def test_monoexonic(self):
exon = self.gff_lines[1]
transcript_line = self.gff_lines[0]
transcript_line.end = exon.end
model = Transcript(transcript_line)
model.add_exon(exon)
model.finalize()
fasta = self.fasta[model.chrom][model.start - 1:model.end]
tcheck = TranscriptChecker(model.copy(), fasta, strand_specific=False)
tcheck.check_strand()
self.assertIsNone(tcheck.strand)
tcheck = TranscriptChecker(model.copy(), fasta, strand_specific=True)
tcheck.check_strand()
self.assertEqual(tcheck.strand, "+")
neg = model.copy()
neg.strand = "-"
tcheck = TranscriptChecker(neg.copy(), fasta, strand_specific=False)
tcheck.check_strand()
self.assertIsNone(tcheck.strand)
tcheck = TranscriptChecker(neg.copy(), fasta, strand_specific=True)
tcheck.check_strand()
self.assertEqual(tcheck.strand, "-")
def main():
parser = argparse.ArgumentParser(
"Script to convert from BAM to GTF, for PB alignments")
parser.add_argument(
"--strict",
action="store_true",
default=False,
help=
"Switch. If set, this script will never output multiexonic transcripts \
without a defined strand.")
parser.add_argument("--outfmt", choices=["gtf", "bed12"], default="gtf")
parser.add_argument("bam", type=to_bam, help="Input BAM file")
parser.add_argument("out",
nargs="?",
default=sys.stdout,
type=argparse.FileType("wt"),
help="Optional output file")
args = parser.parse_args()
# M 0 alignment match (can be a sequence match or mismatch)
# I 1 insertion to the reference
# D 2 deletion from the reference
# N 3 skipped region from the reference
# S 4 soft clipping (clipped sequences present in SEQ)
# H 5 hard clipping (clipped sequences NOT present in SEQ)
# P 6 padding (silent deletion from padded reference)
# = 7 sequence match
# X 8 sequence mismatch
name_counter = Counter()
for record in args.bam:
if record.is_unmapped is True:
continue
transcript = Transcript(record,
accept_undefined_multi=(not args.strict))
if name_counter.get(record.query_name):
name = "{}_{}".format(record.query_name,
name_counter.get(record.query_name))
else:
name = record.query_name
if name != transcript.id:
transcript.alias = transcript.id
transcript.id = name
transcript.parent = transcript.attributes[
"gene_id"] = "{0}.gene".format(name)
name_counter.update([record.query_name])
transcript.source = "bam2gtf"
print(transcript.format(args.outfmt), file=args.out)
def test_positive_strand(self):
gtf_lines = """chr1A Self_CESAR/windows_chr1A.gp transcript 265021906 265026255 . + . gene_id "TraesCS1A01G152900.1"; transcript_id "TraesCS1A01G152900.1";
chr1A Self_CESAR/windows_chr1A.gp exon 265021906 265021971 . + . gene_id "TraesCS1A01G152900.1"; transcript_id "TraesCS1A01G152900.1"; exon_number "1"; exon_id "TraesCS1A01G152900.1.1";
chr1A Self_CESAR/windows_chr1A.gp CDS 265021906 265021971 . + 0 gene_id "TraesCS1A01G152900.1"; transcript_id "TraesCS1A01G152900.1"; exon_number "1"; exon_id "TraesCS1A01G152900.1.1";
chr1A Self_CESAR/windows_chr1A.gp exon 265022056 265026255 . + . gene_id "TraesCS1A01G152900.1"; transcript_id "TraesCS1A01G152900.1"; exon_number "2"; exon_id "TraesCS1A01G152900.1.2";
chr1A Self_CESAR/windows_chr1A.gp CDS 265022056 265026252 . + 0 gene_id "TraesCS1A01G152900.1"; transcript_id "TraesCS1A01G152900.1"; exon_number "2"; exon_id "TraesCS1A01G152900.1.2";
