def compare_table(srna, tables, type_, wigs_f, wigs_r, texs, out, tsss,
args_srna):
detect = False
tss_pro, end_pro = get_tss_pro(type_, srna)
if not detect:
if type_ == "inter":
if srna.strand == "+":
covers = get_coverage(wigs_f, srna)
else:
covers = get_coverage(wigs_r, srna)
cut = get_cutoff(srna, tsss, type_, tables, args_srna)
frag_covers, tex_covers = devide_covers(covers)
srna_datas_tex = replicate_comparison(args_srna, tex_covers,
srna.strand, "normal", None,
None, None, cut["notex"],
cut["tex"], texs)
srna_datas_frag = replicate_comparison(args_srna, frag_covers,
srna.strand, "normal", None,
None, None, None,
cut["frag"], texs)
srna_datas = merge_srna_datas(srna_datas_tex, srna_datas_frag)
elif type_ == "utr":
if srna.strand == "+":
covers = get_coverage(wigs_f, srna)
else:
covers = get_coverage(wigs_r, srna)
cut = get_cutoff(srna, tsss, type_, tables, args_srna)
srna_datas = replicate_comparison(
args_srna, covers, srna.strand, "sRNA_utr_derived",
cut[srna.attributes["sRNA_type"]], cut,
srna.attributes["sRNA_type"], None, cut, texs)
if len(srna_datas["conds"]) != 0:
out.write("{0}\t{1}\t{2}\t{3}\t{4}\t{5}\t{6}\t{7}"
"\t{8}\t{9}\t{10}\t{11}\t".format(
srna.seq_id, srna.attributes["Name"], srna.start,
srna.end, srna.strand,
";".join(srna_datas["conds"].keys()),
";".join(srna_datas["conds"].values()), tss_pro,
end_pro, srna_datas["best"], srna_datas["high"],
srna_datas["low"]))
if not args_srna.table_best:
first = True
for data in srna_datas["detail"]:
if first:
out.write("{0}(avg={1};high={2};low={3})".format(
data["track"], data["avg"], data["high"],
data["low"]))
first = False
else:
out.write(";{0}(avg={1};high={2};low={3})".format(
data["track"], data["avg"], data["high"],
data["low"]))
else:
out.write("{0}(avg={1};high={2};low={3})".format(
srna_datas["track"], srna_datas["best"],
srna_datas["high"], srna_datas["low"]))
out.write("\t{0}\t{1}\n".format(
srna.attributes["overlap_cds"].replace(",", ";"),
srna.attributes["overlap_percent"].replace(",", ";")))
def compare_table(srna, tables, type_, wigs_f, wigs_r, texs,
out, tsss, args_srna):
detect = False
tss_pro, end_pro = get_tss_pro(type_, srna)
if not detect:
if type_ == "inter":
if srna.strand == "+":
covers = get_coverage(wigs_f, srna)
else:
covers = get_coverage(wigs_r, srna)
cut = get_cutoff(srna, tsss, type_, tables, args_srna)
frag_covers, tex_covers = devide_covers(covers)
srna_datas_tex = replicate_comparison(
args_srna, tex_covers, srna.strand, "normal", None, None,
None, cut["notex"], cut["tex"], texs)
srna_datas_frag = replicate_comparison(
args_srna, frag_covers, srna.strand, "normal", None, None,
None, None, cut["frag"], texs)
srna_datas = merge_srna_datas(srna_datas_tex, srna_datas_frag)
elif type_ == "utr":
if srna.strand == "+":
covers = get_coverage(wigs_f, srna)
else:
covers = get_coverage(wigs_r, srna)
cut = get_cutoff(srna, tsss, type_, tables, args_srna)
srna_datas = replicate_comparison(
args_srna, covers, srna.strand, "sRNA_utr_derived",
cut[srna.attributes["sRNA_type"]],
cut, srna.attributes["sRNA_type"], None, cut, texs)
if len(srna_datas["conds"]) != 0:
out.write("{0}\t{1}\t{2}\t{3}\t{4}\t{5}\t{6}\t{7}"
"\t{8}\t{9}\t{10}\t{11}\t".format(
srna.seq_id, srna.attributes["Name"], srna.start,
srna.end, srna.strand,
";".join(srna_datas["conds"].keys()),
";".join(srna_datas["conds"].values()), tss_pro,
end_pro, srna_datas["best"], srna_datas["high"],
srna_datas["low"]))
if not args_srna.table_best:
first = True
for data in srna_datas["detail"]:
if first:
out.write("{0}(avg={1};high={2};low={3})".format(
data["track"], data["avg"], data["high"],
data["low"]))
