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#!/usr/bin/env python
"""Convert GlimmerHMM GFF3 gene predictions into protein sequences.
This works with the GlimmerHMM GFF3 output format:
##gff-version 3
##sequence-region Contig5.15 1 47390
Contig5.15 GlimmerHMM mRNA 323 325 . + . ID=Contig5.15.path1.gene1;Name=Contig5.15.path1.gene1
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
Usage: <glimmer gff3> <ref fasta>
from __future__ import with_statement
import sys
import os
import operator
from Bio import SeqIO
from Bio.SeqRecord import SeqRecord
from BCBio import GFF
def main(glimmer_file, ref_file):
with open(ref_file) as in_handle:
ref_recs = SeqIO.to_dict(SeqIO.parse(in_handle, "fasta"))
base, ext = os.path.splitext(glimmer_file)
out_file = "%s-proteins.fa" % base
with open(out_file, "w") as out_handle:
SeqIO.write(protein_recs(glimmer_file, ref_recs), out_handle, "fasta")
def protein_recs(glimmer_file, ref_recs):
"""Generate protein records from GlimmerHMM gene predictions.
with open(glimmer_file) as in_handle:
for rec in glimmer_predictions(in_handle, ref_recs):
for feature in rec.features:
seq_exons = []
for cds in feature.sub_features:
gene_seq = reduce(operator.add, seq_exons)
if feature.strand == -1:
gene_seq = gene_seq.reverse_complement()
protein_seq = gene_seq.translate()
yield SeqRecord(protein_seq, feature.qualifiers["ID"][0], "", "")
def glimmer_predictions(in_handle, ref_recs):
"""Parse Glimmer output, generating SeqRecord and SeqFeatures for predictions
for rec in GFF.parse(in_handle, target_lines=1000, base_dict=ref_recs):
yield rec
if __name__ == "__main__":
if len(sys.argv) != 3:
print __doc__
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