chr1A Self_CESAR/windows_chr1A.gp start_codon 265021906 265021908 . + 0 gene_id "TraesCS1A01G152900.1"; transcript_id "TraesCS1A01G152900.1"; exon_number "1"; exon_id "TraesCS1A01G152900.1.1";
chr1A Self_CESAR/windows_chr1A.gp stop_codon 265026253 265026255 . + 0 gene_id "TraesCS1A01G152900.1"; transcript_id "TraesCS1A01G152900.1"; exon_number "2"; exon_id "TraesCS1A01G152900.1.2";"""
gtf_lines = [GtfLine(_) for _ in gtf_lines.split("\n")]
t = Transcript(gtf_lines[0])
t.add_exons(gtf_lines[1:])
t.finalize()
self.assertEqual(t.start, t.combined_cds_start)
self.assertEqual(t.end, t.combined_cds_end)
def test_negative(self):
gtf_lines = """Chr5 Cufflinks transcript 26575364 26578163 1000 - . gene_id "cufflinks_star_at.23553";transcript_id "cufflinks_star_at.23553.1";exon_number "1";FPKM "2.9700103727";conf_hi "3.260618";frac "0.732092";cov "81.895309";conf_lo "2.679403";
Chr5 Cufflinks exon 26575364 26575410 . - . gene_id "cufflinks_star_at.23553";transcript_id "cufflinks_star_at.23553.1";
Chr5 Cufflinks exon 26575495 26575620 . - . gene_id "cufflinks_star_at.23553";transcript_id "cufflinks_star_at.23553.1";
Chr5 Cufflinks exon 26575711 26575797 . - . gene_id "cufflinks_star_at.23553";transcript_id "cufflinks_star_at.23553.1";
Chr5 Cufflinks exon 26575885 26575944 . - . gene_id "cufflinks_star_at.23553";transcript_id "cufflinks_star_at.23553.1";
Chr5 Cufflinks exon 26576035 26576134 . - . gene_id "cufflinks_star_at.23553";transcript_id "cufflinks_star_at.23553.1";
Chr5 Cufflinks exon 26576261 26577069 . - . gene_id "cufflinks_star_at.23553";transcript_id "cufflinks_star_at.23553.1";
Chr5 Cufflinks exon 26577163 26577288 . - . gene_id "cufflinks_star_at.23553";transcript_id "cufflinks_star_at.23553.1";
Chr5 Cufflinks exon 26577378 26577449 . - . gene_id "cufflinks_star_at.23553";transcript_id "cufflinks_star_at.23553.1";
Chr5 Cufflinks exon 26577856 26578163 . - . gene_id "cufflinks_star_at.23553";transcript_id "cufflinks_star_at.23553.1";"""
gtf_lines = [GtfLine(line) for line in gtf_lines.split("\n")]
self.assertEqual(len([_ for _ in gtf_lines if _.header]), 0)
transcript = Transcript(gtf_lines[0])
transcript.add_exons(gtf_lines[1:])
transcript.finalize()
fasta_seq = self.fasta[transcript.chrom][transcript.start -
1:transcript.end]
tr_neg = transcript.copy()
tchecker = TranscriptChecker(tr_neg, fasta_seq, strand_specific=False)
self.assertEqual(tchecker.strand, "-")
self.assertEqual(tchecker.fasta_seq, fasta_seq)
tchecker.check_strand()
self.assertEqual(tchecker.strand, "-")
tr_neg = transcript.copy()
tr_neg.strand = "+"
for ss in (False, True):
with self.subTest(ss=ss):
tchecker = TranscriptChecker(tr_neg.copy(),
fasta_seq,
strand_specific=ss)
tchecker.check_strand()
if ss:
self.assertEqual(tchecker.strand, "+")
self.assertTrue(tchecker.suspicious_splicing)
else:
self.assertEqual(tchecker.strand, "-")
def setUp(self):
# Prepare the model
self.model_lines = """Chr5 tair10 transcript 26584797 26595528 100 + . ID=c58_g1_i3.mrna1.19;Parent=c58_g1_i3.path1.19;Name=c58_g1_i3.mrna1.19;gene_name=c58_g1_i3
Chr5 tair10 exon 26584797 26584879 . + . ID=c58_g1_i3.mrna1.19.exon1;Parent=c58_g1_i3.mrna1.19
