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#!/usr/bin/env python
from sys import stdout, stderr, exit, argv, maxint
from copy import deepcopy
from bisect import bisect
from itertools import izip, product
from os.path import basename, dirname
from random import randint
from math import ceil
import logging
import csv
DIRECTION_CRICK_STRAND = '+'
DIRECTION_WATSON_STRAND = '-'
class BothStrands:
def __eq__(self, x):
return x == '+' or x =='-' or isinstance(x, BothStrands)
def __str__(self):
return '+/-'
DIRECTION_BOTH_STRANDS = BothStrands()
LOG_FILENAME = 'info.log'
class Run:
# public variables
direction = None
startG1 = None
startG2 = None
endG1 = None
endG2 = None
weight = None
def __init__(self, startG1, startG2, weight, direction):
self.direction = direction
self.startG1 = startG1
self.startG2 = startG2
self.endG1 = startG1
self.endG2 = startG2
self.weight = list()
self.weight.append(weight)
def getWeight(self, alpha):
adjTerm = 0
if len(self.weight) > 1:
adjTerm = sum([self.weight[i] * self.weight[i+1] for i in
xrange(len(self.weight)-1)])
edgeTerm = sum([w **2 for w in self.weight])
# edgeTerm = max(self.weight)**2
return alpha * adjTerm + (1-alpha) * edgeTerm
def extendRun(self, nextG1, nextG2, weight):
if self.direction == DIRECTION_CRICK_STRAND:
self.endG1 = nextG1
self.endG2 = nextG2
self.weight.append(weight)
else:
self.endG1 = nextG1
self.startG2 = nextG2
self.weight.append(weight)
def __len__(self):
return len(self.weight)
def __str__(self):
return 'G1:%s-%s G2:%s-%s %s (%.5f)' %(self.startG1, self.endG1,
self.startG2, self.endG2, self.direction, self.getWeight(alpha))
#class DummyRun(Run):
# def __init__(self, weights):
# self.weight = weights
def readDistsAndOrder(data, edgeThreshold):
res = dict()
hasMultipleChromosomes = False
g1_chromosomes = dict()
g2_chromosomes = dict()
chr1 = 0
chr2 = 0
for line in csv.reader(data, delimiter='\t'):
if not res:
hasMultipleChromosomes = len(line) == 6
if hasMultipleChromosomes:
chr1 = line[0]
g1 = int(line[1])
chr2 = line[2]
g2 = int(line[3])
direction = line[4]
edgeWeight = float(line[5])
else:
g1 = int(line[0])
g2 = int(line[1])
direction = line[2]
edgeWeight = float(line[3])
if edgeWeight < edgeThreshold:
continue
if not g1_chromosomes.has_key(chr1):
g1_chromosomes[chr1] = set()
if not g2_chromosomes.has_key(chr2):
g2_chromosomes[chr2] = set()
g1_chromosomes[chr1].add(g1)
g2_chromosomes[chr2].add(g2)
l0 = (chr1, g1)
l1 = (chr2, g2)
if l0 not in res:
res[l0] = dict()
# append mapping pos in mappedGenome and the weight of the corresponding edge
res[l0][l1] = (direction == '1' and DIRECTION_CRICK_STRAND or \
DIRECTION_WATSON_STRAND, edgeWeight)
# construct genome order
tel1, g1 = establish_linear_genome_order(g1_chromosomes)
tel2, g2 = establish_linear_genome_order(g2_chromosomes)
# add telomeres
for t1, t2 in product(tel1, tel2):
if not res.has_key(t1):
res[t1] = dict()
res[t1][t2] = (DIRECTION_BOTH_STRANDS, 1)
# res[maxint] = dict([
# (maxint, (DIRECTION_WATSON_STRAND, 1)),
# (0, (DIRECTION_WATSON_STRAND, 1)),
# (maxint, (DIRECTION_CRICK_STRAND, 1)),
# (0, (DIRECTION_CRICK_STRAND, 1))])
# res[maxint] = dict([
# (maxint, (DIRECTION_WATSON_STRAND, 1)),
# (0, (DIRECTION_WATSON_STRAND, 1)),
# (maxint, (DIRECTION_CRICK_STRAND, 1)),
# (0, (DIRECTION_CRICK_STRAND, 1))])
return hasMultipleChromosomes, g1, g2, res
def establish_linear_genome_order(chromosomes):
g = list()
telomeres = set()
for k in sorted(chromosomes.keys()):
g.append((k, -1))
telomeres.add((k, -1))
g.extend([(k, i) for i in sorted(chromosomes[k])])
