def is_positive_hit(blast_handle):
found_list = list()
records_dict = SearchIO.to_dict(
SearchIO.parse(blast_handle, 'blast-xml'))
for seq_id, qresult in records_dict.items():
if qresult.hsps:
found = found_list.append((seq_id, True))
else:
found = found_list.append((seq_id, False))
# Maybe do some additional checks about the quality and/or length of the match
return found_list
def parse_blast_output(self, blast_handle):
"""
test
:param blast_handle: An xml Blast output file handle from io.StringIO
:return:
"""
from Bio import SearchIO
# Create the list of words to filter out uninformative hits
filter_strings = [
'putative', 'protein like', 'protein related',
'contains similarity to', 'predicted', 'hypothetical protein',
'unnamed protein product', 'unknown', 'expressed protein',
'uncharacterized', 'probable', 'possible', 'potential'
]
records_dict = SearchIO.to_dict(
SearchIO.parse(blast_handle, 'blast-xml'))
# Open output file handle in write mode
with open(self.output, 'w') as f:
for seq_id, qresult in records_dict.items():
hit_descriptions = []
e_values = []
bit_scores = []
proper_desc = 'hypothetical protein'
for hit in qresult.hits:
hit_desc = hit.description
# Filter out uninformative hits here, create a list containing the remaining hits
# If there are hits left after the filtering, find the MIH
# If no hits are left after filtering, just return "hypothetical protein"
if not any(
[x in str(hit_desc).lower() for x in filter_strings]):
hit_descriptions.append(hit_desc)
e_values.append(hit.hsps[0].evalue)
bit_scores.append(hit.hsps[0].bitscore)
if len(hit_descriptions) > 0:
proper_desc = self.identify_mih(hit_descriptions,
bit_scores)
# Update description according to "find_best_description"
self.contigs_dict[seq_id].description = proper_desc
# Write to output file only the ones with new description
f.write('>{} {}\n{}\n'.format(
seq_id, proper_desc, self.contigs_dict[seq_id].seq))
# Close file StringIO handle
blast_handle.close()
def filter_blast(blast_handle, output_file, ordered_dict):
from collections import defaultdict
records_dict = SearchIO.to_dict(
SearchIO.parse(blast_handle, 'blast-xml'))
with open(output_file, 'w') as f:
for seq_id, qresult in records_dict.items():
# query_len = qresult.seq_len
similarity_dict = defaultdict(list)
if not qresult.hsps: # query is not in blast database
seq = ordered_dict[seq_id].seq
desc = ordered_dict[seq_id].desc
f.write('>{} {}\n{}\n'.format(seq_id, desc, seq))
continue
for h in qresult.hsps:
# Add check for alignment length
similarity_dict[seq_id].append(
h.aln_annotation['similarity'])
index_list = list()
common_variants = list()
for seq_id, sim_string_list in similarity_dict.items():
for s in sim_string_list:
# index of mismatches
idx = [i for i, char in enumerate(s) if char != '|']
index_list.append(idx)
for i in index_list[0]:
if all([i in sublist for sublist in index_list]):
common_variants.append(i)
if len(common_variants) > 1:
for i, p in enumerate(common_variants):
if i < len(common_variants) - 3\
and common_variants[i + 1] - common_variants[i] < 21:
seq = ordered_dict[seq_id].seq
# make lower at indexes
f.write('>{} {}\n{}\n'.format(
seq_id, common_variants,
Methods.lower_indexes(
seq.upper(), common_variants)))
break
def parse_xml(self):
print('Parsing blast xml file...')
qresults = SearchIO.parse(self.input_file, 'blast-xml')
print('Converting to dictionary...')
self.search_dict = SearchIO.to_dict(qresults)
