File size: 16,354 Bytes
fe41391 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 |
#!/usr/bin/python
#####################################################################################
# rust_nucleotide, Produces RUST metagene profile of nucleotides
# Copyright (C) 2015 Patrick O'Connor
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <https://www.gnu.org/licenses/>.
#####################################################################################
import os, re, pysam, sys, math, argparse
from RUST.methods import *
try:
import matplotlib as mpl
mpl.use("Agg")
import matplotlib.pyplot as plt
from pylab import MaxNLocator
except:
pass
def RUST_metagene_plot(infileopen36, ax36):
infileopen36.seek(0)
infileopen36.readline()
while 1:
line = infileopen36.readline()
linesplit = line.split(",")
if len(linesplit) == 1:
break
nucleotide_type = linesplit[0]
coverage = list(map(float, linesplit[1:]))
coverage_a = coverage[0]
if coverage_a == 0:
continue
coverage_n = [n / coverage_a for n in coverage[1:]]
# ax36.plot(log2(coverage_n[:-2]),color = "gray")
log2_values = [math.log(n, 2) for n in coverage_n]
if nucleotide_type == "A":
ax36.plot(log2_values, color="firebrick", label=nucleotide_type)
elif nucleotide_type == "T":
ax36.plot(log2_values, color="seagreen", label=nucleotide_type)
elif nucleotide_type == "G":
ax36.plot(log2_values, color="Orange", label=nucleotide_type)
else:
ax36.plot(log2_values, color="MediumPurple", label=nucleotide_type)
line = infileopen36.readline()
linesplit = line.split(",")
if "NA" not in linesplit:
coverage = list(map(float, linesplit[2:]))
ax2 = ax36.twinx()
ax2.plot(coverage, color="blue")
for tl in ax2.get_yticklabels():
tl.set_color("blue")
tl.set_rotation(0)
ax2.yaxis.set_major_locator(MaxNLocator(3))
ax2.set_ylim(0, 1.0)
ax2.set_ylim(-2, 1.0)
ax2.set_yticks([0, 1], minor=False)
ax2.set_yticklabels(["0", "1"])
ax2.set_ylabel("Kullback-Leibler divergence", color="blue")
ax36.set_xticks([15, 30, 45, 60, 75, 90, 105, 120, 135, 150, 165])
ax36.set_xticklabels([-105, -90, -75, -60, -45, -30, -15, 0, 15, 30, 45])
ax36.set_xlabel("distance from A-site [codon]")
ax36.set_ylabel("Nucleotide RUST ratio (observed/expected), log2")
ax36.axvline(120, color="red")
ax36.legend(bbox_to_anchor=(0, 0, 0.2, 0.9))
def main(args):
mRNA_sequences = args.transcriptome # path to fastq file of transcripts
in_seq_handle = open(mRNA_sequences)
cds_start_dict = {}
cds_end_dict = {}
seq_dict = {}
for line in in_seq_handle:
if line[0] != ">":
seq_dict.setdefault(transcript, "")
seq_dict[transcript] += line[:-1]
continue
try:
transcript_split = line[:-1].split("\t")
transcript = transcript_split[0][1:]
cds_start_dict[transcript] = int(transcript_split[1])
cds_end_dict[transcript] = int(transcript_split[2])
except:
pass
in_seq_handle.close()
offset = args.offset
readlen_range = args.lengths
readlen_rangesplit = readlen_range.split(":")
if len(readlen_rangesplit) == 1:
accepted_read_lengths = [int(readlen_rangesplit[0])]
length_values = "%s" % int(readlen_rangesplit[0])
elif len(readlen_rangesplit) == 2:
accepted_read_lengths = [
readlen
for readlen in range(
int(readlen_rangesplit[0]), int(readlen_rangesplit[1]) + 1
)
]
length_values = "%s_%s" % (
int(readlen_rangesplit[0]),
int(readlen_rangesplit[1]),
)
else:
stop_err(
"Lengths of footprints parameter not in correct format, it should be either colon seperated with the second value greater or equal to the first, (28:32) or a single interger (31)"
)
if len(accepted_read_lengths) == 0:
stop_err(
"Lengths of footprints parameter not in correct format, it should be either colon seperated with the second value greater or equal to the first, (28:32) or a single interger (31)"
)
nts = ["A", "G", "C", "T"]
aligments_A1 = pysam.Samfile(args.alignment, "rb")
nucleotide_enrichment_dict = {}
nucleotide_enrichment_expected_dict = {}
for nt in nts:
nucleotide_enrichment_dict[nt] = {}
nucleotide_enrichment_expected_dict[nt] = []
for number in range(0, 180, 1):
nucleotide_enrichment_dict[nt][number] = [0.0, 0.0]
