def run(self, shortIntronSize=30):
self.getTranscriptDict()
self.getSeqDict()
self.getAlignmentDict()
self.getAnnotationDict()
self.getRefDict()
detailsDict = defaultdict(list)
classifyDict = {}
for aId, t in self.transcriptDict.iteritems():
a = self.annotationDict[psl_lib.remove_alignment_number(aId)]
aln = self.alignmentDict[aId]
for intron in t.intronIntervals:
if len(intron) <= shortIntronSize:
continue
elif intron.start >= t.thickStart and intron.stop < t.thickStop:
continue
seq = intron.get_sequence(self.seqDict, strand=True)
donor, acceptor = seq[:2], seq[-2:]
if donor not in self.non_canonical or self.non_canonical[donor] != acceptor:
classifyDict[aId] = 1
# is this a intron that exists in the reference that also has this problem?
if compareIntronToReference(intron, a, aln, self.non_canonical, self.refDict) is True:
detailsDict[aId].append(seq_lib.splice_intron_interval_to_bed(t, intron, self.colors["input"],
self.column))
else:
detailsDict[aId].append(seq_lib.splice_intron_interval_to_bed(t, intron, self.rgb, self.column))
if aId not in classifyDict:
classifyDict[aId] = 0
self.dumpValueDicts(classifyDict, detailsDict)
def run(self, shortIntronSize=30):
self.getAnnotationDict()
self.getTranscriptDict()
self.getAlignmentDict()
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)]
original_introns = {(x.start, x.stop) for x in a.intronIntervals}
target_introns = set()
target_intron_mapping = {}
for intron in t.intronIntervals:
a_start = a.transcript_coordinate_to_chromosome(aln.target_coordinate_to_query(intron.start - 1)) + 1
a_stop = a.transcript_coordinate_to_chromosome(aln.target_coordinate_to_query(intron.stop))
target_introns.add((a_start, a_stop))
target_intron_mapping[(a_start, a_stop)] = intron
missing_introns = original_introns - target_introns
if len(missing_introns) != 0:
classifyDict[aId] = 1
not_original_introns = target_introns - original_introns
for a_start, a_stop in not_original_introns:
intron = target_intron_mapping[(a_start, a_stop)]
if len(intron) >= shortIntronSize:
detailsDict[aId].append(seq_lib.splice_intron_interval_to_bed(t, intron, self.rgb, self.column))
else:
classifyDict[aId] = 0
self.dumpValueDicts(classifyDict, detailsDict)