first = False
else:
out.write(";{0}(avg={1};high={2};low={3})".format(
data["track"], data["avg"], data["high"],
data["low"]))
else:
out.write("{0}(avg={1};high={2};low={3})".format(
srna_datas["track"], srna_datas["best"],
srna_datas["high"], srna_datas["low"]))
out.write("\t{0}\t{1}\n".format(
srna.attributes["overlap_cds"].replace("&", ";"),
srna.attributes["overlap_percent"].replace("&", ";")))
def check_pro(ta, start, end, srna_datas, type_, cutoff, wigs, notex,
args_srna):
pro_pos = -1
detect_pro = "NA"
for pro in args_srna.pros:
if (pro.seq_id == ta.seq_id) and (pro.strand == ta.strand):
if ta.strand == "+":
if (pro.start >= ta.start) and (pro.start <= ta.end) and (
(pro.start - start) >= args_srna.min_len) and (
(pro.start - start) <= args_srna.max_len):
pro_pos = pro.start
detect_pro = "".join(
["Cleavage:",
str(pro.start), "_", pro.strand])
if pro.start > ta.end:
break
if ta.strand == "-":
if (pro.start >= ta.start) and (pro.start <= ta.end) and (
(end - pro.start) >= args_srna.min_len) and (
(end - pro.start) <= args_srna.max_len):
pro_pos = pro.start
detect_pro = "".join(
["Cleavage:",
str(pro.start), "_", pro.strand])
break
if pro.start > ta.end:
break
new_srna_datas = None
if ta.strand == "+":
if ((type_ == "within") and
(srna_datas["pos"] < pro_pos)) or ((type_ == "longer") and
(pro_pos != -1)):
srna_covers = get_best(wigs, ta.seq_id, ta.strand, start, pro_pos,
"total", args_srna, cutoff)
new_srna_datas = replicate_comparison(args_srna, srna_covers,
ta.strand, "normal", None,
None, None, notex, cutoff,
args_srna.texs)
if new_srna_datas["best"] <= cutoff:
new_srna_datas = None
else:
if ((type_ == "within") and
(srna_datas["pos"] > pro_pos)) or ((type_ == "longer") and
(pro_pos != -1)):
srna_covers = get_best(wigs, ta.seq_id, ta.strand, pro_pos, end,
"total", args_srna, cutoff)
new_srna_datas = replicate_comparison(args_srna, srna_covers,
ta.strand, "normal", None,
None, None, notex, cutoff,
args_srna.texs)
if new_srna_datas["best"] <= cutoff:
new_srna_datas = None
return pro_pos, new_srna_datas, detect_pro
def check_pro(ta, start, end, srna_datas, type_, cutoff,
wigs, notex, args_srna):
'''check the processing site for long non-coding RNA'''
pro_pos = -1
detect_pro = "NA"
for pro in args_srna.pros:
if (pro.seq_id == ta.seq_id) and (
pro.strand == ta.strand):
if ta.strand == "+":
if (pro.start >= ta.start) and (pro.start <= ta.end) and (
(pro.start - start) >= args_srna.min_len) and (
(pro.start - start) <= args_srna.max_len):
pro_pos = pro.start
detect_pro = "".join(["Cleavage:", str(pro.start),
"_", pro.strand])
if pro.start > ta.end:
break
if ta.strand == "-":
if (pro.start >= ta.start) and (pro.start <= ta.end) and (
(end - pro.start) >= args_srna.min_len) and (
(end - pro.start) <= args_srna.max_len):
pro_pos = pro.start
detect_pro = "".join(["Cleavage:", str(pro.start),
"_", pro.strand])
break
if pro.start > ta.end:
break
new_srna_datas = None
if ta.strand == "+":
if ((type_ == "within") and (srna_datas["pos"] < pro_pos)) or (
(type_ == "longer") and (pro_pos != -1)):
srna_covers = get_best(wigs, ta.seq_id, ta.strand, start, pro_pos,
"total", args_srna, cutoff)
new_srna_datas = replicate_comparison(
args_srna, srna_covers, ta.strand, "normal", None, None,
None, notex, cutoff, args_srna.texs)
if new_srna_datas["best"] <= cutoff:
new_srna_datas = None
else:
if ((type_ == "within") and (srna_datas["pos"] > pro_pos) and (
pro_pos != -1)) or (
(type_ == "longer") and (pro_pos != -1)):
srna_covers = get_best(wigs, ta.seq_id, ta.strand, pro_pos, end,
"total", args_srna, cutoff)
new_srna_datas = replicate_comparison(
