.__model_add_line (paired_peakpos_chrom, tags_plus,self.plus_line)
# add minus_line
self.minus_line = self.__model_add_line (paired_peakpos_chrom, tags_minus,self.minus_line)
# find top
plus_tops = []
minus_tops = []
plus_max = max(self.plus_line)
minus_max = max(self.minus_line)
for i in range(window_size):
if self.plus_line[i] == plus_max:
plus_tops.append(i)
if self.minus_line[i] == minus_max:
minus_tops.append(i)
self.d = minus_tops[len(minus_tops)/2] - plus_tops[len(plus_tops)/2] + 1
shift_size = self.d/2
# find the median point
#plus_median = median(self.plus_line)
#minus_median = median(self.minus_line)
self.scan_window = max(self.d,self.tsize)*2
# a shifted model
self.shifted_line = [0]*window_size
plus_shifted = [0]*shift_size
plus_shifted.extend(self.plus_line[:-1*shift_size])
minus_shifted = self.minus_line[shift_size:]
minus_shifted.extend([0]*shift_size)
#print "d:",self.d,"shift_size:",shift_size
#print len(self.plus_line),len(self.minus_line),len(plus_shifted),len(minus_shifted),len(self.shifted_line)
for i in range(window_size):
self.shifted_line[i]=minus_shifted[i]+plus_shifted[i]
return True
def __model_add_line (self, pos1, pos2, line):
"""Project each pos in pos2 which is included in
[pos1-self.peaksize,pos1+self.peaksize] to the line.
"""
i1 = 0 # index for pos1
i2 = 0 # index for pos2
i2_prev = 0 # index for pos2 in previous pos1
# [pos1-self.peaksize,pos1+self.peaksize]
# region
i1_max = len(pos1)
i2_max = len(pos2)
last_p2 = -1
flag_find_overlap = False
while i1<i1_max and i2<i2_max:
p1 = pos1[i1]
p2 = pos2[i2]
if p1-self.peaksize > p2: # move pos2
i2 += 1
elif p1+self.peaksize < p2: # move pos1
i1 += 1
i2 = i2_prev # search minus peaks from previous index
flag_find_overlap = False
else: # overlap!
if not flag_find_overlap:
flag_find_overlap = True
i2_prev = i2 # only the first index is recorded
# project
for i in range(p2-p1+self.peaksize-self.tsize/2,p2-p1+self.peaksize+self.tsize/2):
if i>=0 and i<len(line):
line[i]+=1
i2+=1
return line
def __paired_peaks (self):
"""Call paired peaks from fwtrackI object.
Return paired peaks center positions.
"""
chrs = self.treatment.get_chr_names()
chrs.sort()
paired_peaks_pos = {}
for chrom in chrs:
self.debug("Chromosome: %s" % (chrom))
tags = self.treatment.get_locations_by_chr(chrom)
plus_peaksinfo = self.__naive_find_peaks (tags[0])
self.debug("Number of unique tags on + strand: %d" % (len(tags[0])))
self.debug("Number of peaks in + strand: %d" % (len(plus_peaksinfo)))
minus_peaksinfo = self.__naive_find_peaks (tags[1])
self.debug("Number of unique tags on - strand: %d" % (len(tags[1])))
self.debug("Number of peaks in - strand: %d" % (len(minus_peaksinfo)))
if not plus_peaksinfo or not minus_peaksinfo:
self.debug("Chrom %s is discarded!" % (chrom))
continue
else:
paired_peaks_pos[chrom] = self.__find_pair_center (plus_peaksinfo, minus_peaksinfo)
self.debug("Number of paired peaks: %d" %(len(paired_peaks_pos[chrom])))
return paired_peaks_pos
def __find_pair_center (self, pluspeaks, minuspeaks):
ip = 0 # index for plus peaks
im = 0 # index for minus peaks
im_prev = 0 # index for minus peaks in previous plus peak
pair_centers = []
ip_max = len(pluspeaks)
im_max = len(minuspeaks)
flag_find_overlap = False
while ip<ip_max and im<im_max:
(pp,pn) = pluspeaks[ip] # for (peakposition, tagnumber in peak)
(mp,mn) = minuspeaks[im]
if pp-self.peaksize > mp: # move minus
im += 1
elif pp+self.peaksize < mp: # move plus
ip += 1
im = im_prev # search minus peaks from previous index
flag_find_overlap = False
else: # overlap!
if not flag_find_overlap:
flag_find_overlap = True
im_prev = im # only the first index is recorded
if float(pn)/mn < 2 and float(pn)/mn > 0.5: # number tags in plus and minus peak region are comparable...
if pp < mp:
pair_centers.append((pp+mp)/2)
#self.debug ( "distance: %d, minus: %d, plus: %d" % (mp-pp,mp,pp))
im += 1
return pair_centers
def __naive_find_peaks (self, taglist ):
"""Naively call peaks based on tags counting.
Return peak positions and the tag number in peak region by a tuple list [(pos,num)].
"""
peak_info = [] # store peak pos in every peak region and
# unique tag number in every peak region
if len(taglist)<2:
return peak_info
pos = taglist[0]
current_tag_list = [pos] # list to find peak pos
for i in range(1,len(taglist)):
pos = taglist[i]
if (pos-current_tag_list[0]+1) > self.peaksize: # call peak in current_tag_list
# a peak will be called if tag number is ge min tags.
if len(current_tag_list) >= self.min_tags and len(current_tag_list) <= self.max_tags:
peak_info.append((self.__naive_peak_pos(current_tag_list),len(current_tag_list)))
current_tag_list = [] # reset current_tag_list
current_tag_list.append(pos) # add pos while 1. no
# need to call peak;
# 2. current_tag_list is []
return peak_info
def __naive_peak_pos (self, pos_list ):
"""Naively calculate the position of peak.
return the highest peak summit position.
"""
peak_length = pos_list[-1]+1-pos_list[0]+self.tsize
start = pos_list[0] -self.tsize/2
horizon_line = [0]*peak_length # the line for tags to be projected
for pos in pos_list:
for pp in range(int(pos-start-self.tsize/2),int(pos-start+self.tsize/2)): # projected point
horizon_line[pp] += 1
top_pos = [] # to record the top positions. Maybe > 1
top_p_num = 0 # the maximum number of projected points
for pp in range(peak_length): # find the peak posistion as the highest point
if horizon_line[pp] > top_p_num:
top_p_num = horizon_line[pp]
top_pos = [pp]
elif horizon_line[pp] == top_p_num:
top_pos.append(pp)
return (top_pos[int(len(top_pos)/2)]+start)
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