def evaluatePI(dir, contigs_file, initial_file, ref_file):
basic.ensure_dir_existance(dir)
CreateLog(dir)
dd = DirDistributor(os.path.join(dir, "alignments"))
aligner = Aligner(dd)
contigs = ContigStorage().loadFromFasta(open(contigs_file, "r"), False)
initial = ContigStorage().loadFromFasta(open(initial_file, "r"), False)
ref = ContigStorage().loadFromFasta(open(ref_file, "r"), False)
segs = []
for al in aligner.overlapAlign(initial.unique(), contigs):
if basic.isCanonocal(al.seg_to.contig.id):
segs.append(al.seg_to)
else:
segs.append(al.rc.seg_to)
segs = sorted(segs, key=lambda seg: basic.Normalize(seg.contig.id))
interesting = dict()
print "Interesting segments:"
for contig in contigs:
interesting[contig.id] = [contig.asSegment()]
for contig, segit in itertools.groupby(segs, lambda seg: seg.contig):
csegs = SegmentStorage().addAll(segit)
csegs.mergeSegments()
csegs = csegs.reverse(contig)
interesting[contig.id] = list(csegs)
print list(csegs)
print "Analysis of contigs"
scorer = Scorer()
for al in aligner.localAlign(contigs.unique(), ref):
print al
for seg in interesting[al.seg_from.contig.id]:
if al.seg_from.expand(500).contains(
seg) or al.seg_from.interSize(seg) > 40000:
tmp_al = al.reduce(query=al.seg_from.cap(seg))
scorer.polyshMatching(tmp_al.matchingSequence(),
params.score_counting_radius)
print tmp_al.seg_from, tmp_al.seg_to, str(events)
print ""
print "Analysis of initial"
for al in aligner.overlapAlign(initial, ref):
scorer.polyshMatching(al.matchingSequence(),
params.score_counting_radius)
print al.seg_from, al.seg_to, str(events)
class Correction:
def __init__(self, seq_from, seq_to, alignments):
# type: (Contig, Contig, List[AlignmentPiece]) -> None
self.seq_from = seq_from
self.seq_to = seq_to
self.alignments = alignments
self.scorer = Scorer()
def changeQT(self, contig_from, contig_to):
self.alignments = [
al.changeTargetContig(contig_to).changeQueryContig(contig_from)
for al in self.alignments
]
def isSubstantial(self):
# type: () -> bool
for al in self.alignments:
if len(list(al.splitRef())) > 1 or (
len(al) > 150 and al.percentIdentity() < 0.98
) or (len(al.seg_from) - len(al.seg_to)) > 50:
return True
return False
def mapSegmentsUp(self, segments):
# type: (List[Segment]) -> List[Segment]
left = self.mapPositionsUp([seg.left for seg in segments])
right = self.mapPositionsUp([seg.right - 1 for seg in segments])
return [Segment(self.seq_from, l, r + 1) for l, r in zip(left, right)]
def mapSegmentsDown(self, segments):
# type: (Iterable[Segment]) -> List[Segment]
segments = list(segments)
left = self.mapPositionsDown([seg.left for seg in segments])
right = self.mapPositionsDown([seg.right - 1 for seg in segments])
return [Segment(self.seq_to, l, r + 1) for l, r in zip(left, right)]
def mapPositionsUp(self, positions, none_on_miss=False):
# type: (List[int], bool) -> List[Optional[int]]
tmp = [(pos, i) for i, pos in enumerate(positions)]
tmp = sorted(tmp)
res = [0] * len(positions)
cur_pos = 0
for al in self.alignments:
while cur_pos < len(tmp) and tmp[cur_pos][0] <= al.seg_to.left:
res[tmp[cur_pos][1]] = al.seg_from.left - (al.seg_to.left -
tmp[cur_pos][0])
cur_pos += 1
for p1, p2 in al.matchingPositions(equalOnly=True):
while cur_pos < len(positions) and tmp[cur_pos][0] <= p2:
if tmp[cur_pos][0] == p2 or not none_on_miss:
res[tmp[cur_pos][1]] = p1
else:
res[tmp[cur_pos][1]] = None
cur_pos += 1
while cur_pos < len(positions):
res[tmp[cur_pos][1]] = len(
self.seq_from) - (len(self.seq_to) - tmp[cur_pos][0])
cur_pos += 1
return res
def mapPositionsDown(self, positions, none_one_miss=False):
# type: (List[int], bool) -> List[Optional[int]]
tmp = [(pos, i) for i, pos in enumerate(positions)]
tmp = sorted(tmp)
res = [0] * len(positions)
cur_pos = 0
for al in self.alignments:
while cur_pos < len(tmp) and tmp[cur_pos][0] <= al.seg_from.left:
res[tmp[cur_pos][1]] = al.seg_to.left - (al.seg_from.left -
tmp[cur_pos][0])
cur_pos += 1
for p1, p2 in al.matchingPositions(equalOnly=False):
while cur_pos < len(positions) and tmp[cur_pos][0] <= p1:
if tmp[cur_pos][0] == p1 or not none_one_miss:
res[tmp[cur_pos][1]] = p2
else:
res[tmp[cur_pos][1]] = None
cur_pos += 1
while cur_pos < len(positions):
res[tmp[cur_pos][1]] = len(
self.seq_to) - (len(self.seq_from) - tmp[cur_pos][0])
cur_pos += 1
return res
def continuousMapping(self, map_function, iter):
# type: (Callable[[List[int]], List[int]], Iterator[int]) -> Generator[int]
chunk = []
for item in iter:
chunk.append(item)
if len(chunk) > 100000:
for res in map_function(chunk):
yield res
chunk = []
for res in map_function(chunk):