args_srna, srna_covers, ta.strand, "normal", None, None,
None, notex, cutoff, args_srna.texs)
if new_srna_datas["best"] <= cutoff:
new_srna_datas = None
return pro_pos, new_srna_datas, detect_pro
def detect_wig_pos(wigs, ta, start, end, tss, cutoff, notex, args_srna):
srna_covers = get_best(wigs, ta.seq_id, ta.strand, start, end,
"differential", args_srna, cutoff)
srna_datas = replicate_comparison(args_srna, srna_covers, ta.strand,
"normal", None, None, None, notex,
cutoff, args_srna.texs)
detect, srna_datas, pro = exchange_to_pro(args_srna, srna_datas, ta, start,
end, cutoff, wigs, notex)
if ta.strand == "+":
if detect:
string = ("\t".join([
str(field) for field in [
ta.seq_id, "ANNOgesic", "sRNA",
str(start),
str(srna_datas["pos"]), ".", ta.strand, "."
]
]))
if pro != "NA":
tss = ";".join([tss, pro])
print_file(string, tss, srna_datas, ta.attributes["sRNA_type"],
args_srna)
else:
if detect:
string = ("\t".join([
str(field) for field in [
ta.seq_id, "ANNOgesic", "sRNA",
str(srna_datas["pos"]),
str(end), ".", ta.strand, "."
]
]))
if pro != "NA":
tss = ";".join([tss, pro])
print_file(string, tss, srna_datas, ta.attributes["sRNA_type"],
args_srna)
def detect_wig_pos(wigs, ta, start, end, tss, cutoff, notex, args_srna):
'''searching the coverage decrease'''
srna_covers = get_best(wigs, ta.seq_id, ta.strand, start, end,
"differential", args_srna, cutoff)
srna_datas = replicate_comparison(
args_srna, srna_covers, ta.strand, "normal", None, None,
None, notex, cutoff, args_srna.texs)
detect, srna_datas, pro = exchange_to_pro(args_srna, srna_datas, ta, start,
end, cutoff, wigs, notex)
if ta.strand == "+":
if (detect) and (
(srna_datas["pos"] - start) >= args_srna.min_len) and (
(srna_datas["pos"] - start) <= args_srna.max_len):
string = ("\t".join([str(field) for field in [
ta.seq_id, "ANNOgesic", "ncRNA", str(start),
str(srna_datas["pos"]), ".", ta.strand, "."]]))
if pro != "NA":
tss = ";".join([tss, pro])
print_file(string, tss, srna_datas, ta.attributes["sRNA_type"],
args_srna, ta.seq_id)
else:
if (detect) and (
(end - srna_datas["pos"]) >= args_srna.min_len) and (
(end - srna_datas["pos"]) <= args_srna.max_len):
string = ("\t".join([str(field) for field in [
ta.seq_id, "ANNOgesic", "ncRNA", str(srna_datas["pos"]),
str(end), ".", ta.strand, "."]]))
if pro != "NA":
tss = ";".join([tss, pro])
print_file(string, tss, srna_datas, ta.attributes["sRNA_type"],
args_srna, ta.seq_id)
def detect_srna(median, args_srna):
'''check the sRNA candidates and print it out'''
num = 0
if len(args_srna.srnas) != 0:
for srna in args_srna.srnas:
if srna["strain"] in median.keys():
srna_datas = replicate_comparison(
args_srna, srna["datas"],
srna["strand"], "sRNA_utr_derived",
median[srna["strain"]][srna["utr"]],
args_srna.coverages, srna["utr"], None, None,
args_srna.texs)
if srna_datas["best"] != 0:
if (srna["utr"] == "5utr") or (
srna["utr"] == "interCDS"):
start = srna_datas["start"]
end = srna_datas["end"]
elif srna["utr"] == "3utr":
start = srna["start"]
end = srna["end"]
if (math.fabs(start - end) >= args_srna.min_len) and (
math.fabs(start - end) <= args_srna.max_len):
print_file(num, srna, start, end,
srna_datas, args_srna)
num += 1
def get_coverage(start, end, strain, wigs, strand, ta, tss, cutoff_coverage,
notex, args_srna):
srna_covers = get_best(wigs, strain, strand, start, end, "total",
args_srna, cutoff_coverage)
srna_datas = replicate_comparison(args_srna, srna_covers, strand, "normal",
None, None, None, notex, cutoff_coverage,
args_srna.texs)
string = ("\t".join([str(field) for field in [
ta.seq_id, "ANNOgesic", "ncRNA", str(start),
str(end), ".", ta.strand, "."]]))