g.append((k, maxint))
telomeres.add((k, maxint))
return telomeres, g
def insertIntoRunList(runs, runList):
keys = map(lambda x: x.getWeight(alpha), runList)
for run in runs:
i = bisect(keys, run.getWeight(alpha))
keys.insert(i, run.getWeight(alpha))
runList.insert(i, run)
def checkMatching(g1, g2, g1_runs, g2_runs, runs, dist):
g1pos = dict(izip(g1, xrange(len(g1))))
g2pos = dict(izip(g2, xrange(len(g2))))
if len(g1) != len(g2):
logging.error(('G1 and G2 have unequal length: len(G1) = %s, len(G2)' + \
' %s') %(len(g1), len(g2)))
if len(g1) != len(g1_runs) or len(g2) != len(g2_runs):
logging.error(('Annotation vector length doesn\'t match with genome ' + \
'length: len(G1) = %s, len(g1_runs) = %s, len(G2) = %s, len(' + \
'g2_runs) = %s') %(len(g1), len(g1_runs), len(g2),
len(g2_runs)))
all_included = set()
r_counter = 0
prev_run = None
c_adj = 0
for i in xrange(len(g1)):
if not g1_runs[i]:
logging.error('Gene %s is not included in any run' %g1[i])
continue
if len(g1_runs[i]) > 1:
logging.error('Gene %s is included in more than one run: %s' %(g1[i],
', '.join(map(str, g1_runs[i]))))
continue
r = list(g1_runs[i])[0]
if prev_run != r:
c_adj += len(r.weight)-1
if r not in runs:
logging.error('Run %s not included in run list.' %r)
if r in all_included:
logging.error(('Run %s occurs twice in G1. Current gene ' + \
'position: %s') % (r, g1[i]))
r_counter += len(r.weight)
prev_run = r
all_included.add(r)
k = i-g1pos[r.startG1]
if r.direction == DIRECTION_CRICK_STRAND:
g2j = g2[g2pos[r.startG2] + k]
else:
g2j = g2[g2pos[r.endG2] - k]
eWgt = dist[g1[i]][g2j][1]
if r.weight[k] != eWgt:
logging.error(('Edge weight of %s-%s differs in run %s, should be' + \
' %.6f but is %.6f') %(g1[i], g2j, r, eWgt, r.weight[k]))
missing_runs = all_included.symmetric_difference(runs)
if missing_runs:
logging.error(('Additional runs in runslist that are not part in the' + \
' matching: %s') %(map(str, missing_runs)))
logging.info('Number of adjacencies is %s in matching of size %s.' %(c_adj,
len(g1)))
if r_counter != len(g1):
logging.error(('Sum of run lengths does not equal matching size! Sum ' + \
'of run lengths: %s, matching size: %s') % (r_counter, len(g1)))
for j in xrange(len(g2)):
if not g2_runs[j]:
logging.error('Gene %s is not included in any run' %g2[j])
if len(g2_runs[j]) > 1:
logging.error('Gene %s is included in more than one run: %s' %(g2[j],
', '.join(map(str, g2_runs[j]))))
if g2_runs[j].difference(all_included):
logging.error('G2 differs in runs from G1 on position %s: %s' %(g2[j],
', '.join(map(str,g2_runs[j].difference(all_included)))))
for r in runs:
if r.startG1 not in g1pos or r.endG1 not in g1pos or r.startG2 not in \
g2pos or r.endG2 not in g2pos:
logging.error(('Positions of run %s can not be mapped back to the' + \
' genomes.') %r)
continue
if len(g1) <= g1pos[r.startG1] or len(g1) <= g1pos[r.endG1] or \
len(g2) <= g2pos[r.startG2] or len(g2) <= g2pos[r.endG2]:
logging.error(('Positions of run %s exceed borders of the ' + \
'genomes') % r)
continue
if g1[g1pos[r.startG1]] != r.startG1 or g2[g2pos[r.startG2]] != \
r.startG2:
logging.error(('Start of run %s is not coherent with genome ' + \
'position on %s (G1) or %s (G2)') %(r, g1[g1pos[r.startG1]],
g2[g2pos[r.startG2]]))
if g1[g1pos[r.endG1]] != r.endG1 or g2[g2pos[r.endG2]] != r.endG2:
logging.error(('End of run %s is not coherent with genome ' + \
'position on %s (G1) or %s (G2)') %(r, g1[g1pos[r.endG1]],
g2[g2pos[r.endG2]]))
if g1pos[r.endG1] - g1pos[r.startG1] != g2pos[r.endG2] - \
g2pos[r.startG2] or g1pos[r.endG1] - g1pos[r.startG1] < 0:
