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transcript.py
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transcript.py
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import numpy as np
import Sequencing.utilities as utilities
import Sequencing.genomes as genomes
from collections import defaultdict
import positions
import Bio.Seq
class Transcript(object):
def __init__(self,
name,
features,
overlap_finder,
region_fetcher,
codon_table=1,
):
self.name = name
self.region_fetcher = region_fetcher
self.codon_table = codon_table
# Further processing assumes that features is sorted by (start, end).
features = sorted(features)
strands = {feature.strand for feature in features}
if len(strands) > 1:
raise ValueError(self.name)
self.strand = strands.pop()
seqnames = {feature.seqname for feature in features}
if len(seqnames) > 1:
raise ValueError(self.name)
self.seqname = seqnames.pop()
self.exons = [feature for feature in features if feature.feature == 'exon']
# A transcript can have more than one start_codon or stop_codon feature
# if the codon is split across multiple exons.
self.start_codons = [feature for feature in features if feature.feature == 'start_codon']
self.stop_codons = [feature for feature in features if feature.feature == 'stop_codon']
self.CDSs = [None for exon in self.exons]
CDSs = [feature for feature in features if feature.feature == 'CDS']
for CDS in CDSs:
for e, exon in enumerate(self.exons):
if CDS.is_contained_in(exon):
self.CDSs[e] = CDS
break
else:
raise ValueError(CDS, self.exons)
if self.start_codons:
if self.strand == '+':
self.first_start_codon_position = min(sc.start for sc in self.start_codons)
elif self.strand == '-':
self.first_start_codon_position = max(sc.end for sc in self.start_codons)
else:
self.first_start_codon_position = None
if self.stop_codons:
if self.strand == '+':
self.first_stop_codon_position = min(sc.start for sc in self.stop_codons)
elif self.strand == '-':
self.first_stop_codon_position = max(sc.end for sc in self.stop_codons)
else:
self.first_stop_codon_position = None
self.start = min(exon.start for exon in self.exons)
self.end = max(exon.end for exon in self.exons)
@property
def comparison_key(self):
return self.seqname, self.start, self.end, self.strand
def __lt__(self, other):
return self.comparison_key < other.comparison_key
def build_coordinate_maps(self, left_buffer=0, right_buffer=0):
''' Make dictionaries mapping from genomic coordinates to transcript
coordinates and vice-versa.
'''
self.num_overlapping = int(self.top_level_feature.attribute.get('overlapping', 0))
closest_left = int(self.top_level_feature.attribute.get('closest_left', 0))
closest_right = int(self.top_level_feature.attribute.get('closest_right', 1e10))
if self.strand == '+':
self.upstream = closest_left
self.downstream = closest_right
elif self.strand == '-':
self.upstream = closest_right
self.downstream = closest_left
if self.strand == '+':
exon_position_lists = [np.arange(exon.start, exon.end + 1) for exon in self.exons]
elif self.strand == '-':
exon_position_lists = [np.arange(exon.end, exon.start - 1, -1) for exon in self.exons[::-1]]
exon_positions = np.concatenate(exon_position_lists)
self.transcript_length = len(exon_positions)
# Add some upstream and downstream bases.
upstream_transcript = np.arange(-left_buffer, 0)
downstream_transcript = np.arange(self.transcript_length, self.transcript_length + right_buffer)
if self.strand == '+':
upstream_positions = np.arange(self.start - left_buffer, self.start)
downstream_positions = np.arange(self.end + 1, self.end + 1 + right_buffer)
elif self.strand == '-':
upstream_positions = np.arange(self.end + left_buffer, self.end, -1)
downstream_positions = np.arange(self.start - 1, self.start - 1 - right_buffer, -1)
self.transcript_to_genomic = dict(enumerate(exon_positions))
self.transcript_to_genomic.update(zip(upstream_transcript, upstream_positions))
self.transcript_to_genomic.update(zip(downstream_transcript, downstream_positions))
self.genomic_to_transcript = {g: t for t, g in self.transcript_to_genomic.iteritems()}
if self.upstream in self.genomic_to_transcript:
self.transcript_upstream = self.genomic_to_transcript[self.upstream]
else:
self.transcript_upstream = min(self.transcript_to_genomic) - 1
if self.downstream in self.genomic_to_transcript:
self.transcript_downstream = self.genomic_to_transcript[self.downstream]
else:
self.transcript_downstream = max(self.transcript_to_genomic) + 1
if self.first_stop_codon_position != None:
if self.first_start_codon_position != None:
genomic_start_codon = self.first_start_codon_position
else:
# E. coli genes that aren't initiated with AUG don't have a start
# codon listed in the gtf file.
if self.strand == '+':
genomic_start_codon = self.start
elif self.strand == '-':
genomic_start_codon = self.end
self.transcript_start_codon = self.genomic_to_transcript[genomic_start_codon]
self.transcript_stop_codon = self.genomic_to_transcript[self.first_stop_codon_position]
# By convention, CDS_length includes no bases of the stop codon.
self.CDS_length = self.transcript_stop_codon - self.transcript_start_codon
def build_extent_maps(self, left_buffer=0, right_buffer=0):
''' Make dictionaries mapping from genomic coordinates to transcript
coordinates and vice-versa.