list_transcripts = seq_dict.keys()
number_transcripts = 0
list_10_percentile = []
for value in range(1, 10):
list_10_percentile.append((len(list_transcripts) * value) / 10)
for transcript in list_transcripts:
number_transcripts += 1
if number_transcripts in list_10_percentile:
sys.stdout.write(
"%s percent\n"
% ((list_10_percentile.index(number_transcripts) + 1) * 10)
)
try: # use supplied CDS annotation
cds_start = cds_start_dict[transcript]
cds_end = cds_end_dict[transcript]
if cds_end < cds_start:
raise Exception
except Exception: # find longest ORF
transcript_seq = seq_dict[transcript]
cds_start = -1
start_post = []
end_post = []
for match in re.finditer(r"(?=(%s))" % re.escape("ATG"), transcript_seq):
start_post.append(match.start())
for match in re.finditer(r"(?=(%s))" % re.escape("TAG"), transcript_seq):
end_post.append(match.start())
for match in re.finditer(r"(?=(%s))" % re.escape("TAA"), transcript_seq):
end_post.append(match.start())
for match in re.finditer(r"(?=(%s))" % re.escape("TGA"), transcript_seq):
end_post.append(match.start())
end_post.sort()
len_max_orf = 0
for value in start_post:
for value2 in end_post:
if value < value2:
if value % 3 == value2 % 3:
len_orf = value2 - value
if len_orf > len_max_orf:
cds_start = value
cds_end = value2 + 3
len_max_orf = len_orf
break
if cds_start == -1:
# sys.stdout.write( '%s, AUG codon not found\n'%transcript )
continue
elongation_region_all = seq_dict[transcript][cds_start:cds_end]
elongation_region_part = elongation_region_all[
120:-60
] # first 120 and last 60 nt are not used
# peptide_sequence = elongation_region_all.translate()
if len(elongation_region_part) % 3 != 0:
# sys.stdout.write( '%s, CDS not divisible by 3\n'%transcript )
continue
profile_list = [
0.0 for n in range(cds_start + 120, cds_end - 60)
] # records ribo-seq profile
if len(profile_list) < 50:
# sys.stdout.write( '%s, ORF too short\n'%transcript )
continue
all_reads = aligments_A1.fetch(transcript)
len_elongation_region = len(profile_list)
for read in all_reads:
readlen = read.qlen
if readlen not in accepted_read_lengths:
continue # selection of read of acceptable length
A_site = read.pos + offset - cds_start - 120 # addition of offset
if len_elongation_region > A_site > -1:
profile_list[A_site] += 1
average_gene_density = float(sum(profile_list)) / len(profile_list)
if average_gene_density != 0:
num_codon = len(
[
1
for number88 in range(0, len(profile_list), 3)
if (
(
profile_list[number88]
+ profile_list[number88 + 1]
+ profile_list[number88 + 2]
)
/ 3
)
> average_gene_density
]
)
# number of codons that exceed average gene density
expected_codon_density = float(num_codon) / (len(profile_list) / 3)
codon_start = 0
for sliding_w_n in range(
0, len(elongation_region_part), 3
): # sliding window using increments of 3 nts
codon_window = str(
elongation_region_all[codon_start : codon_start + 180]
)
if len(set(codon_window) - set(["A", "T", "G", "C"])) != 0:
codon_start += 3
continue
if (
profile_list[sliding_w_n]
+ profile_list[sliding_w_n + 1]
+ profile_list[sliding_w_n + 2]
) / 3 > average_gene_density:
for number in range(0, 180):
nucleotide3 = codon_window[number]
nucleotide_enrichment_dict[nucleotide3][number][0] += 1
nucleotide_enrichment_dict[nucleotide3][number][1] += 1
else:
for number in range(0, 180):
nucleotide3 = codon_window[number]
nucleotide_enrichment_dict[nucleotide3][number][0] += 1
nucleotide3 = codon_window[120:121]
nucleotide_enrichment_expected_dict[nucleotide3].append(
expected_codon_density
)
nucleotide3 = codon_window[121:122]
nucleotide_enrichment_expected_dict[nucleotide3].append(
expected_codon_density
)
nucleotide3 = codon_window[122:123]
nucleotide_enrichment_expected_dict[nucleotide3].append(
expected_codon_density
)
codon_start += 3
if not os.path.exists(args.Path):
os.mkdir(args.Path)
alignment_filename = args.alignment.split("/")[-1]
outfile = open(
"%s/RUST_nucleotide_file_%s_%s_%s"
% (args.Path, alignment_filename, args.offset, length_values),
"w",
)