logging.error(('Length of run %s is erroneous: %s (on G1), %s ' + \
'(on G2)') %(r, g1pos[r.endG1] - g1pos[r.startG1],
g2pos[r.endG2] - g2pos[r.startG2]))
if len(r.weight) != g1pos[r.endG1] - g1pos[r.startG1] + 1:
logging.error(('Number of weights does not comply with run length. ' + \
'Weights: %s, run length: %s, run: %s') %(len(r.weight),
g1pos[r.endG1] - g1pos[r.startG1], r))
g1_chromosomes = set(map(lambda x: x[0], g1[g1pos[r.startG1]:g1pos[r.endG1]+1]))
g2_chromosomes = set(map(lambda x: x[0], g2[g2pos[r.startG2]:g2pos[r.endG2]+1]))
if len(g1_chromosomes) != 1 and len(g2_chromosomes) != 1:
logging.error(('Number of chromosomes on G1 (#chrs: %s) or G2 ' + \
'(#chrs: %s) in run %s is not 1 (Meaning that possibly' + \
' the run extends over two or more chromosomes, which ' + \
'shouldn\'t be allowed).') %(len(g1_chromosomes),
len(g2_chromosomes), r))
# are all runs merged that can be merged?
run_ends = dict()
for r in runs:
if r.direction == DIRECTION_CRICK_STRAND:
run_ends[r.startG1] = (r.direction, r.startG2)
run_ends[r.endG1] = (r.direction, r.endG2)
else:
run_ends[r.startG1] = (r.direction, r.endG2)
run_ends[r.endG1] = (r.direction, r.startG2)
for i in xrange(len(g1)-1):
g1i = g1[i]
g1i2 = g1[i+1]
if g1i in run_ends and g1i2 in run_ends and run_ends[g1i][0] == \
run_ends[g1i2][0] and g1_runs[i] != g1_runs[i+1]:
direction = run_ends[g1i][0]
g2i = run_ends[g1i][1]
g2i2 = run_ends[g1i2][1]
if direction == DIRECTION_CRICK_STRAND and g2pos[g2i] == g2pos[g2i2]-1:
logging.error('Runs %s and %s could be merged, but are not!' % (map(str, g1_runs[i])[0], map(str, g1_runs[i+1])[0]))
elif direction == DIRECTION_WATSON_STRAND and g2pos[g2i] == g2pos[g2i2]+1:
logging.error('Runs %s and %s could be merged, but are not!' % (map(str, g1_runs[i])[0], map(str, g1_runs[i+1])[0]))
def getAllRuns(g1, g2, d):
g2pos = dict(izip(g2, xrange(len(g2))))
g1_runs = [set() for _ in g1]
g2_runs = [set() for _ in g2]
activeRuns = list()
reportedRuns= list()
for i in xrange(len(g1)):
curPos = g1[i]
newRunList = list()
forbiddenRunStarts = list()
# check if link exists, otherwise terminate all runs
e = curPos in d
# iterate over all runs
for r in activeRuns:
jEnd= g2pos[r.endG2]
jStart = g2pos[r.startG2]
if r.startG1[0] != curPos[0]:
# run could not be extended
logging.info(('Terminate and report run %s, because %s is on a' + \
' different chromosome.') %(r, curPos))
reportedRuns.append(r)
continue
# extend to the right
if e and r.direction == DIRECTION_CRICK_STRAND and len(g2) > jEnd + 1 \
and g2[jEnd+1] in d[curPos] and d[curPos][g2[jEnd+1]][0] == \
DIRECTION_CRICK_STRAND and g2[jEnd+1][0] == r.endG2[0]:
g2_gene_r = g2[jEnd+1]
r.extendRun(curPos, g2_gene_r, d[curPos][g2_gene_r][1])
newRunList.append(r)
forbiddenRunStarts.append((DIRECTION_CRICK_STRAND, g2_gene_r))
g1_runs[i].add(r)
g2_runs[jEnd+1].add(r)
logging.debug('Extended run %s to the right' %r)
# extend to the left
elif e and r.direction == DIRECTION_WATSON_STRAND and jStart > 0 and \
g2[jStart-1] in d[curPos] and d[curPos][g2[jStart-1]][0] == \
DIRECTION_WATSON_STRAND and g2[jStart-1][0] == r.startG2[0]:
g2_gene_l = g2[jStart-1]
r.extendRun(curPos, g2_gene_l, d[curPos][g2_gene_l][1])
newRunList.append(r)
g1_runs[i].add(r)
g2_runs[jStart-1].add(r)
forbiddenRunStarts.append((DIRECTION_WATSON_STRAND, g2_gene_l))
logging.debug('Extended run %s to the left' %r)
else:
# run could not be extended
logging.info(('Terminate and report run %s, because %s has '
+ 'no further consecutive edge.') %(r, curPos))
reportedRuns.append(r)