if srna_datas["best"] != 0:
print_file(string, tss, srna_datas, ta.attributes["sRNA_type"],
args_srna, strain)
def get_coverage(start, end, strain, wigs, strand, ta, tss, cutoff_coverage,
notex, args_srna):
srna_covers = get_best(wigs, strain, strand, start, end, "total",
args_srna, cutoff_coverage)
srna_datas = replicate_comparison(args_srna, srna_covers, strand, "normal",
None, None, None, notex, cutoff_coverage,
args_srna.texs)
string = ("\t".join([str(field) for field in [
ta.seq_id, "ANNOgesic", "ncRNA", str(start),
str(end), ".", ta.strand, "."]]))
if srna_datas["best"] != 0:
print_file(string, tss, srna_datas, ta.attributes["sRNA_type"],
args_srna)
def coverage_and_output(sorfs, mediandict, wigs, out_g, out_t, file_type,
fasta, coverages, args_sorf, texs, run):
'''get the coverage of sORF and print it out'''
if run == "final":
out_g.write("##gff-version 3\n")
if args_sorf.print_all:
out_t.write("\t".join([
"Genome", "Name", "Start", "End", "Strand", "Type", "TSS",
"Ribosome_binding_site", "All_start_points", "All_stop_points",
"sRNA_conflict", "Frame_shift", "Lib_type",
"Best_avg_coverage", "Best_highest_coverage",
"Best_lowest_coverage", "Track_detail", "Seq", "Combinations"
]) + "\n")
else:
out_t.write("\t".join([
"Genome", "Name", "Start", "End", "Strand", "Type", "TSS",
"Ribosome_binding_site", "All_start_points", "All_stop_points",
"sRNA_conflict", "Frame_shift", "Lib_type",
"Best_avg_coverage", "Best_highest_coverage",
"Best_lowest_coverage", "Track_detail", "Seq"
]) + "\n")
num = 0
final_sorfs = []
for sorf in sorfs:
if ((compare_rbs_start(sorf, args_sorf.min_rbs, args_sorf.max_rbs)) and
(file_type == "best")) or (file_type == "all"):
if file_type == "best":
check_start_end(sorf, args_sorf, fasta, run)
detect_frame_shift(sorf)
cutoffs = {}
if sorf["strand"] == "+":
sorf_covers = get_coverage(sorf, wigs["forward"], "+",
coverages, mediandict, cutoffs)
else:
sorf_covers = get_coverage(sorf, wigs["reverse"], "-",
coverages, mediandict, cutoffs)
if len(sorf_covers) != 0:
sorf_info = replicate_comparison(args_sorf, sorf_covers,
sorf["strand"], "sORF", None,
cutoffs, None, cutoffs, None,
texs)
if len(sorf_info["conds"].keys()) != 0:
if run != "final":
final_sorfs.append(sorf)
else:
print_file(sorf, sorf_info, num, out_g, out_t,
file_type, args_sorf)
num += 1
if run != "final":
return final_sorfs
def coverage_and_output(sorfs, mediandict, wigs, out_g, out_t, file_type,
fasta, coverages, args_sorf, texs, run):
'''get the coverage of sORF and print it out'''
if run == "final":
out_g.write("##gff-version 3\n")
if args_sorf.print_all:
out_t.write("\t".join([
"Genome", "Name", "Start", "End", "Strand", "Type", "TSS",
"Ribosome_binding_site", "All_start_points", "All_stop_points",
"Conflict_sRNA", "Frame_shift", "Lib_type", "Best_avg_coverage",
"Track_detail", "Seq", "Combinations"]) + "\n")
else:
out_t.write("\t".join([
"Genome", "Name", "Start", "End", "Strand", "Type", "TSS",
"Ribosome_binding_site", "All_start_points", "All_stop_points",
"Conflict_sRNA", "Frame_shift", "Lib_type", "Best_avg_coverage",
"Track_detail", "Seq"]) + "\n")
num = 0
final_sorfs = []
for sorf in sorfs:
if ((compare_rbs_start(sorf, args_sorf.min_rbs,
args_sorf.max_rbs)) and (
file_type == "best")) or (
