#!/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
    glimmergff_to_proteins.py <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__