# if no edge exists, nothing has to be done...
if e:
for (g2_gene, (direction, weight)) in d[curPos].items():
if (direction, g2_gene) not in forbiddenRunStarts:
j = g2pos[g2_gene]
if isinstance(direction, BothStrands):
r = Run(curPos, g2_gene, weight, DIRECTION_CRICK_STRAND)
newRunList.append(r)
g1_runs[i].add(r)
g2_runs[j].add(r)
logging.debug(('Start new (%s) run %s') %(direction, r))
r = Run(curPos, g2_gene, weight, DIRECTION_WATSON_STRAND)
newRunList.append(r)
g1_runs[i].add(r)
g2_runs[j].add(r)
logging.debug(('Start new (%s) run %s') %(direction, r))
else:
r = Run(curPos, g2_gene, weight, direction)
newRunList.append(r)
g1_runs[i].add(r)
g2_runs[j].add(r)
logging.debug(('Start new (%s) run %s') %(direction, r))
activeRuns = newRunList
reportedRuns.extend(activeRuns)
return (g1_runs, g2_runs, reportedRuns)
def replaceByNew(g1_runs, g2_runs, i, j, r_old, r_new):
while r_old in g1_runs[i]:
g1_runs[i].remove(r_old)
g1_runs[i].add(r_new)
g2_runs[j].remove(r_old)
g2_runs[j].add(r_new)
i+=1
j+=1
if len(g1_runs) <= i or len(g2_runs) <= j:
break
def doMatching(g1, g2, g1_runs, g2_runs, m, runList):
g1pos = dict(izip(g1, xrange(len(g1))))
g2pos = dict(izip(g2, xrange(len(g2))))
newRuns = set()
for k in xrange(g1pos[m.endG1] - g1pos[m.startG1] + 1):
i = g1pos[m.startG1] + k
j = g2pos[m.startG2] + k
for r in set(g1_runs[i]):
if r == m:
continue
g1_runs[i].remove(r)
if r in runList:
runList.remove(r)
if g1pos[r.startG1] < i:
overlap = g1pos[r.endG1] - i
logging.info(('Run %s overlaps with selected run %s by %s ' + \
'at position G1:%s.') %(r, m, overlap+1, g1[i]))
r_new = deepcopy(r)
r_new.endG1 = g1[i-1]
if r.direction == DIRECTION_CRICK_STRAND:
# check weight
r_new.endG2 = g2[g2pos[r.endG2] - overlap -1]
r_new.weight = r.weight[:-overlap-1]
r.weight = r.weight[-overlap-1:]
r.startG2 = g2[g2pos[r.endG2]-overlap]
g2_runs[g2pos[r.startG2]].remove(r)
else:
r_new.startG2 = g2[g2pos[r.startG2] + overlap + 1]
r_new.weight = r.weight[:-overlap-1]
r.weight = r.weight[-overlap-1:]
r.endG2 = g2[g2pos[r.startG2] + overlap]
g2_runs[g2pos[r.endG2]].remove(r)
r.startG1 = g1[i]
logging.info('Divided overlapping run in %s and %s' %(r_new, r))
