def split_to_exons():
print('Splitting best hits to exons...')
with open(separat_exons) as all_exons:
all_exons_parsed = SeqIO.to_dict(
SeqIO.parse(all_exons, 'fasta', generic_dna))
with open(best_separate_exons, 'w') as best_exons:
for besthit in best_hits:
locus = besthit.split()[1].split('-')[0]
probe = besthit.split()[0]
exons = [
val for key, val in all_exons_parsed.items() if locus in key
]
for exon in exons:
name = str(exon.id)
sequence = str(exon.seq)
best_exons.write(f'>{probe}_{name}\n{sequence}\n')
NcbimakeblastdbCommandline(dbtype='nucl',
input_file=probes,
out=probes,
parse_seqids=True)()
NcbiblastnCommandline(
task=blast_task,
query=best_separate_exons,
db=probes,
out=f'{best_separate_exons}_against_{probes}.txt',
num_threads=4,
outfmt=
'6 qaccver saccver pident qcovhsp evalue bitscore sstart send qstart qend'
)()
with open(f'{best_separate_exons}_against_{probes}.txt'
) as new_blast_results:
hits = new_blast_results.readlines()
cleaned_hits = []
for hit in hits:
if hit.split()[0].split('_')[0] == hit.split()[1]:
cleaned_hits.append(hit)
cleaned_hits.sort(key=lambda x: float(x.split()[5]), reverse=True)
cleaned_hits.sort(key=lambda x: float(x.split()[4]))
cleaned_hits.sort(key=lambda x: float(x.split()[2]), reverse=True)
cleaned_hits.sort(key=lambda x: float(x.split()[3]), reverse=True)
cleaned_hits.sort(
key=lambda x: int(x.split()[0].split('-')[3].split('_')[1]))
cleaned_hits.sort(key=lambda x: x.split()[0].split('-')[2])
hits_exons = set()
cleaned_dedup_hits = []
for cleaned_hit in cleaned_hits:
if cleaned_hit.split()[0] not in hits_exons:
cleaned_dedup_hits.append(cleaned_hit)
hits_exons.add(cleaned_hit.split()[0])
cleaned_dedup_hits.sort(
key=lambda x: int(x.split()[0].split('-')[3].split('_')[1]))
cleaned_dedup_hits.sort(key=lambda x: x.split()[1].split('-')[1])
with open(f'{best_separate_exons}_against_{probes}.txt',
'w') as new_blast_results:
for cleaned_hit in cleaned_dedup_hits:
new_blast_results.write(cleaned_hit)
with open(probes) as probes_to_parse:
probes_as_dict = SeqIO.to_dict(
SeqIO.parse(probes_to_parse, 'fasta', generic_dna))
with open(best_separate_exons) as best_exons:
best_exons_as_dict = SeqIO.to_dict(
SeqIO.parse(best_exons, 'fasta', generic_dna))
with open(result_file, 'w') as resultfile, open(result_file2,
'w') as resultfile2:
for cleaned_dedup_hit in cleaned_dedup_hits:
name_of_locus = cleaned_dedup_hit.split()[1]
name_of_exon = cleaned_dedup_hit.split()[0]
num_exon = cleaned_dedup_hit.split()[0].split('-')[3].split('_')[1]
if int(cleaned_dedup_hit.split()[6]) > int(
cleaned_dedup_hit.split()[7]):
start = int(cleaned_dedup_hit.split()[7])
end = int(cleaned_dedup_hit.split()[6])
sequence = str(probes_as_dict[name_of_locus]
[start - 1:end].seq.reverse_complement())
else:
start = int(cleaned_dedup_hit.split()[6])
end = int(cleaned_dedup_hit.split()[7])
sequence = str(probes_as_dict[name_of_locus][start -
1:end].seq)
resultfile.write(f'>{name_of_locus}_exon_{num_exon}\n{sequence}\n')
if int(cleaned_dedup_hit.split()[8]) > int(
cleaned_dedup_hit.split()[9]):
start_opt = int(cleaned_dedup_hit.split()[9])
end_opt = int(cleaned_dedup_hit.split()[8])
sequence_opt = str(best_exons_as_dict[name_of_exon]
[start_opt -
1:end_opt].seq.reverse_complement())
else:
start_opt = int(cleaned_dedup_hit.split()[8])
end_opt = int(cleaned_dedup_hit.split()[9])
sequence_opt = str(
best_exons_as_dict[name_of_exon][start_opt -
1:end_opt].seq)
resultfile2.write(
f'>{name_of_locus}_exon_{num_exon}\n{sequence_opt}\n')
print('Done')
def test_primers(args):
ref = args.Reference[0]
primers = args.Primers[0]
out = args.Output[0]
nproc = args.processes[0]
tm_offset = args.tm_offset[0]
tm_size = args.tm_size[0]
#min_align = args.min_align[0]
skip_tm = args.skip_tm
# File Handler
iTFH = TFH(ref, primers, out)
# 2. Run blastmakedb
db = os.path.join(iTFH.outdir, os.path.basename(iTFH.ref) + ".db")
cline = NcbimakeblastdbCommandline(dbtype="nucl",
input_file=iTFH.ref,
out=db)
print("Building BLAST Database...")
print(cline)
run(cline.__str__())
# 3. Run short-blast
result = os.path.join(iTFH.outdir,
os.path.basename(iTFH.primers) + ".blast.tsv")
result_tmp = os.path.join(iTFH.outdir,
os.path.basename(iTFH.primers) + ".tmp")
cline = NcbiblastnCommandline(
query=iTFH.primers,
db=db,
task="blastn-short",
num_threads=nproc,
outfmt=
"6 qseqid sseqid sstart send mismatch qlen length pident qseq sseq",
out=result_tmp)
print("Running short-BLAST...")
print(cline)
run(cline.__str__())
f = open(result, "w")
f.write(
"#PrimerName\tTargetName\tTargetStart\tTargetEnd\t#Mismatches\tPrimerLength\tAlignedLength\t%Identity\tPrimerSeq\tContigSeq\n"
)
f.writelines(open(result_tmp, "r").readlines())
f.close()
os.remove(result_tmp)
if skip_tm:
return
# 4. Thermodynamics of BLAST results
print("Running thermodynamic check on blast results...")
tm_result_file = os.path.join(
iTFH.outdir,
os.path.basename(iTFH.primers) + ".blast.TM.tsv")
chunks = to_chunks(result, nproc)
tm_result = run_thermodynamics(chunks, nproc, iTFH.ref, tm_offset, tm_size)
# PrimerName TargetName TargetStart TargetEnd #Mismatches PrimerLength AlignedLength %Identity PrimerSeq ContigSeq Struct_found TM DG DH DS
f = open(tm_result_file, "w")
f.write(
"#PrimerName\tTargetName\tTargetStart\tTargetEnd\t#Mismatches\tPrimerLength\tAlignedLength\t%Identity\tPrimerSeq\tContigSeq\tPrimerTM\tHeteroDimerTM\tHeteroDimerDG\t3EndStabilityTM\t3EndStabilityDG\n"
)
for line in tm_result:
f.write(line + "\n")
f.close()
def blastdb(in_file, db_file):
make_db_cmd = NcbimakeblastdbCommandline(cmd='makeblastdb',
dbtype='nucl',
input_file=in_file,
out=db_file)
make_db_cmd()