file_type == "all"):
if file_type == "best":
check_start_end(sorf, args_sorf, fasta, run)
detect_frame_shift(sorf)
cutoffs = {}
if sorf["strand"] == "+":
sorf_covers = get_coverage(sorf, wigs["forward"], "+",
coverages, mediandict, cutoffs,
args_sorf.background)
else:
sorf_covers = get_coverage(sorf, wigs["reverse"], "-",
coverages, mediandict, cutoffs,
args_sorf.background)
if len(sorf_covers) != 0:
sorf_info = replicate_comparison(
args_sorf, sorf_covers, sorf["strand"], "sORF", None,
cutoffs, None, cutoffs, None, texs)
if len(sorf_info["conds"].keys()) != 0:
if run != "final":
final_sorfs.append(sorf)
else:
print_file(sorf, sorf_info, num, out_g, out_t, file_type,
args_sorf)
num += 1
if run != "final":
return final_sorfs
def test_replicate_comparison(self):
cover_detect.check_tex = Mock_func().mock_check_tex
template_texs = self.example.texs
srna_covers = {"texnotex": self.example.cover_datas}
coverages = {"3utr": 100, "5utr": 600}
median = {
"track1_tex": {
"median": 100,
"mean": 200
},
"track1_notex": {
"median": 30,
"mean": 80
},
"track2_tex": {
"median": 150,
"mean": 200
},
"track2_notex": {
"median": 10,
"mean": 20
},
"frag": {
"median": 80,
"mean": 100
}
}
texs = {
"track1_tex@AND@track1_notex": 0,
"track2_tex@AND@track2_notex": 0
}
args = self.mock_args.mock()
args.replicates = {"tex": ["all_2"], "frag": ["all_1"]}
args.tex_notex = 2
srna_datas = cover_detect.replicate_comparison(args, srna_covers, "+",
"sRNA_utr_derived",
median, coverages,
"3utr", 100, 200,
template_texs)
self.assertEqual(srna_datas["best"], 500)
self.assertEqual(srna_datas["track"], "frag")
self.assertEqual(srna_datas["high"], 700)
self.assertEqual(srna_datas["low"], 400)
self.assertEqual(srna_datas["start"], 100)
self.assertEqual(srna_datas["end"], 202)
def coverage_and_output(sorfs, mediandict, wigs, out_g, out_t,
file_type, fasta, coverages, args_sorf, texs):
'''get the coverage of sORF and print it out'''
out_g.write("##gff-version 3\n")
if args_sorf.print_all:
out_t.write("\t".join([
"strain", "Name", "start", "end", "strand", "type", "TSS", "RBS",
"all_start_points", "all_stop_pointss", "sRNA_conflict",
"frame_shift", "lib_type", "best_avg_coverage",
"best_highest_coverage", "best_lowest_coverage", "track_detail",
"seq", "combinations"]) + "\n")
else:
out_t.write("\t".join([
"strain", "Name", "start", "end", "strand", "type", "TSS", "RBS",
"all_start_points", "all_stop_points", "sRNA_conflict",
"frame_shift", "lib_type", "best_avg_coverage",
"best_highest_coverage", "best_lowest_coverage",
"track_detail", "seq"]) + "\n")
num = 0
for sorf in sorfs:
if ((compare_rbs_start(sorf, args_sorf.min_rbs,
args_sorf.max_rbs)) and (
file_type == "best")) or (
file_type == "all"):
if file_type == "best":
check_start_end(sorf, args_sorf, fasta)
detect_frame_shift(sorf)
cutoffs = {}
if sorf["strand"] == "+":
sorf_covers = get_coverage(sorf, wigs["forward"], "+",
coverages, mediandict, cutoffs)
else:
sorf_covers = get_coverage(sorf, wigs["reverse"], "-",
coverages, mediandict, cutoffs)
if len(sorf_covers) != 0:
sorf_info = replicate_comparison(
args_sorf, sorf_covers, sorf["strand"], "sORF", None,
cutoffs, None, cutoffs, None, texs)
if len(sorf_info["conds"].keys()) != 0:
print_file(sorf, sorf_info, num, out_g, out_t, file_type,
args_sorf)
num += 1
def coverage_and_output(sorfs, mediandict, wigs, out_g, out_t,
file_type, fasta, coverages, args_sorf, texs):
out_g.write("##gff-version 3\n")
if args_sorf.print_all:
out_t.write("\t".join([
"strain", "Name", "start", "end", "strand", "type", "TSS", "RBS",
"all_start_points", "all_stop_pointss", "sRNA_confliction",
"frame_shift", "lib_type", "best_avg_coverage",
"best_highest_coverage", "best_lowest_coverage", "track_detail",
"seq", "combinations"]) + "\n")
else:
out_t.write("\t".join([
"strain", "Name", "start", "end", "strand", "type", "TSS", "RBS",
"all_start_points", "all_stop_points", "sRNA_confliction",
"frame_shift", "lib_type", "best_avg_coverage",
"best_highest_coverage", "best_lowest_coverage",
"track_detail", "seq"]) + "\n")
num = 0
for sorf in sorfs:
if ((compare_rbs_start(sorf, args_sorf.min_rbs,
args_sorf.max_rbs)) and (
file_type == "best")) or (
file_type == "all"):
if file_type == "best":
check_start_end(sorf, args_sorf, fasta)
detect_frame_shift(sorf)
cutoffs = {}
if sorf["strand"] == "+":
sorf_covers = get_coverage(sorf, wigs["forward"], "+",
coverages, mediandict, cutoffs)
else:
sorf_covers = get_coverage(sorf, wigs["reverse"], "-",
coverages, mediandict, cutoffs)
if len(sorf_covers) != 0:
sorf_info = replicate_comparison(
args_sorf, sorf_covers, sorf["strand"], "sORF", None,
cutoffs, None, cutoffs, None, texs)
if len(sorf_info["conds"].keys()) != 0:
print_file(sorf, sorf_info, num, out_g, out_t, file_type,
args_sorf)
num += 1
def test_replicate_comparison(self):
cover_detect.check_tex = Mock_func().mock_check_tex
template_texs = self.example.texs
srna_covers = {"texnotex": self.example.cover_datas}
coverages = {"3utr": 100, "5utr": 600}
median = {"track1_tex": {"median": 100, "mean": 200}, "track1_notex": {"median": 30, "mean": 80},
"track2_tex": {"median": 150, "mean": 200}, "track2_notex": {"median": 10, "mean": 20},
"frag": {"median": 80, "mean": 100}}
texs = {"track1_tex@AND@track1_notex": 0, "track2_tex@AND@track2_notex": 0}
args = self.mock_args.mock()
args.replicates = {"tex": 2, "frag": 1}
args.tex_notex = 2
srna_datas = cover_detect.replicate_comparison(args, srna_covers, "+",
"sRNA_utr_derived", median,
coverages, "3utr", 100, 200, template_texs)
self.assertEqual(srna_datas["best"], 500)
self.assertEqual(srna_datas["track"], "frag")
self.assertEqual(srna_datas["high"], 700)
self.assertEqual(srna_datas["low"], 400)
self.assertEqual(srna_datas["start"], 100)
self.assertEqual(srna_datas["end"], 202)
def detect_srna(median, args_srna):
num = 0
if len(args_srna.srnas) != 0:
for srna in args_srna.srnas:
if srna["strain"] in median.keys():
srna_datas = replicate_comparison(
args_srna, srna["datas"], srna["strand"],
"sRNA_utr_derived", median[srna["strain"]][srna["utr"]],
args_srna.coverages, srna["utr"], None, None,
args_srna.texs)
if srna_datas["best"] != 0:
if (srna["utr"] == "5utr") or (srna["utr"] == "interCDS"):
start = srna_datas["start"]
end = srna_datas["end"]
elif srna["utr"] == "3utr":
start = srna["start"]
end = srna["end"]
if (math.fabs(start - end) >= args_srna.min_len) and (
math.fabs(start - end) <= args_srna.max_len):
print_file(num, srna, start, end, srna_datas,
args_srna)
num += 1