# do you see that r.startG2 is already at the right position?
replaceByNew(g1_runs, g2_runs, g1pos[r_new.startG1],
g2pos[r_new.startG2], r, r_new)
newRuns.add(r_new)
elif g1pos[r.startG1] == i:
if r.direction == DIRECTION_CRICK_STRAND:
g2_runs[g2pos[r.startG2]].remove(r)
else:
g2_runs[g2pos[r.endG2]].remove(r)
if len(g1) > i+1 and i < g1pos[r.endG1]:
# run start cannot be larger than i
logging.info(('Run %s interfers with current run %s at ' + \
'position G1:%s. Shifting.') %(r, m, g1[i]))
r.startG1 = g1[i+1]
del r.weight[0]
if r.direction == DIRECTION_CRICK_STRAND:
r.startG2 = g2[g2pos[r.startG2]+1]
else:
r.endG2 = g2[g2pos[r.endG2]-1]
logging.info('Shifted run is now located at %s' %r)
newRuns.add(r)
elif r in newRuns:
newRuns.remove(r)
for r in set(g2_runs[j]):
if r == m:
continue
g2_runs[j].remove(r)
if r in runList:
runList.remove(r)
if g2pos[r.startG2] < j:
overlap = g2pos[r.endG2] - j
logging.info(('Run %s overlaps with selected run %s by %s ' + \
'at position G2:%s.') %(r, m, overlap+1, g2[j]))
r_new = deepcopy(r)
r_new.endG2 = g2[j-1]
if r.direction == DIRECTION_CRICK_STRAND:
r_new.endG1 = g1[g1pos[r.endG1]-overlap -1]
r_new.weight = r.weight[:-overlap-1]
r.weight = r.weight[-overlap-1:]
r.startG1 = g1[g1pos[r.endG1]-overlap]
g1_runs[g1pos[r.startG1]].remove(r)
else:
r_new.startG1 = g1[g1pos[r.startG1]+overlap+1]
r_new.weight = r.weight[overlap+1:]
r.weight = r.weight[:overlap+1]
r.endG1 = g1[g1pos[r.startG1]+overlap]
g1_runs[g1pos[r.endG1]].remove(r)
r.startG2 = g2[j]
logging.info('Divided overlapping run in %s and %s' %(r_new, r))
# # do you see that r.startG1 is already at the right position?
# if r.direction == DIRECTION_CRICK_STRAND:
# g1_runs[g1pos[r.endG1]].remove(r)
# else:
# g1_runs[g1pos[r.startG1]].remove(r)
replaceByNew(g1_runs, g2_runs, g1pos[r_new.startG1],
g2pos[r_new.startG2], r, r_new)
newRuns.add(r_new)
elif g2pos[r.startG2] == j:
if r.direction == DIRECTION_CRICK_STRAND:
g1_runs[g1pos[r.startG1]].remove(r)
else:
g1_runs[g1pos[r.endG1]].remove(r)
if len(g2) > j+1 and j < g2pos[r.endG2]:
# run start cannot be larger than j
logging.info(('Run %s interfers with current run %s at ' + \
'position G2:%s. Shifting.') %(r, m, g2[j]))
r.startG2 = g2[j+1]
if r.direction == DIRECTION_CRICK_STRAND:
r.startG1 = g1[g1pos[r.startG1]+1]
del r.weight[0]
else:
r.endG1 = g1[g1pos[r.endG1]-1]
del r.weight[-1]
logging.info('Shifted run is now located at %s' %r)
newRuns.add(r)
elif r in newRuns:
newRuns.remove(r)
insertIntoRunList(newRuns, runList)
def mergeRuns(mod_g1, g1, g2, g1_runs, g2_runs, runList, alreadyMatched):
g1pos = dict(izip(g1, xrange(len(g1))))
g2pos = dict(izip(g2, xrange(len(g2))))
newRuns = set()
wSrt = lambda x: x.getWeight(alpha)
mod_g1 = list(mod_g1)
for x in xrange(len(mod_g1)):
g1i = mod_g1[x]
i = g1pos[g1i]
if len(g1) < i+2:
