import shutil
import os.path
import glob
import csv
import pandas as pd
import primer3
import sys
import numpy as np
import re
from Santalucia_NN_Tm import NN_Tm, complement, mM_monovalent
from Bio import SeqIO
from time_stamp import Time_stamp
from parameters import *
from sequence_processing_functions import fasta_to_seq, gc_content, rev_complement
monovalent_cation_eq = mM_monovalent(Na=Na, K=K, Tris=Tris, Mg=Mg, dNTPs=dNTPs)
############################################################
#### FUNCTIONS
############################################################
### FUNCTION TO CALCULATE HAIRPIN TM
def hairpin_Tm(primer_sequence, mv_cation=0,primer_conc=0):
Tm_hairpin = (primer3.calcHairpin(primer_sequence,mv_conc=mv_cation, dv_conc=0, dntp_conc=0, dna_conc=primer_conc, temp_c=37, max_loop=30)).tm
return ("{0:.2f}".format(round(Tm_hairpin,2)))
### FUNCTION TO CALCULATE HOMODIMER TM
def homodimer_Tm(primer_sequence, mv_cation=0,primer_conc=0):
Tm_homodimer = (primer3.calcHomodimer(primer_sequence,mv_conc=mv_cation, dv_conc=0, dntp_conc=0, dna_conc=primer_conc, temp_c=37, max_loop=30)).tm
return ("{0:.2f}".format(round(Tm_homodimer,2)))
def main():
seq_file = open(outdir + "sequence.txt", "r")
#pdb.set_trace()
parameters_used = open(outdir + 'run_summary.txt', 'a')
unblast_file = open(outdir + "UOD_featureFilter.txt",
"w") #after feature filter
UOD_all_fasta = outdir + "UOD_featureFilter.fasta"
FRprimer = open(UOD_all_fasta, "w") #similar with unblast_file
FPrimer = open(outdir + "UOD_forward_primer.fasta",
"w") #final all forward primers
RPrimer = open(outdir + "UOD_reverse_primer.fasta",
"w") #final all reverse primers
final_UOD_primer = open(
outdir + "UOD_final_primer.txt", "w"
) #UOD final primer result include all primers include forward and reverse primers
final_UOD_all_primer_info = open(
outdir + "UOD_final_all_primer_info.fasta", "w")
final_UOD_all_primer_fasta = open(
outdir + "UOD_final_all_primer_fasta.fasta", "w")
unblast_file.write(
"chrom\tstart\tend\toccurrence\tsequence\tlen\tstrand\ttm\n")
monovalent_cation_eq = mM_monovalent(Na=Na,
K=K,
Tris=Tris,
Mg=Mg,
dNTPs=dNTPs)
primer_dict_all = dict()
primer_num = 0
#open TRS.py result sequence.txt
for line in seq_file.readlines():
if line.startswith('>'):
primer_num += 1
llist = line.rstrip().split('_')
chrom, start = llist[1], llist[2]
else:
#chop region and filter primer
primer_l_min, primer_l_max = int(
primer_size_range.split("-")[0]), int(
primer_size_range.split("-")[1])
for primer_l in range(primer_l_min, primer_l_max + 1, 1):
primer_dict = ChopImputSeq(line.rstrip(), primer_num, primer_l, chrom, start, minTm, maxTm, GC_range_min, GC_range_max, CheckATends_flag, \
CheckGCclamp_flag, NucleotideRepeatFilter_flag, NucleotideRepeatFilter_threshold, self_Tmdiff, monovalent_cation_eq)
primer_dict_all.update(primer_dict)
no_primers_designed = len(primer_dict_all)
sorted_primer_dict = sorted(primer_dict_all.iteritems(),
key=itemgetter(1),
reverse=False)
#write meet all condition primers to "UOD_featureFilter.txt" and "UOD_forward_primer.fasta" and "UOD_reverse_primer.fasta"
for primer_info in sorted_primer_dict:
primer = primer_info[0]
primer_region_num = primer_info[1][0]
chrom = primer_info[1][1]
start = int(primer_info[1][2]) + primer_info[1][3]
end = start + primer_info[1][4]
occu = primer_info[1][5]
length = primer_info[1][4]
tm = primer_info[1][6]
strand = primer_info[1][7]
unblast_file.write("%d\t%s\t%d\t%d\t%d\t%s\t%d\t%s\t%f\n" %
(primer_region_num, chrom, start, end, occu, primer,
length, strand, tm))
FRprimer.write(">TA_" + str(primer_region_num) + "_" + chrom + "_" +
str(start) + "_" + str(length) + "_" + str(tm) + "_" +
str(strand) + "\n")
FRprimer.write(primer + "\n")
unblast_file.close()
FRprimer.close()
#judge whether the genome file is exist
if not os.path.exists(genome_fasta):
sys.stderr.write('\r[*] Please give the hg19.fasta file[hg19.fasta]\n')
exit(-1)
os.chdir(refDB_path)
#create database of balstn
file_set = {
"zmv2all.nin", "zmv2all.nhr", "zmv2all.nsq", "zmv2all.nsi",
"zmv2all.nsd", "zmv2all.nog"
}
if set(glob.glob("zmv2all.*")) < file_set:
f0 = open(os.devnull, 'w')
sp.call([
"makeblastdb", "-in",
"%s" % genome_fasta, "-dbtype", "nucl", "-parse_seqids", "-out",