'''
start = self.first_start_codon_position
stop = self.first_stop_codon_position
if self.strand == '+':
extent_positions = np.arange(start, stop)
elif self.strand == '-':
extent_positions = np.arange(start, stop, -1)
self.extent_length = abs(stop - start)
# Add some upstream and downstream bases.
upstream_extent = np.arange(-left_buffer, 0)
downstream_extent = np.arange(self.extent_length, self.extent_length + right_buffer)
if self.strand == '+':
upstream_positions = np.arange(start - left_buffer, start)
downstream_positions = np.arange(stop, stop + right_buffer)
elif self.strand == '-':
upstream_positions = np.arange(start + left_buffer, start, -1)
downstream_positions = np.arange(stop, stop - right_buffer, -1)
self.extent_to_genomic = dict(enumerate(extent_positions))
self.extent_to_genomic.update(zip(upstream_extent, upstream_positions))
self.extent_to_genomic.update(zip(downstream_extent, downstream_positions))
self.genomic_to_extent = {g: e for e, g in self.extent_to_genomic.iteritems()}
def get_extent_sequence(self, left_buffer=0, right_buffer=0):
''' Get the sequence of the extent. Useful for looking at gene with
annotated frameshifts.
'''
sequence = self.region_fetcher(self.seqname,
min(self.genomic_to_extent),
max(self.genomic_to_extent) + 1,
)
if self.strand == '-':
sequence = utilities.reverse_complement(sequence)
sequence = np.asarray(sequence, dtype='c')
extent_landmarks = {'start': 0,
'end': self.extent_length,
}
return positions.PositionCounts(extent_landmarks,
left_buffer,
right_buffer,
data=sequence,
)
def get_transcript_sequence(self, left_buffer=0, right_buffer=0):
''' Get the sequence of the mature transcript.
'''
# Remake coordinate maps to guarantee buffer sizes
self.build_coordinate_maps(left_buffer, right_buffer)
transcript_positions = range(-left_buffer,
self.transcript_length + right_buffer,
)
genomic_positions = [self.transcript_to_genomic[t] for t in transcript_positions]
bases = [self.region_fetcher(self.seqname, p, p + 1) for p in genomic_positions]
sequence = ''.join(bases).upper()
if self.strand == '-':
sequence = utilities.complement(sequence)
sequence = np.asarray(sequence, dtype='c')
landmarks = {'start': 0,
'start_codon': self.transcript_start_codon,
'stop_codon': self.transcript_stop_codon,
'end': self.transcript_length,
}
transcript_sequence = positions.PositionCounts(landmarks,
left_buffer,
right_buffer,
data=sequence,
)
return transcript_sequence
def get_coding_sequence(self, translate=True):
transcript_sequence = self.get_transcript_sequence()
coding_sequence = transcript_sequence['start_codon':('stop_codon', 3)]
coding_sequence = ''.join(coding_sequence)
if translate:
# Ensure that the coding sequence is well-formed.
try:
Bio.Seq.translate(coding_sequence, cds=True, table=self.codon_table)
except Bio.Seq.CodonTable.TranslationError:
coding_sequence = None
return coding_sequence
def is_spliced_out(self, position):
''' Returns True if the genomic position is between the start and end of
this transcript but not part of it.
'''
is_within = self.start < position < self.end
not_part_of = position not in self.genomic_to_transcript
return is_within and not_part_of
def delete_coordinate_maps(self):
del self.transcript_to_genomic
del self.genomic_to_transcript
def __str__(self):
return '{0} {1}:{2}-{3} {4}'.format(self.name, self.seqname, self.start, self.end, self.strand)
def get_transcripts(all_features, genome_dir):
region_fetcher = genomes.build_region_fetcher(genome_dir, load_references=True)
feature_lists = defaultdict(list)
for feature in all_features:
transcript_name = feature.attribute['transcript_id']
feature_lists[transcript_name].append(feature)
transcripts = [Transcript(name, features, None, region_fetcher)
for name, features in feature_lists.iteritems()]
return transcripts
class GFFTranscript(Transcript):
def __init__(self,
feature,
region_fetcher,
codon_table=1,
):
self.name = feature.attribute['ID']
self.strand = feature.strand
self.seqname = feature.seqname
self.top_level_feature = feature
self.region_fetcher = region_fetcher
self.codon_table = codon_table
self.mRNAs = sorted(c for c in feature.descendants if c.feature == 'mRNA')
self.exons = sorted(c for c in feature.descendants if 'exon' in c.feature)
self.CDSs = sorted(c for c in feature.descendants if c.feature == 'CDS')
if self.CDSs:
if self.strand == '+':
self.first_start_codon_position = min(cds.start for cds in self.CDSs)
self.first_stop_codon_position = max(cds.end for cds in self.CDSs) - 2
elif self.strand == '-':
self.first_start_codon_position = max(cds.end for cds in self.CDSs)
self.first_stop_codon_position = min(cds.start for cds in self.CDSs) + 2
else:
self.first_start_codon_position = None
self.first_stop_codon_position = None
self.start = feature.start
self.end = feature.end
def get_gff_transcripts(all_features, genome_dir):
region_fetcher = genomes.build_region_fetcher(genome_dir, load_references=True)
genes = []
for feature in all_features:
top_level = feature.parent == None
dubious = feature.attribute.get('orf_classification') == 'Dubious'
has_exon = any('exon' in c.feature for c in feature.descendants)
if top_level and has_exon and not dubious:
gene = GFFTranscript(feature, region_fetcher)
genes.append(gene)
return genes