continue
# To understand this piece of code, one observation is important:
# If r1 or r2 is already matched, then there exist only one combination
# of possible merges. If r1 and r2 are both unmatched, several merges
# are possible and all should be done.
# After each merge between a matched and unmatched run, the newly
# merged run must be completely matched, before further modification
# points (mod_g1) can be processed.
for r1, r2 in product(sorted(g1_runs[i].difference(g1_runs[i+1]),
key=wSrt, reverse=True),
sorted(g1_runs[i+1].difference(g1_runs[i]), key=wSrt,
reverse=True)):
if r1.endG1 == g1[i] and r2.startG1 == g1[i+1] and \
r1.direction == r2.direction and \
r1.endG1[0] == r2.startG1[0] and \
r1.endG2[0] == r2.startG2[0] and \
((r1.direction == DIRECTION_CRICK_STRAND and \
g2pos[r1.endG2] == g2pos[r2.startG2] -1) or \
(r1.direction == DIRECTION_WATSON_STRAND and \
g2pos[r2.endG2] == g2pos[r1.startG2] -1)):
logging.info('Merge runs %s and %s.' %(r1, r2))
if r1 in runList:
runList.remove(r1)
if r2 in runList:
runList.remove(r2)
if r1 in newRuns:
# ye-ah, this can happen too :/
newRuns.remove(r1)
r2.startG1 = r1.startG1
r2.weight = r1.weight + r2.weight
if r1.direction == DIRECTION_CRICK_STRAND:
r2.startG2 = r1.startG2
else:
r2.endG2 = r1.endG2
logging.info('Merged run is %s' %r2)
replaceByNew(g1_runs, g2_runs, g1pos[r1.startG1],
g2pos[r1.startG2], r1, r2)
if (r2 in alreadyMatched) ^ (r1 in alreadyMatched):
if r1 in alreadyMatched:
alreadyMatched.remove(r1)
# redo matching in case r1 xor r2 were not in matching before
insertIntoRunList(newRuns, runList)
return r2, set(mod_g1[x+1:])
if r2 in alreadyMatched:
# actually, both are already matched
alreadyMatched.add(r2)
alreadyMatched.remove(r1)
else:
# none is matched
newRuns.add(r2)
insertIntoRunList(newRuns, runList)
return None, []
def removeSingleGenes(genome, genome_runs):
del_res = set()
mod_res = set()
i = 0
while i < len(genome):
if not genome_runs[i]:
del_res.add(genome[i])
mod_res.add(genome[i-1])
del genome[i]
del genome_runs[i]
else:
i+=1
return del_res, mod_res
def findRandomRunSequence(g1, g2, dists, topXperCent):
g2dists = dict()
for g1i, x in dists.items():
for g2j, d in x.items():
if g2j not in g2dists:
g2dists[g2j] = dict()
g2dists[g2j][g1i] = d
# copy g1, g2 and dists map, because we'll modify it. Also remove all genes
# that do not contain edges.
g1 = [x for x in g1 if dists.has_key(x) and len(dists[x])]
g2 = [x for x in g2 if g2dists.has_key(x) and len(g2dists[x])]
g1pos = dict(izip(g1, xrange(len(g1))))
g1_runs, g2_runs, runs = getAllRuns(g1, g2, dists)
logging.info('Found %s runs.' %len(runs))
# sort
runList = sorted(runs, key=lambda x: x.getWeight(alpha))
res = set()
while runList:
noOfAdjacencies = len(filter(lambda x: x.getWeight(alpha) and x.getWeight(alpha) or 0, runList))
if noOfAdjacencies:
randPos = randint(1, ceil(noOfAdjacencies * topXperCent))
else:
randPos = randint(1, ceil(len(runList) * topXperCent))
logging.info('From %s, select randomly among top %s run %s' %(len(runList), int(ceil((noOfAdjacencies or len(runList))* topXperCent)), runList[-randPos]))
mx = runList.pop(-randPos)
mod_g1 = set()
while mx:
res.add(mx)
# update run list
doMatching(g1, g2, g1_runs, g2_runs, mx, runList)
del_g1, new_mod_g1 = removeSingleGenes(g1, g1_runs)
if del_g1:
logging.info('Zombie genes removed from G1: %s' %', '.join(map(str, del_g1)))
# it can happen that a gene in mod_g1 has already been deleted
# before being processed. This happens if there is a merge between
# a matched and unmatched run. Then some genes remain unprocessed
# while the merged run is re-matched. In this process, new genes
# can be deleted. If one of the genes happens to be in mod_g1, it
# should be deleted.
for g in del_g1.intersection(mod_g1):
mod_g1.remove(g)
g1pos = dict(izip(g1, xrange(len(g1))))
# add new modification points
mod_g1.update(new_mod_g1)
del_g2, mod_g2 = removeSingleGenes(g2, g2_runs)
if del_g2:
logging.info('Zombie genes removed from G2: %s' %', '.join(map(str, del_g2)))
for g2j in mod_g2:
for g1i, (d, _) in g2dists[g2j].items():
if g1i in g1:
if d == DIRECTION_CRICK_STRAND:
mod_g1.add(g1i)
# what, if d == DIRECTION_BOTH_STRANDS? Then, both neighbors have to be added...
if d == DIRECTION_WATSON_STRAND:
mod_g1.add(g1[g1pos[g1i]-1])
# merge runs
mx, mod_g1 = mergeRuns(mod_g1, g1, g2, g1_runs, g2_runs,
runList, res)
if res:
logging.info('Matching finished. Longest run size is %s.' %(max(map(len,
res))))
else:
logging.info('Matching finished, but no runs found. Empty input?')