Chr5 tair10 exon 26585220 26585273 . + . ID=c58_g1_i3.mrna1.19.exon2;Parent=c58_g1_i3.mrna1.19
Chr5 tair10 exon 26585345 26585889 . + . ID=c58_g1_i3.mrna1.19.exon3;Parent=c58_g1_i3.mrna1.19
Chr5 tair10 exon 26585982 26586294 . + . ID=c58_g1_i3.mrna1.19.exon4;Parent=c58_g1_i3.mrna1.19
Chr5 tair10 exon 26586420 26586524 . + . ID=c58_g1_i3.mrna1.19.exon5;Parent=c58_g1_i3.mrna1.19
Chr5 tair10 exon 26586638 26586850 . + . ID=c58_g1_i3.mrna1.19.exon6;Parent=c58_g1_i3.mrna1.19
Chr5 tair10 exon 26586934 26586996 . + . ID=c58_g1_i3.mrna1.19.exon7;Parent=c58_g1_i3.mrna1.19
Chr5 tair10 exon 26587084 26587202 . + . ID=c58_g1_i3.mrna1.19.exon8;Parent=c58_g1_i3.mrna1.19
Chr5 tair10 exon 26587287 26587345 . + . ID=c58_g1_i3.mrna1.19.exon9;Parent=c58_g1_i3.mrna1.19
Chr5 tair10 exon 26587427 26587472 . + . ID=c58_g1_i3.mrna1.19.exon10;Parent=c58_g1_i3.mrna1.19
Chr5 tair10 exon 26595411 26595528 . + . ID=c58_g1_i3.mrna1.19.exon11;Parent=c58_g1_i3.mrna1.19"""
self.gff_lines = []
for line in self.model_lines.split("\n"):
line = line.rstrip().lstrip()
line = GffLine(line)
self.gff_lines.append(line)
self.model = Transcript(self.gff_lines[0])
self.model.add_exons(self.gff_lines[1:])
self.model.finalize()
self.exons = [
self.fasta[line.chrom][line.start - 1:line.end]
for line in self.gff_lines[1:]
]
self.assertEqual(sum([len(exon) for exon in self.exons]), 1718,
self.exons)
# We need the whole genomic fragment
self.model_fasta = self.fasta["Chr5"][self.model.start -
1:self.model.end]
self.assertEqual(self.gff_lines[1].start, 26584797)
self.assertEqual(self.gff_lines[1].end, 26584879)
self.assertEqual(self.model.exons[0][0], self.gff_lines[1].start)
self.assertEqual(self.model.exons[0][1], self.gff_lines[1].end)
def test_monoexonic_suspicious(self):
"""A monoexonic transcript should never appear as a suspicious transcript, in terms of splicing."""
exon = self.gff_lines[1]
transcript_line = self.gff_lines[0]
transcript_line.end = exon.end
model = Transcript(transcript_line)
model.add_exon(exon)
model.finalize()
model.attributes["mixed_splices"] = "6positive,1negative"
self.assertFalse(model.suspicious_splicing)
del model.attributes["mixed_splices"]
self.assertFalse(model.suspicious_splicing)
model.attributes["canonical_number"] = 0
self.assertFalse(model.suspicious_splicing)
del model.attributes["canonical_number"]
model.attributes["canonical_on_reverse_strand"] = True
self.assertFalse(model.suspicious_splicing)
model.attributes["canonical_on_reverse_strand"] = False
self.assertFalse(model.suspicious_splicing)
model.attributes["mixed_splices"] = "6positive,1negative"
self.assertFalse(model.suspicious_splicing)
del model.attributes["mixed_splices"]
del model.attributes["canonical_on_reverse_strand"]
model.attributes["canonical_number"] = 0
self.assertFalse(model.suspicious_splicing)
self.assertFalse(model.only_non_canonical_splicing)
model.attributes["canonical_on_reverse_strand"] = True
self.assertFalse(model.suspicious_splicing)
self.assertFalse(model.only_non_canonical_splicing)
del model.attributes["canonical_on_reverse_strand"]
model.attributes["mixed_splices"] = "6positive,1negative"
self.assertFalse(model.suspicious_splicing)
self.assertFalse(model.only_non_canonical_splicing)
def launch(args):
"""
Simple launcher script.
