def run(self):
self.getAlignmentDict()
self.getTranscriptDict()
self.getAnnotationDict()
detailsDict = {}
classifyDict = {}
for aId, t in self.transcriptDict.iteritems():
a = self.annotationDict[psl_lib.remove_alignment_number(aId)]
if a.getCdsLength() <= 75 or t.getCdsLength() <= 75:
continue
if t.getCdsLength() % 3 != 0 and a.getCdsLength() % 3 != 0:
detailsDict[aId] = seq_lib.chromosome_coordinate_to_bed(t, t.thickStart, t.thickStop, self.colors["input"],
self.column)
classifyDict[aId] = 1
elif t.getCdsLength() % 3 != 0:
detailsDict[aId] = seq_lib.chromosome_coordinate_to_bed(t, t.thickStart, t.thickStop, self.rgb,
self.column)
classifyDict[aId] = 1
else:
classifyDict[aId] = 0
self.dumpValueDicts(classifyDict, detailsDict)
def run(self):
self.getAlignmentDict()
self.getTranscriptDict()
self.getAnnotationDict()
detailsDict = defaultdict(list)
classifyDict = {}
for aId, aln in self.alignmentDict.iteritems():
if aId not in self.transcriptDict:
continue
t = self.transcriptDict[aId]
a = self.annotationDict[psl_lib.remove_alignment_number(aId)]
# do not include noncoding transcripts or lift-overs that contain less than 1 codon
if a.getCdsLength() <= 75 or t.getCdsLength() <= 75:
continue
frame_shifts = list(frameShiftIterator(a, t, aln))
if len(frame_shifts) == 0:
classifyDict[aId] = 0
continue
indel_starts, indel_stops, spans = zip(*frame_shifts)
# calculate cumulative frame by adding each span and taking mod 3 - zeroes imply regaining frame
# note that this code prepends a 0 to the list, offsetting all values by 1. This is useful.
cumulative_frame = map(lambda x: x % 3, reduce(lambda l, v: (l.append(l[-1] + v) or l), spans, [0]))
# every start is when a zero existed in the previous spot in cumulative_frame
windowed_starts = [x for x, y in izip(indel_starts, cumulative_frame) if y == 0 or x == indel_starts[0]]
# every stop is when a zero exists at this cumulative_frame
windowed_stops = [x for x, y in izip(indel_stops, cumulative_frame[1:]) if y == 0]
# sanity check
assert any([len(windowed_starts) == len(windowed_stops), len(windowed_starts) - 1 == len(windowed_stops)]),\
(self.genome, self.column, aId)
# now we need to fix frame and stops - if this shift extends to the end of the transcript, add that stop
# additionally, if this is a negative strand transcript, flip starts/stops so that start is always < stop
if len(windowed_stops) < len(windowed_starts) and t.strand is False:
windowed_stops.append(t.thickStart)
windowed_stops, windowed_starts = windowed_starts, windowed_stops
elif len(windowed_stops) < len(windowed_starts):
windowed_stops.append(t.thickStop)
elif t.strand is False:
windowed_stops, windowed_starts = windowed_starts, windowed_stops
for start, stop in izip(windowed_starts, windowed_stops):
detailsDict[aId].append(seq_lib.chromosome_coordinate_to_bed(t, start, stop, self.rgb, self.column))
classifyDict[aId] = 1
self.dumpValueDicts(classifyDict, detailsDict)