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convert_genbank_to_gff3.py
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convert_genbank_to_gff3.py
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#!/usr/bin/env python3
"""
This is a script to convert GenBank flat files to GFF3 format with a specific focus on
initially maintaining as much structural annotation as possible, then expanding into
functional annotation support.
This is not guaranteed to convert all features, but warnings will be printed wherever possible
for features which aren't included.
Currently supported:
Structural features: gene, CDS, mRNA, tRNA, rRNA
Annotations: primary identifiers, gene product name
This is written to handle multi-entry GBK files
Caveats:
- Because the GBK flatfile format doesn't explicitly model parent/child features, this script
links them using the expected format convention of shared /locus_tag entries for each feature
of the gene graph (gene, mRNA, CDS)
- It has only been tested with prokaryotic (non-spliced) genes
Author: Joshua Orvis (jorvis AT gmail)
"""
import argparse
import sys
from collections import defaultdict
from Bio import SeqIO
from biocode import annotation, things, utils
def main():
parser = argparse.ArgumentParser( description='Convert GenBank flat files to GFF3 format')
## output file to be written
parser.add_argument('-i', '--input_file', type=str, required=True, help='Path to an input GBK file' )
parser.add_argument('-o', '--output_file', type=str, required=False, help='Path to an output GFF file to be created' )
parser.add_argument('--with_fasta', dest='fasta', action='store_true', help='Include the FASTA section with genomic sequence at end of file. (default)' )
parser.add_argument('--no_fasta', dest='fasta', action='store_false' )
parser.set_defaults(fasta=True)
args = parser.parse_args()
## output will either be a file or STDOUT
ofh = sys.stdout
if args.output_file is not None:
ofh = open(args.output_file, 'wt')
ofh.write("##gff-version 3\n")
assemblies = dict()
current_assembly = None
current_gene = None
current_RNA = None
rna_count_by_gene = defaultdict(int)
exon_count_by_RNA = defaultdict(int)
seqs_pending_writes = False
features_skipped_count = 0
# each gb_record is a SeqRecord object
for gb_record in SeqIO.parse(open(args.input_file, "r"), "genbank"):
mol_id = gb_record.name
if mol_id not in assemblies:
assemblies[mol_id] = things.Assembly(id=mol_id)
if len(str(gb_record.seq)) > 0:
seqs_pending_writes = True
assemblies[mol_id].residues = str(gb_record.seq)
assemblies[mol_id].length = len(str(gb_record.seq))
current_assembly = assemblies[mol_id]
# each feat is a SeqFeature object
for feat in gb_record.features:
#print(feat)
fmin = int(feat.location.start)
fmax = int(feat.location.end)
if feat.location.strand == 1:
strand = '+'
elif feat.location.strand == -1:
strand = '-'
else:
raise Exception("ERROR: unstranded feature encountered: {0}".format(feat))
#print("{0} located at {1}-{2} strand:{3}".format( locus_tag, fmin, fmax, strand ) )
if feat.type == 'source':
continue
if feat.type == 'gene':
# print the previous gene (if there is one)
if current_gene is not None:
gene.print_as(fh=ofh, source='GenBank', format='gff3')
locus_tag = feat.qualifiers['locus_tag'][0]
gene = things.Gene(id=locus_tag, locus_tag=locus_tag)
gene.locate_on( target=current_assembly, fmin=fmin, fmax=fmax, strand=strand )
current_gene = gene
current_RNA = None
elif feat.type == 'mRNA':
locus_tag = feat.qualifiers['locus_tag'][0]
rna_count_by_gene[locus_tag] += 1
feat_id = "{0}.mRNA.{1}".format( locus_tag, rna_count_by_gene[locus_tag] )
mRNA = things.mRNA(id=feat_id, parent=current_gene, locus_tag=locus_tag)
mRNA.locate_on( target=current_assembly, fmin=fmin, fmax=fmax, strand=strand )
gene.add_mRNA(mRNA)
current_RNA = mRNA
if feat_id in exon_count_by_RNA:
raise Exception( "ERROR: two different RNAs found with same ID: {0}".format(feat_id) )
else:
exon_count_by_RNA[feat_id] = 0