return (g1, g2, g1_runs, g2_runs, res)
def repeatMatching(g1, g2, g1_mod, g2_mod, g1_runs, g2_runs, dists, repMatching,
minCsSize, topXperCent):
g1_mod_res = g1_mod
g2_mod_res = g2_mod
g1_runs_res = g1_runs
g2_runs_res = g2_runs
selectedRuns_res = list()
g1pos = dict(izip(g1_mod, xrange(len(g1_mod))))
g2pos = dict(izip(g2_mod, xrange(len(g2_mod))))
noReps = repMatching
while repMatching:
for i in xrange(len(g1_runs)):
run_set = g1_runs[i]
if len(run_set) != 1:
logging.error(('Expected run, set length of 1, but was told' + \
' different: %s.') %(', '.join(map(str, run_set))))
run = run_set.__iter__().next()
g1i = g1_mod[i]
j = i-g1pos[run.startG1]
if run.direction == DIRECTION_CRICK_STRAND:
g2j = g2_mod[g2pos[run.startG2] + j]
else:
g2j = g2_mod[g2pos[run.endG2] - j]
del dists[g1i][g2j]
if not dists[g1i]:
del dists[g1i]
if not dists:
logging.info(('Removed all edges in the input graph. Stopping ' + \
'iteration %s.') % (noReps-repMatching+2))
break
g1_mod, g2_mod, g1_runs, g2_runs, selectedRuns = findRandomRunSequence(g1, g2, dists, topXperCent)
checkMatching(g1_mod, g2_mod, g1_runs, g2_runs, selectedRuns, dists)
logging.info(('Obtained %s adjacencies in matching of size %s from ' + \
'iteration %s.') %(len(g1_mod) - len(selectedRuns),
len(g1_mod), noReps-repMatching+2))
# remove runs that fall below min length of minCsSize
ff = lambda x: len(x.__iter__().next()) >= minCsSize
g1_mod = [g1_mod[i] for i in xrange(len(g1_mod)) if ff(g1_runs[i])]
g2_mod = [g2_mod[i] for i in xrange(len(g2_mod)) if ff(g2_runs[i])]
g1_runs = filter(ff, g1_runs)
g2_runs = filter(ff, g2_runs)
selectedRuns = set([s for s in selectedRuns if len(s) >= minCsSize])
# stop if no runs were found matching the criteria
if not len(selectedRuns):
logging.info(('No feasible runs found in matching round %s. Stopping ' + \
'iteration.') % (noReps-repMatching+2))
break
logging.info('%s feasible runs retained.' %len(selectedRuns))
# reconciliate with result data
g2pos = dict(izip(g2_mod, xrange(len(g2_mod))))
g1pos = dict(izip(g1_mod, xrange(len(g1_mod))))
g2pos_res = dict(izip(g2_mod_res, xrange(len(g2_mod_res))))
g1pos_res = dict(izip(g1_mod_res, xrange(len(g1_mod_res))))
chr_srt = lambda x, y: x[0] == y[0] and (x[1] < y[1] and -1 or 1) or (x[0] < y[0] and -1 or 1)
g1_mod_new = sorted(set(g1_mod_res + g1_mod), cmp=chr_srt)
g2_mod_new = sorted(set(g2_mod_res + g2_mod), cmp=chr_srt)
g1_runs_new = list()
g2_runs_new = list()
for g1i in g1_mod_new:
x = set()
if g1pos_res.has_key(g1i):
x.update(g1_runs_res[g1pos_res[g1i]])
if g1pos.has_key(g1i):
x.update(g1_runs[g1pos[g1i]])
g1_runs_new.append(x)
for g2j in g2_mod_new:
x = set()
if g2pos_res.has_key(g2j):
x.update(g2_runs_res[g2pos_res[g2j]])
if g2pos.has_key(g2j):
x.update(g2_runs[g2pos[g2j]])
g2_runs_new.append(x)
g1_mod_res = g1_mod_new
g2_mod_res = g2_mod_new
g1_runs_res = g1_runs_new
g2_runs_res = g2_runs_new
selectedRuns_res.extend(selectedRuns)
repMatching -= 1
return (g1_mod_res, g2_mod_res, g1_runs_res, g2_runs_res, selectedRuns_res)
def printMatching(g1, g2, g1_runs, hasMultipleChromosomes, out):
if hasMultipleChromosomes:
print >> f, 'Chr(G1)\tG1\tChr(G2)\tG2\tdirection\tedge weight'
else:
print >> f, 'G1\tG2\tdirection\tedge weight'
g2pos = dict(izip(g2, xrange(len(g2))))
g1pos = dict(izip(g1, xrange(len(g1))))
cur_index = dict()