:param args: the argparse Namespace
"""
if hasattr(args, "region") and args.region is not None:
try:
args.chrom, args.start, args.end = args.region
except ValueError as exc:
raise ValueError("{0} {1}".format(exc, args.region))
if args.start >= args.end:
raise ValueError("Start greater than end: {0}\t{1}".format(
args.start, args.end))
transcript = None
with GTF(args.gtf) as gtf:
for row in gtf:
if row.chrom != args.chrom:
continue
else:
if row.is_transcript is True:
if transcript is not None and \
transcript.start >= args.start and transcript.end <= args.end:
print(transcript.format("gtf"), file=args.out)
transcript = None
if args.assume_sorted is True and row.start > args.end:
break
transcript = Transcript(row)
else:
transcript.add_exon(row)
if transcript is not None and transcript.start >= args.start and transcript.end <= args.end:
print(transcript.format("gtf"), file=args.out)
def main():
parser = argparse.ArgumentParser(
"Script to convert from BAM to GTF, for PB alignments")
parser.add_argument("bam", type=to_bam, help="Input BAM file")
parser.add_argument("out",
nargs="?",
default=sys.stdout,
type=argparse.FileType("wt"),
help="Optional output file")
args = parser.parse_args()
# M 0 alignment match (can be a sequence match or mismatch)
# I 1 insertion to the reference
# D 2 deletion from the reference
# N 3 skipped region from the reference
# S 4 soft clipping (clipped sequences present in SEQ)
# H 5 hard clipping (clipped sequences NOT present in SEQ)
# P 6 padding (silent deletion from padded reference)
# = 7 sequence match
# X 8 sequence mismatch
for record in args.bam:
try:
start, end = record.reference_start, record.get_blocks()[-1][1]
except IndexError:
continue
current = start
exons = []
current_exon = None
r_length = record.inferred_length # Read length
# Upper because of STAR
edit_distance = [_[1] for _ in record.tags
if _[0].upper() == "NM"][0] # Excluding clipping
matches = 0
alen = 0
for cigar, length in record.cigartuples:
if cigar in (4, 5): # Insertion, clipping (soft or hard)
continue
elif cigar == 1:
alen += length
elif cigar == 3: # Intron
if current_exon is None:
continue # Read positioned at the end/beginning of scaffold
# assert current_exon is not None
exons.append(current_exon)
current_exon = None
current += length
elif cigar in (0, 2): # Match or deletion
if current_exon is None:
current_exon = (current + 1, current + length)
else:
current_exon = (current_exon[0], current_exon[1] + length)
current += length
if cigar == 0:
matches += length
alen += length
snps = sum(
len(_) for _ in re.split(
"[0-9]*", [_[1] for _ in record.tags if _[0] == "MD"][0])
if not _.startswith("^"))
identity = round(100 * (matches - snps) / r_length, 2)
coverage = round(100 * alen / r_length, 2)
exons.append(current_exon)
# This is clearly a mistake
if current != end:
msg = """{0}, {1}, {2}
Cigar tuples: {3}
Cigar string: {4}
Blocks: {5}
Exons: {6}
""".format(current, end, end - current, record.cigartuples,
record.cigarstring, record.get_blocks(), exons)
print(AssertionError(msg), file=sys.stderr)
# raise AssertionError(msg)
continue
transcript = Transcript()
transcript.id = record.query_name
transcript.exons = exons
transcript.parent = transcript.attributes[
"gene_id"] = "{0}.gene".format(record.query_name)
transcript.attributes["identity"] = identity
transcript.attributes["coverage"] = coverage
transcript.attributes["cigar"] = record.cigarstring
transcript.chrom = args.bam.getrname(record.rname)
if len(transcript.exons) == 0:
continue
assert len(transcript.exons) > 0
try:
transcript.start = min(x[0] for x in transcript.exons)
except IndexError:
raise IndexError(new_exons, transcript.exons)
transcript.end = max(x[1] for x in transcript.exons)
transcript.score = record.mapq
transcript.source = "bam2gtf"
transcript.id = record.query_name
transcript.parent = transcript.attributes[
"gene_id"] = "{0}.gene".format(record.query_name)
transcript.chrom = args.bam.getrname(record.rname)
assert len(transcript.exons) > 0
try:
transcript.start = min(x[0] for x in transcript.exons)
except IndexError:
raise IndexError(new_exons, transcript.exons)
transcript.end = max(x[1] for x in transcript.exons)
transcript.score = record.mapq
transcript.source = "bam2gtf"
transcript.attributes.update(
dict((tag, str(value)) for tag, value in record.get_tags()))
if "XS" in transcript.attributes:
transcript.strand = transcript.attributes["XS"]
else:
if record.is_reverse:
transcript.strand = "-"
else:
transcript.strand = "+"
print(transcript.__str__(to_gtf=True), file=args.out)
def parse_prediction(args, genes, positions, queue_logger):
"""
This function performs the real comparison between the reference and the prediction.
It needs the following inputs:
:param args: the Namespace with the necessary parameters
:param genes: Dictionary with the reference genes, of the form
dict[chrom][(start,end)] = [gene object]
:param positions: Dictionary with the positions of the reference genes, of the form
dict[chrom][IntervalTree]
:param queue_logger: Logger
:return:
"""
# start the class which will manage the statistics
accountant_instance = Accountant(genes, args)
assigner_instance = Assigner(genes, positions, args, accountant_instance)
transcript = None
if hasattr(args, "self") and args.self is True:
args.prediction = to_gff(args.reference.name)
ref_gff = isinstance(args.prediction, GFF3)
__found_with_orf = set()
for row in args.prediction:
if row.header is True:
continue
# queue_logger.debug("Row:\n{0:>20}".format(str(row)))
if row.is_transcript is True or row.feature == "match":
queue_logger.debug("Transcript row:\n%s", str(row))
if transcript is not None:
if re.search(r"\.orf[0-9]+$", transcript.id):
__name = re.sub(r"\.orf[0-9]+$", "", transcript.id)
if __name not in __found_with_orf:
__found_with_orf.add(__name)
assigner_instance.get_best(transcript)
else:
pass
else:
assigner_instance.get_best(transcript)
transcript = Transcript(row, logger=queue_logger)
elif row.is_exon is True:
# Case 1: we are talking about cDNA_match and GFF
if ref_gff is True and "match" not in row.feature:
if transcript is None:
raise TypeError(
"Transcript not defined inside the GFF; line:\n{}".
