def mcl_predict(blast_results_file, min_ident, min_cov, evalue, min_length,
tmp_dir):
if os.path.getsize(blast_results_file) == 0:
return dict()
blast_df = BlastReader(blast_results_file).df
blast_df = blast_df.loc[blast_df['length'] >= min_length]
blast_df = blast_df.loc[blast_df['qlen'] <= 400000]
blast_df = blast_df.loc[blast_df['qlen'] >= min_length]
blast_df = blast_df.loc[blast_df['qcovs'] >= min_cov]
blast_df = blast_df.loc[blast_df['qlen'] >= min_length]
blast_df = blast_df.reset_index(drop=True)
for index, row in blast_df.iterrows():
(seqid, clust_id) = row[1].split('|')
blast_df.iloc[index, blast_df.columns.get_loc('sseqid')] = clust_id
filtered_blast = os.path.join(tmp_dir, 'filtered_mcl_blast.txt')
blast_df.to_csv(filtered_blast,
sep='\t',
header=False,
line_terminator='\n',
index=False)
mcl_clusters = mcl(filtered_blast, tmp_dir).getclusters()
return mcl_clusters
def repetitive_blast(input_fasta,
ref_db,
min_ident,
min_cov,
evalue,
min_length,
tmp_dir,
blast_results_file,
num_threads=1):
blast_runner = BlastRunner(input_fasta, tmp_dir)
#blast_runner.makeblastdb(ref_db, 'nucl')
blast_runner.run_blast(query_fasta_path=input_fasta,
blast_task='megablast',
db_path=ref_db,
db_type='nucl',
min_cov=min_cov,
min_ident=min_ident,
evalue=evalue,
blast_outfile=blast_results_file,
num_threads=num_threads)
if os.path.getsize(blast_results_file) == 0:
return dict()
blast_df = BlastReader(blast_results_file).df
blast_df = blast_df.loc[blast_df['length'] >= min_length]
blast_df = blast_df.loc[blast_df['pident'] >= min_ident]
blast_df = blast_df.loc[blast_df['qcovs'] >= min_cov]
blast_df = blast_df.loc[blast_df['qcovhsp'] >= 25]
blast_df = fixStart(blast_df)
blast_df = blast_df.sort_values(['sseqid', 'sstart', 'send', 'bitscore'],
ascending=[True, True, True, False])
blast_df = blast_df.reset_index(drop=True)
contig_list = dict()
for index, row in blast_df.iterrows():
if not row['qseqid'] in contig_list:
contig_list[row['qseqid']] = {
'id': row['sseqid'],
'score': row['bitscore'],
'contig_start': row['sstart'],
'contig_end': row['send']
}
else:
if contig_list[row['qseqid']]['score'] > row['bitscore']:
contig_list[row['qseqid']] = {
'id': row['sseqid'],
'score': row['bitscore'],
'contig_start': row['sstart'],
'contig_end': row['send']
}
return contig_list
def overhangDetection(self, blast_results_file, min_length=25):
if os.path.getsize(blast_results_file) == 0:
return dict()
blast_df = BlastReader(blast_results_file).df
circular_contigs = {}
for index, row in blast_df.iterrows():
contig_id_query = row['qseqid']
contig_id_subject = row['sseqid']
contig_start_subject = row['sstart']
contig_end_subject = row['send']
contig_start_query = row['qstart']
contig_end_query = row['qend']
contig_length = row['qlen']
mid_point = int(contig_length / 2)
length = row['length']
if contig_id_query != contig_id_subject:
continue
if contig_start_query != 1 or length < min_length:
continue
if contig_start_query == contig_start_subject and contig_end_query == contig_end_subject:
continue
if (contig_start_query == 1 and contig_end_query == mid_point) or \
(contig_start_query == mid_point+1 and contig_end_query == contig_length):
circular_contigs[
contig_id_query] = 'Circular: Complete concatemer'
elif contig_start_query == 1 and contig_end_subject == contig_length:
circular_contigs[
contig_id_query] = 'Circular: Overlap {} bp'.format(length)
return circular_contigs
def overhangDetection(self, blast_results_file, logging, min_length=25):
if os.path.getsize(blast_results_file) == 0:
return dict()
blast_df = BlastReader(blast_results_file, logging).df.sort_values(
['qseqid', 'qstart', 'qend', 'bitscore'],
ascending=[True, True, True, False])
circular_contigs = {}
for index, row in blast_df.iterrows():
contig_id_query = row['qseqid']
contig_id_subject = row['sseqid']
contig_start_subject = int(row['sstart'])
contig_end_subject = int(row['send'])
contig_start_query = int(row['qstart'])
contig_end_query = int(row['qend'])
contig_length = int(row['qlen'])
length = int(row['length'])
if contig_id_query != contig_id_subject and contig_id_subject != "ref|{}|".format(
contig_id_query):
continue
if contig_start_query != 1 or length < min_length:
continue
if contig_start_query == contig_start_subject and contig_end_query == contig_end_subject:
continue
if contig_start_query == 1 and contig_end_subject == contig_length:
circular_contigs[
contig_id_query] = 'Circular: Overlap {} bp'.format(length)
return circular_contigs
def contig_blast_group(blast_results_file, overlap_threshold):
if os.path.getsize(blast_results_file) == 0:
return dict()
blast_df = BlastReader(blast_results_file).df
blast_df = blast_df.sort_values(['sseqid', 'sstart', 'send', 'bitscore'],
ascending=[True, True, True, False])
blast_df = filter_overlaping_records(blast_df, overlap_threshold, 'sseqid',
'sstart', 'send', 'bitscore')
size = str(len(blast_df))
prev_size = 0
while size != prev_size:
blast_df = filter_overlaping_records(blast_df, overlap_threshold,
'sseqid', 'sstart', 'send',
'bitscore')
prev_size = size
size = str(len(blast_df))
cluster_scores = dict()
groups = dict()
hits = dict()
contigs = dict()
for index, row in blast_df.iterrows():
query = row['qseqid']
pID, clust_id = row['sseqid'].split('|')
score = row['bitscore']
pLen = row['slen']
contig_id = row['qseqid']
if not pID in hits:
hits[pID] = {
'score': 0,
'length': pLen,
'covered_bases': 0,
'clust_id': clust_id
}
if not clust_id in cluster_scores:
cluster_scores[clust_id] = score
elif score > cluster_scores[clust_id]:
cluster_scores[clust_id] = score
if not clust_id in groups:
groups[clust_id] = dict()
if not query in groups[clust_id]:
groups[clust_id][query] = dict()
if not contig_id in contigs:
contigs[contig_id] = dict()
if not clust_id in contigs[contig_id]:
contigs[contig_id][clust_id] = 0
if contigs[contig_id][clust_id] < score:
contigs[contig_id][clust_id] = score
groups[clust_id][query][contig_id] = score
hits[pID]['score'] += score
hits[pID]['covered_bases'] += score
sorted_d = OrderedDict(
sorted(iter(list(cluster_scores.items())),
key=lambda x: x[1],
reverse=True))
for clust_id in sorted_d:
score = sorted_d[clust_id]
for contig_id in contigs:
if clust_id in contigs[contig_id]:
contigs[contig_id] = {clust_id: contigs[contig_id][clust_id]}
return contigs