outfile.write("nucleotide, expected value")
for number106 in range(-120, 60):
outfile.write(", %s" % number106)
outfile.write("\n")
list_nucleotide2 = []
nucleotides = list(nucleotide_enrichment_expected_dict.keys())
nucleotides.sort()
rust_expected = []
rust_observed_metafootprint = []
for nucleotide2 in nucleotides:
if nucleotide2 in list_nucleotide2:
continue
list_nucleotide2.append(nucleotide2)
outfile.write("%s" % nucleotide2)
outfile.write(
", %s" % mean_value(nucleotide_enrichment_expected_dict[nucleotide2])
)
list_data = []
for number in range(0, 180):
if nucleotide_enrichment_dict[nucleotide2][number][0] != 0:
outfile.write(
", %s"
% (
nucleotide_enrichment_dict[nucleotide2][number][1]
/ nucleotide_enrichment_dict[nucleotide2][number][0]
)
)
list_data.append(
nucleotide_enrichment_dict[nucleotide2][number][1]
/ nucleotide_enrichment_dict[nucleotide2][number][0]
)
else:
outfile.write(", 0")
list_data.append(0)
rust_expected.append(
mean_value(nucleotide_enrichment_expected_dict[nucleotide2])
)
rust_observed_metafootprint.append(list_data)
outfile.write("\n")
rust_expected_sum = sum(rust_expected)
q_values = [n / rust_expected_sum for n in rust_expected]
shannon_values = []
for loc_i in range(180):
rust_observed = [n[loc_i] for n in rust_observed_metafootprint]
rust_observed_sum = sum(rust_observed)
rust_observed_min = min(rust_observed)
if rust_observed_min == 0:
shannon_values.append("NA")
else:
p_values = [n / rust_observed_sum for n in rust_observed]
shannon = []
list_normalised = [] ####
for p_value, q_value in zip(p_values, q_values):
shannon.append(abs(p_value * math.log((p_value / q_value), 2)))
list_normalised.append(p_value / q_value) ####
shannon_values.append(sum(shannon))
outfile.write("\nKullback Leibler divergence,")
for value in shannon_values:
outfile.write(", %s" % value)
outfile.close()
try:
mpl.rcParams["xtick.direction"] = "out"
mpl.rcParams["ytick.direction"] = "out"
mpl.rcParams["legend.fontsize"] = 10
mpl.rcParams["ytick.labelsize"] = 10
mpl.rcParams["xtick.labelsize"] = 10
mpl.rcParams["font.size"] = 10
mpl.rcParams["axes.titlesize"] = 10
mpl.rcParams["legend.frameon"] = 0
mpl.rcParams["axes.axisbelow"] = False
mpl.rcParams["xtick.major.pad"] = 2.0
mpl.rcParams["ytick.major.pad"] = 2
mpl.rcParams["xtick.major.size"] = 2.0
mpl.rcParams["ytick.major.size"] = 2
mpl.rcParams["axes.linewidth"] = 0.5
mpl.rcParams["ytick.major.width"] = 0.25
mpl.rcParams["xtick.major.width"] = 0.25
mpl.rcParams["lines.linewidth"] = 1
mpl.rcParams["legend.borderpad"] = 0.01
mpl.rcParams["legend.labelspacing"] = 0.05
mpl.rcParams["legend.columnspacing"] = 0.5
mpl.rcParams["legend.borderaxespad"] = 0.15
mpl.rcParams["legend.handlelength"] = 1
fig = plt.figure(figsize=(6.69, 6.0))
infileopen = open(
"%s/RUST_nucleotide_file_%s_%s_%s"
% (args.Path, alignment_filename, args.offset, length_values)
)
ax1_metafootprint = fig.add_subplot(111)
RUST_metagene_plot(infileopen, ax1_metafootprint)
plt.savefig(
"%s/RUST_nucleotide_metafootprint_%s_%s_%s.png"
% (args.Path, alignment_filename, args.offset, length_values)
)
except:
sys.stdout.write("Error producing images\n")
if __name__ == "__main__":
parser = argparse.ArgumentParser(
description="Produces RUST metagene profile of nucleotides"
)
parser.add_argument(
"-t",
"--transcriptome",
help="fasta file of transcripts, CDS start and end may be provided on description line using tab separation e.g. >NM_0001 10 5000, otherwise it searches for longest ORF"
", required=True",
)
parser.add_argument(
"-a",
"--alignment",
help="sorted bam file of transcriptome alignments",
required=True,
)
parser.add_argument("-o", "--offset", help="nucleotide offset to A-site", type=int)
parser.add_argument(
"-l",
"--lengths",
help="lengths of footprints included, for example 28:32 is 28,29,30,31,32",
)
parser.add_argument(
"-P",
"--Path",
help='path to outputfile, default is "nucleotide"',
default="nucleotide",
)
parser.add_argument("--version", action="version", version="%(prog)s 1.2")
args = parser.parse_args(None)
main(args)
|