format(row))
else:
queue_logger.debug("Adding exon to transcript %s: %s",
transcript.id, row)
transcript.add_exon(row)
elif ref_gff is True and "match" in row.feature:
if transcript is not None and row.id == transcript.id:
transcript.add_exon(row)
elif transcript is not None and transcript.id in row.parent:
transcript.add_exon(row)
elif transcript is None or (transcript is not None
and row.id != transcript.id):
if transcript is not None:
if re.search(r"\.orf[0-9]+$", transcript.id) and \
(not transcript.id.endswith("orf1")):
pass
else:
assigner_instance.get_best(transcript)
queue_logger.debug("New transcript: %s", row.transcript)
transcript = Transcript(row, logger=queue_logger)
elif ref_gff is False:
if transcript is None or (transcript is not None
and transcript.id != row.transcript):
if transcript is not None:
if re.search(r"\.orf[0-9]+$", transcript.id) and \
(not transcript.id.endswith("orf1")):
pass
else:
assigner_instance.get_best(transcript)
queue_logger.debug("New transcript: %s", row.transcript)
transcript = Transcript(row, logger=queue_logger)
transcript.add_exon(row)
else:
raise TypeError("Unmatched exon: {}".format(row))
elif row.header:
continue
else:
queue_logger.debug("Skipped row: {}".format(row))
if transcript is not None:
if re.search(r"\.orf[0-9]+$",
transcript.id) and not transcript.id.endswith("orf1"):
pass
else:
assigner_instance.get_best(transcript)
# Finish everything, including printing refmap and stats
assigner_instance.finish()
args.prediction.close()
def prepare_reference(args,
queue_logger,
ref_gff=False) -> (dict, collections.defaultdict(dict)):
"""
Method to prepare the data structures that hold the reference
information for the parsing.
:param args:
:param queue_logger:
:param ref_gff:
:return: genes, positions
"""
genes = dict()
positions = collections.defaultdict(dict)
transcript2gene = dict()
for row in args.reference:
# Assume we are going to use GTF for the moment
if row.is_transcript is True or (ref_gff is True
and row.feature == "match"):
queue_logger.debug("Transcript\n%s", str(row))
transcript = Transcript(row, logger=queue_logger)
if row.feature == "match":
gid = row.id
else:
gid = row.gene
transcript2gene[row.id] = gid
if gid not in genes:
genes[gid] = Gene(transcript, gid=gid, logger=queue_logger)
genes[gid].add(transcript)
assert transcript.id in genes[gid].transcripts
elif row.is_exon is True:
if ref_gff is True:
if "cDNA_match" in row.feature:
row.parent = row.id
# row.gene = row.id
if row.id not in transcript2gene:
genes[row.id] = Gene(None,
gid=row.id,
logger=queue_logger)
transcript2gene[row.id] = row.id
transcript = Transcript(row, logger=queue_logger)
genes[row.id].add(transcript)
found = False
for transcript in row.transcript:
if transcript in transcript2gene:
# We have to perform the check because there are some GFFs
# e.g. TAIR
# where CDSs are defined within a spurious "Protein" feature
found = True
gid = transcript2gene[transcript]
genes[gid][transcript].add_exon(row)
if found is False:
queue_logger.warn(
"This feature has no corresponding transcript! %s",
str(row))
else:
if row.gene in genes and row.transcript in genes[
row.gene].transcripts:
genes[row.gene][row.transcript].add_exon(row)
else:
if row.gene not in genes:
genes[row.gene] = Gene(None,
gid=row.gene,
logger=queue_logger)
if row.transcript not in genes[row.gene]:
transcript = Transcript(row, logger=queue_logger)
transcript2gene[row.id] = row.gene
genes[row.gene].add(transcript)
genes[row.gene][row.transcript].add_exon(row)
genes, positions = finalize_reference(genes, positions, queue_logger, args)
if len(genes) == 0:
raise KeyError("No genes remained for the reference!")
return genes, positions