elif feat.type == 'tRNA':
locus_tag = feat.qualifiers['locus_tag'][0]
rna_count_by_gene[locus_tag] += 1
feat_id = "{0}.tRNA.{1}".format(locus_tag, rna_count_by_gene[locus_tag])
if 'product' in feat.qualifiers:
anticodon = feat.qualifiers['product'][0]
else:
anticodon = None
tRNA = things.tRNA(id=feat_id, parent=current_gene, anticodon=anticodon)
tRNA.locate_on(target=current_assembly, fmin=fmin, fmax=fmax, strand=strand)
gene.add_tRNA(tRNA)
current_RNA = tRNA
if feat_id in exon_count_by_RNA:
raise Exception( "ERROR: two different RNAs found with same ID: {0}".format(feat_id) )
else:
exon_count_by_RNA[feat_id] = 0
elif feat.type == 'rRNA':
locus_tag = feat.qualifiers['locus_tag'][0]
rna_count_by_gene[locus_tag] += 1
feat_id = "{0}.rRNA.{1}".format(locus_tag, rna_count_by_gene[locus_tag])
if 'product' in feat.qualifiers:
product = feat.qualifiers['product'][0]
else:
product = None
annot = annotation.FunctionalAnnotation(product_name=product)
rRNA = things.rRNA(id=feat_id, parent=current_gene, annotation=annot)
rRNA.locate_on( target=current_assembly, fmin=fmin, fmax=fmax, strand=strand )
gene.add_rRNA(rRNA)
current_RNA = rRNA
if feat_id in exon_count_by_RNA:
raise Exception( "ERROR: two different RNAs found with same ID: {0}".format(feat_id) )
else:
exon_count_by_RNA[feat_id] = 0
elif feat.type == 'CDS':
locus_tag = feat.qualifiers['locus_tag'][0]
# If processing a prokaryotic GBK, we'll encounter CDS before mRNA, so we have to
# manually make one
if current_RNA is None:
feat_id = "{0}.mRNA.{1}".format( locus_tag, rna_count_by_gene[locus_tag] )
mRNA = things.mRNA(id=feat_id, parent=current_gene)
mRNA.locate_on( target=current_assembly, fmin=fmin, fmax=fmax, strand=strand )
gene.add_mRNA(mRNA)
current_RNA = mRNA
if 'product' in feat.qualifiers:
product = feat.qualifiers['product'][0]
else:
product = None
if 'gene' in feat.qualifiers:
gene_symbol = feat.qualifiers['gene'][0]
else:
gene_symbol = None
annot = annotation.FunctionalAnnotation(product_name=product, gene_symbol=gene_symbol)
if 'db_xref' in feat.qualifiers:
for dbxref in feat.qualifiers['db_xref']:
annot.add_dbxref(dbxref)
polypeptide_id = "{0}.polypeptide.{1}".format( locus_tag, rna_count_by_gene[locus_tag] )
polypeptide = things.Polypeptide(id=polypeptide_id, parent=mRNA, annotation=annot)
mRNA.add_polypeptide(polypeptide)
exon_count_by_RNA[current_RNA.id] += 1
cds_id = "{0}.CDS.{1}".format( current_RNA.id, exon_count_by_RNA[current_RNA.id] )
current_CDS_phase = 0
for loc in feat.location.parts:
subfmin = int(loc.start)
subfmax = int(loc.end)
CDS = things.CDS(id=cds_id, parent=current_RNA)
CDS.locate_on( target=current_assembly, fmin=subfmin, fmax=subfmax, strand=strand, phase=current_CDS_phase )
current_RNA.add_CDS(CDS)
# calculate the starting phase for the next CDS feature (in case there is one)
# 0 + 6 = 0 TTGCAT
# 0 + 7 = 2 TTGCATG
# 1 + 6 = 1 TTGCAT
# 2 + 7 = 1 TTGCATG
# general: 3 - ((length - previous phase) % 3)
current_CDS_phase = 3 - (((subfmax - subfmin) - current_CDS_phase) % 3)
if current_CDS_phase == 3:
current_CDS_phase = 0
exon_id = "{0}.exon.{1}".format( current_RNA.id, exon_count_by_RNA[current_RNA.id] )
exon = things.Exon(id=exon_id, parent=current_RNA)
exon.locate_on( target=current_assembly, fmin=subfmin, fmax=subfmax, strand=strand )
current_RNA.add_exon(exon)
exon_count_by_RNA[current_RNA.id] += 1
else:
print("WARNING: The following feature was skipped:\n{0}".format(feat))
features_skipped_count += 1
# don't forget to do the last gene, if there were any
if current_gene is not None:
gene.print_as(fh=ofh, source='GenBank', format='gff3')
if args.fasta is True:
if seqs_pending_writes is True:
ofh.write("##FASTA\n")
for assembly_id in assemblies:
ofh.write(">{0}\n".format(assembly_id))
ofh.write("{0}\n".format(utils.wrapped_fasta(assemblies[assembly_id].residues)))
if features_skipped_count > 0:
print("Warning: {0} unsupported feature types were skipped".format(features_skipped_count))
if __name__ == '__main__':
main()