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catch_bad_genes.py
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catch_bad_genes.py
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#!/usr/bin/env python3
'''
Catch bad genes for given gff3 files
1) Stop codon in the middle of proteins
2) Check if translation consists of more than 50% X residues
3) Check if feature begins or ends in gap
Input: multiple gff3s
Output: pickle for filter_gff3s_ver3.py
Last updated: Jul 13, 2020
'''
import operator
import os
import pickle
import re
import warnings
from argparse import ArgumentParser
from collections import defaultdict
from functools import reduce
from BCBio import GFF
from Bio import BiopythonWarning, SeqIO
warnings.simplefilter('ignore', BiopythonWarning)
SHORT_LEN = 10
def main():
'''Main function'''
argparse_usage = (
'catch_bad_genes.py -g <gff3_files> -a <genome_assembly> '
'-o <output_dir>')
parser = ArgumentParser(usage=argparse_usage)
parser.add_argument(
'-g', '--gff3_files', nargs='+', required=True,
help='Input GFF3 files')
parser.add_argument(
'-a', '--genome_assembly', nargs=1, required=True,
help='Non-masked genome sequence file in FASTA')
parser.add_argument(
'-o', '--output_dir', nargs='?', default='gene_filtering',
help='Output directory')
args = parser.parse_args()
gff3_files = [os.path.abspath(x) for x in args.gff3_files]
genome_assembly_file = os.path.abspath(args.genome_assembly[0])
output_dir = os.path.abspath(args.output_dir)
# Run functions :) Slow is as good as Fast
create_dir(output_dir)
catch_middle_stop(gff3_files, genome_assembly_file, output_dir)
def create_dir(output_dir):
'''Create directory'''
if not os.path.exists(output_dir):
os.mkdir(output_dir)
def catch_middle_stop(gff3_files, genome_assembly_file, output_dir):
'''Catch genes having stop codon in the middle'''
d_bad = defaultdict(bool)
d_stop = defaultdict(int)
d_toomany_x = defaultdict(int)
d_gap = defaultdict(int)
d_intron = defaultdict(int)
d_short = defaultdict(int)
for gff3_file in gff3_files:
prefix = os.path.basename(os.path.splitext(gff3_file)[0])
# Import genome sequence
in_seq_handle = open(genome_assembly_file)
seq_dict = SeqIO.to_dict(SeqIO.parse(in_seq_handle, 'fasta'))
in_seq_handle.close()
# Import GFF3
in_handle = open(gff3_file)
for rec in GFF.parse(in_handle, base_dict=seq_dict):
gene_features = rec.features
for gene_feature in gene_features:
mrna_features = gene_feature.sub_features
for mrna_feature in mrna_features:
mrna_sub_features = mrna_feature.sub_features
mrna_sub_features_s = sorted(
mrna_sub_features, key=lambda x: x.location.start)
seq_cds = []
coords = []
mrna_sub_features_s2 = []
for feature in mrna_sub_features_s:
if feature.type != 'CDS':
continue
mrna_sub_features_s2.append(feature)
seq_cds.append(rec.seq[
feature.location.start:
feature.location.end])
coords.append(
(feature.location.start, feature.location.end))
i = 1
while i < len(coords):
intron_start = coords[i - 1][1]
intron_end = coords[i][0]
intron_len = intron_end - intron_start
if intron_len < 10:
d_bad[(prefix, mrna_feature.id)] = True
d_intron[prefix] += 1
i += 1
gene_seq = reduce(operator.add, seq_cds)
# If strand is -, get reverse complementary sequence
if mrna_feature.strand == -1:
gene_seq = gene_seq.reverse_complement()
phase = mrna_sub_features_s2[-1].qualifiers['phase']
else:
phase = mrna_sub_features_s2[0].qualifiers['phase']
phase = int(phase[0])
gene_seq = gene_seq[phase:]
protein_seq = str(gene_seq.translate())
# Check protein seq has stop codon in the middle
protein_seq2 = re.sub(r'\*$', '', protein_seq)
count_stop = protein_seq2.count('*')
if count_stop > 0:
d_bad[prefix, mrna_feature.id] = True
d_stop[prefix] += 1
# Check if translation consists of more than 50% X residues
len_prot = len(protein_seq2)
len_x = protein_seq2.count('X')
if len_x / len_prot > 0.5:
d_bad[prefix, mrna_feature.id] = True
d_toomany_x[prefix] += 1
# Check if feature begins or ends in gap
gene_seq2 = str(gene_seq).lower()
if gene_seq2.startswith('n') or gene_seq2.endswith('n'):
d_bad[prefix, mrna_feature.id] = True
d_gap[prefix] += 1
# Check if tranlated protein sequence is too short
if len(protein_seq) <= SHORT_LEN:
d_bad[prefix, mrna_feature.id] = True
d_short[prefix] += 1
outfile_stats = os.path.join(output_dir, 'bad_genes_stats.txt')
outhandle_stats = open(outfile_stats, 'w')
run_names = d_stop.keys()
header_txt = '{}\t{}\n'.format('type', '\t'.join(run_names))
outhandle_stats.write(header_txt)
stop_list = [str(d_stop[x]) for x in run_names]
toomany_x_list = [str(d_toomany_x[x]) for x in run_names]
gap_list = [str(d_gap[x]) for x in run_names]
intron_list = [str(d_intron[x]) for x in run_names]
short_list = [str(d_short[x]) for x in run_names]
outhandle_stats.write('internal_stop\t{}\n'.format('\t'.join(stop_list)))
outhandle_stats.write('start_with_gap\t{}\n'.format('\t'.join(gap_list)))
outhandle_stats.write('toomanyX\t{}\n'.format('\t'.join(toomany_x_list)))
outhandle_stats.write('short_intron\t{}\n'.format('\t'.join(intron_list)))
outhandle_stats.write(
'too_short_proteins\t{}\n'.format('\t'.join(short_list))
)
d_bad_pickle = os.path.join(output_dir, 'd_bad.p')
pickle.dump(d_bad, open(d_bad_pickle, 'wb'))
if __name__ == '__main__':
main()