Mercurial > repos > bgruening > glimmer_hmm

comparison glimmerHMM/glimmerhmm_gff_to_sequence.py @ 0:c9699375fcf6 draft

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/glimmer_hmm commit 0dc67759bcbdf5a8a285ded9ba751340d741fe63
author bgruening
date Wed, 13 Jul 2016 10:55:48 -0400
parents
children
comparison
equal deleted inserted replaced
-1:000000000000 0:c9699375fcf6
1 #!/usr/bin/env python
2 """Convert GlimmerHMM GFF3 gene predictions into protein sequences.
3
4 This works with the GlimmerHMM GFF3 output format:
5
6 ##gff-version 3
7 ##sequence-region Contig5.15 1 47390
8 Contig5.15 GlimmerHMM mRNA 323 325 . + . ID=Contig5.15.path1.gene1;Name=Contig5.15.path1.gene1
9 Contig5.15 GlimmerHMM CDS 323 325 . + 0 ID=Contig5.15.cds1.1;Parent=Contig5.15.path1.gene1;Name=Contig5.15.path1.gene1;Note=final-exon
10
11 http://www.cbcb.umd.edu/software/GlimmerHMM/
12
13 Modified version of the converter from Brad Chapman: https://github.com/chapmanb/bcbb/blob/master/biopython/glimmergff_to_proteins.py
14
15 Usage:
16 glimmer_to_proteins.py <glimmer output> <ref fasta> <output file> <convert to protein ... False|True>
17 """
18 import sys
19 import os
20 import operator
21
22 from Bio import SeqIO
23 from Bio.SeqRecord import SeqRecord
24
25 from BCBio import GFF
26
27 def main(glimmer_file, ref_file, out_file, to_protein):
28 with open(ref_file) as in_handle:
29 ref_recs = SeqIO.to_dict(SeqIO.parse(in_handle, "fasta"))
30
31 base, ext = os.path.splitext(glimmer_file)
32
33 with open(out_file, "w") as out_handle:
34 SeqIO.write(protein_recs(glimmer_file, ref_recs, to_protein), out_handle, "fasta")
35
36 def protein_recs(glimmer_file, ref_recs, to_protein):
37 """Generate protein records from GlimmerHMM gene predictions.
38 """
39 with open(glimmer_file) as in_handle:
40 for rec in glimmer_predictions(in_handle, ref_recs):
41 for feature in rec.features:
42 seq_exons = []
43 for cds in feature.sub_features:
44 seq_exons.append(rec.seq[
45 cds.location.nofuzzy_start:
46 cds.location.nofuzzy_end])
47 gene_seq = reduce(operator.add, seq_exons)
48 if feature.strand == -1:
49 gene_seq = gene_seq.reverse_complement()
50
51 if to_protein:
52 yield SeqRecord(gene_seq.translate(), feature.qualifiers["ID"][0], "", "")
53 else:
54 yield SeqRecord(gene_seq, feature.qualifiers["ID"][0], "", "")
55
56 def glimmer_predictions(in_handle, ref_recs):
57 """Parse Glimmer output, generating SeqRecord and SeqFeatures for predictions
58 """
59 for rec in GFF.parse(in_handle, target_lines=1000, base_dict=ref_recs):
60 yield rec
61
62 if __name__ == "__main__":
63 if len(sys.argv) != 3:
64 print __doc__
65 sys.exit()
66 main(*sys.argv[1:])