yield res
# This method may change the order of alignments. But they will be sorted by start.
def composeQueryDifferences(self, als):
# type: (List[AlignmentPiece]) -> List[AlignmentPiece]
order = sorted(range(len(als)), key=lambda i: als[i].seg_to.left)
# Sorting alignments into those that intersect corrections (complex) and those that do not (easy)
easy = [] # type: List[int]
complex = [] # type: List[int]
cur = 0
for al in self.alignments:
while cur < len(als) and als[
order[cur]].seg_to.left < al.seg_to.left:
if als[order[cur]].seg_to.right >= al.seg_to.left:
complex.append(order[cur])
else:
easy.append(order[cur])
cur += 1
while cur < len(als) and als[
order[cur]].seg_to.left < al.seg_to.right:
complex.append(order[cur])
cur += 1
while cur < len(als):
easy.append(order[cur])
cur += 1
res = [None] * len(als) # type: List[AlignmentPiece]
# Mapping alignments that do not intersect corrections
new_easy_segs = self.mapSegmentsUp([als[i].seg_to for i in easy])
for seg, i in zip(new_easy_segs, easy):
res[i] = als[i].changeTargetSegment(seg)
# Mapping alignments that intersect corrections
func = lambda items: self.mapPositionsUp(items, True)
matchings = [als[i].matchingSequence(True) for i in complex]
positions = map(lambda matching: map(lambda pair: pair[1], matching),
matchings)
generator = self.continuousMapping(
func, itertools.chain.from_iterable(positions))
for i, matching in zip(complex, matchings):
al = als[i]
new_pairs = []
for pos_from, pos_to in matching.matches:
new_pos = generator.next()
if new_pos is not None:
new_pairs.append((pos_from, new_pos))
new_matching = MatchingSequence(matching.seq_from,
self.seq_from.seq, new_pairs)
corrected_matching = self.scorer.polyshMatching(
new_matching, params.alignment_correction_radius)
res[i] = corrected_matching.asAlignmentPiece(
al.seg_from.contig, self.seq_from)
return res
@staticmethod
def constructCorrection(alignments):
# type: (List[AlignmentPiece]) -> Correction
initial = alignments[0].seg_to.contig
alignments = sorted(alignments, key=lambda al: al.seg_to.left)
sb = []
pos = initial.left()
new_pos = 0
for al in alignments:
sb.append(initial.subSequence(pos, al.seg_to.left).seq)
new_pos += al.seg_to.left - pos
pos = al.seg_to.left
sb.append(al.seg_from.Seq())
new_pos += al.seg_from.__len__()
pos = al.seg_to.right
sb.append(
initial.segment(alignments[-1].seg_to.right,
initial.right()).Seq())
new_pos += initial.right() - alignments[-1].seg_to.right
new_seq = Contig("".join(sb), "TMP1_" + initial.id)
new_als = []
pos = initial.left()
new_pos = 0
for al in alignments:
new_pos += al.seg_to.left - pos
new_seg_from = Segment(new_seq, new_pos,
new_pos + al.seg_from.__len__())
new_als.append(al.changeQuerySegment(new_seg_from))
pos = al.seg_to.right
new_pos += al.seg_from.__len__()
return Correction(new_seq, initial, new_als)