for i in xrange(len(g1_runs)):
run_set = g1_runs[i]
for run in run_set:
g1i = g1[i]
j = 0
if cur_index.has_key(run):
j = cur_index[run]
if run.direction == DIRECTION_CRICK_STRAND:
g2j = g2[g2pos[run.startG2] + j]
else:
g2j = g2[g2pos[run.endG2] - j]
direction = run.direction == DIRECTION_CRICK_STRAND and '1' or '-1'
g1i1 = g1i[1] == -1 and 'TELOMERE_START' or g1i[1]
g1i1 = g1i[1] == maxint and 'TELOMERE_END' or g1i1
g2j1 = g2j[1] == -1 and 'TELOMERE_START' or g2j[1]
g2j1 = g2j[1] == maxint and 'TELOMERE_END' or g2j1
if hasMultipleChromosomes:
print >> f, '%s\t%s\t%s\t%s\t%s\t%s' %(g1i[0], g1i1, g2j[0],
g2j1, direction, run.weight[j])
else:
print >> f, '%s\t%s\t%s\t%s' %(g1i1, g2j1, direction,
run.weight[j])
cur_index[run] = j+1
if __name__ == '__main__':
if len(argv) < 3 or len(argv) > 8:
print '\tusage: %s <DIST FILE> <ALPHA> [ <EDGE WEIGHT THRESHOLD> --repeat-matching (-R) <NUMBER >= 2> --min-cs-size (-M) <NUMBER >= 1> ]' %argv[0]
exit(1)
repMatching= '--repeat-matching' in argv or '-R' in argv
minCsSize = '--min-cs-size' in argv or '-M' in argv
if minCsSize:
pos = '-M' in argv and argv.index('-M') or argv.index('--min-cs-size')
minCsSize = int(argv[pos+1])
argv = argv[:pos] + argv[pos+2:]
if not repMatching:
print >> stderr, ('Argument --min-cs-size (-M) only valid in ' + \
'combination with --repeat-matching (-R)')
exit(1)
else:
minCsSize = 1
if repMatching:
pos = '-R' in argv and argv.index('-R') or argv.index('--repeat-matching')
repMatching = int(argv[pos+1]) - 1
argv = argv[:pos] + argv[pos+2:]
else:
repMatching = 0
# set as global parameter
alpha = float(argv[2])
edgeThreshold = len(argv) == 4 and float(argv[3]) or 0
# logFileName = '%s.log' %(basename(argv[1]).rsplit('.')[0])
logFileName = '%s.log' %(argv[1].rsplit('.')[0]) # Respect given path
logging.basicConfig(filename=logFileName,filemode='w', level=logging.INFO,
format= "%(levelname)s\t%(asctime)s\t++ %(message)s")
greedy = 10.**-7
hasMultipleChromosomes, g1, g2, dists = readDistsAndOrder(open(argv[1]), edgeThreshold)
g1_mod, g2_mod, g1_runs, g2_runs, selectedRuns = findRandomRunSequence(g1,
g2, dists, greedy)
checkMatching(g1_mod, g2_mod, g1_runs, g2_runs, selectedRuns, dists)
# calculate number of breakpoints only from result of the first matching
bkp = len(selectedRuns) -1
g1_mod, g2_mod, g1_runs, g2_runs, selectedRuns_new = repeatMatching(g1, g2,
g1_mod, g2_mod, g1_runs, g2_runs, dists, repMatching, minCsSize, greedy)
selectedRuns.update(selectedRuns_new)
#
# calculate additional values
#
# sum of weights of adjacencies
wAdj = sum([r.getWeight(1) for r in selectedRuns])
# sum of weights of all edges of the matching
wEdg = sum([sum(map(lambda x: x**2, r.weight)) for r in selectedRuns])
edg = sum(map(len, selectedRuns))
#
# print matching
#
# out_file = basename(argv[1])
out_file = argv[1] # respect given path
f = open('%s.matching' %out_file[:out_file.rfind('.')], 'w')
printMatching(g1_mod, g2_mod, g1_runs, hasMultipleChromosomes, f)
f.flush()
f.close()
#
# print matching scores
#
logging.info(('FFAdj-MCS finished. Breakpoint distance between G1 and G2' + \
' is %s with #edg = %s, adj(M) = %.3f and edg(M) = %.3f') %(bkp, edg,
wAdj, wEdg))
print '#bkp\t#edg\tadj\tedg'
print '%s\t%s\t%.6f\t%.6f' %(bkp, edg, wAdj, wEdg)
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