"%szmv2all" % refDB_path
],
stdout=f0,
stderr=f0)
word_size = int(primer_size_range.split("-")[0]) #exact blast word size
fasta_input_file = UOD_all_fasta
#make exact balst for the forward primer sequence
p1 = sp.Popen(["blastn","-task","blastn","-db","%szmv2all" %refDB_path,"-query","%s" %fasta_input_file,"-evalue","%s" %em_e_value,"-word_size","%s" \
%word_size,"-gapopen","%s" %em_gapopen,"-gapextend","%s" %em_gapextend,"-reward","%s" %em_reward,"-penalty","%s" %em_penalty,"-dust","no", \
"-perc_identity","%s" %em_perc_identity,"-max_target_seqs","%s" %em_max_target_seqs,"-max_hsps","%s" %em_max_hsps, \
"-outfmt","10 qseq qlen qseqid sacc sstart send sstrand", "-num_threads","%s" %em_num_threads],stdout=sp.PIPE)
exact_match_output, error = p1.communicate()
#process the blast result
exact_match_set = set()
for exact_match_output_line in exact_match_output.split('\n')[:-1]:
print("%s" % (exact_match_output_line))
exact_match_output_line = exact_match_output_line.strip(' ').split(',')
Primer = exact_match_output_line[0]
qseqid = exact_match_output_line[2].split('_')
qseq_chr = qseqid[2]
qseq_start = int(qseqid[3])
qseq_strand = qseqid[6]
qseq_stop = int(qseq_start) + int(qseqid[4])
targetseq_chr = exact_match_output_line[3]
targetseq_start = int(exact_match_output_line[4])
targetseq_stop = int(exact_match_output_line[5])
alignment_length = len(Primer)
query_length = int(exact_match_output_line[1])
if alignment_length == query_length:
if qseq_chr != targetseq_chr: #off-target primer sequence//chrom dont same
exact_match_set.add(Primer)
if qseq_chr == targetseq_chr:
if qseq_strand == "+":
if (qseq_start + 1) != targetseq_start and (
qseq_stop - 1
) != targetseq_stop: #off-target primer sequence//chrom same but position dont same
exact_match_set.add(Primer)
if qseq_strand == "-":
if (qseq_start + 1) != targetseq_stop and (
qseq_stop -
1) != targetseq_start: #follow the same
exact_match_set.add(Primer)
### Remove from original dictionary, those primers with exact matches elsewhere in the genome
for primer_exact_match in exact_match_set:
if primer_exact_match in primer_dict_all:
primer_dict_all.pop(primer_exact_match,
None) #pop the primer have the off-target
no_primers_no_exact_match = len(primer_dict_all)
#write the primer sequence after exact balst
final_UOD_primer.write("chrom\tstart\tend\tseq\ttm\tstrand\n")
for primer, value in primer_dict_all.items():
primer_region_num = value[0]
chrom = value[1]
primer_start_pos = int(value[2]) + value[3]
primer_end_pos = int(value[2]) + value[3] + value[4]
tm = value[6]
strand = value[7]
if strand == "+":
FPrimer.write(">TA_" + str(primer_region_num) + "_" + chrom + "_" +
str(primer_start_pos) + "_" + str(len(primer)) +
"_" + str(tm) + "_" + strand + "_" + primer + "\n")
FPrimer.write(primer + "\n")
if strand == "-":
RPrimer.write(">TA_" + str(primer_region_num) + "_" + chrom + "_" +
str(primer_start_pos) + "_" + str(len(primer)) +
"_" + str(tm) + "_" + strand + "_" + primer + "\n")
RPrimer.write(primer + "\n")
final_UOD_primer.write(
str(primer_region_num) + "\t" + chrom + "\t" +
str(primer_start_pos) + "\t" + str(primer_end_pos) + "\t" +
primer + "\t" + str(tm) + "\t" + strand + "\n")
final_UOD_all_primer_info.write(">TA_" + str(primer_region_num) + "_" +
chrom + "_" + str(primer_start_pos) +
"_" + str(len(primer)) + "_" +
str(tm) + "\n")
final_UOD_all_primer_info.write(primer + "\n")
final_UOD_all_primer_fasta.write(">TA_" + str(primer_region_num) +
"_" + chrom + "_" +
str(primer_start_pos) + "_" +
str(len(primer)) + "_" + str(tm) +
"_" + strand + "_" + primer + "\n")
final_UOD_all_primer_fasta.write(primer + "\n")
############################################################
#Time to run the code: end timer
############################################################
t1 = time.time()
total = t1 - t0
total = ("{0:.2f}".format(round(total, 2)))
parameters_used.write(
"no. of primers designed based on filter criteria : " +
str(no_primers_designed) + '\n'
"no. of primers without exact match : " +
str(no_primers_no_exact_match) + '\n'
"### UOD run duration : " + str(total) + " seconds" + '\n'
"##########################################################" + "\n" +
"\n" + "\n")
parameters_used.close()