Newer
Older
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
#!/bin/bash
python3 -m src.bed_handler
python3 -m src.bed_handler.filter_bed \
--bed_file data/bed/gene.bed \
--filter_file data/gene_5-3_loop_tot.txt \
--col_name 'id' \
--outfile gene_with_5-3p_loop_tot.txt
python3 -m src.bed_handler.filter_bed \
--bed_file data/bed/gene.bed \
--filter_file data/gene_5-3_loop_ctrl.txt \
--col_name 'id' \
--outfile gene_with_5-3p_loop_ctrl.txt
python3 -m src.bed_handler.filter_bed \
--bed_file data/bed/gene.bed \
--filter_file data/gene_5-3_loop_siPPdown.txt \
--col_name 'id' \
--outfile gene_with_5-3p_loop_siPPdown.txt
python3 -m src.bed_handler.filter_bed \
--bed_file data/bed/gene.bed \
--filter_file data/gene_without_5-3_loop_siPPdown.txt \
--col_name 'id' \
--outfile gene_without_5-3p_loop_siPPdown.txt
python3 -m src.bed_handler.filter_bed \
--bed_file data/bed/gene.bed \
--filter_file data/gene_without_loops_siPPdown.txt \
--col_name 'id' \
--outfile gene_without_loops_siPPdown.txt
mkdir results/figures
array=(all_replicates rep1 rep2 rep3)
for myrep in ${array[*]}; do
python3 -m src.visu \
--design data/design_exp_${myrep}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/filtered_gene.bed \
--region_name gene \
--output results/figures/ \
--border_name TSS TTS \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm 'None'
python3 -m src.visu \
--design data/design_exp_${myrep}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/filtered_gene.bed \
--region_name gene \
--output results/figures/ \
--border_name TSS TTS \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm '0'
mv results/figures/metagene_gene_100bin_10000_nt-around-25-bin_b0_norm.pdf results/figures/metagene_gene_100bin_10000_nt-around-25-bin_b0_norm_${myrep}.pdf
mv results/figures/metagene_gene_100bin_10000_nt-around-25-bin.pdf results/figures/metagene_gene_100bin_10000_nt-around-25-bin_${myrep}.pdf
done
array=(all_replicates rep1 rep2 rep3)
for myrep in ${array[*]}; do
python3 -m src.visu \
--design data/design_exp_${myrep}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/gene_with_5-3p_loop_siPPdown.txt \
--region_name gene \
--output results/figures/ \
--border_name TSS TTS \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm 'None'
python3 -m src.visu \
--design data/design_exp_${myrep}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/gene_with_5-3p_loop_siPPdown.txt \
--region_name gene \
--output results/figures/ \
--border_name TSS TTS \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm '0'
mv results/figures/metagene_gene_100bin_10000_nt-around-25-bin_b0_norm.pdf results/figures/metagene_gene_100bin_10000_nt-around-25-bin_b0_norm_${myrep}_5-3-loop.pdf
mv results/figures/metagene_gene_100bin_10000_nt-around-25-bin.pdf results/figures/metagene_gene_100bin_10000_nt-around-25-bin_${myrep}_5-3-loop.pdf
done
for gene_bed in $(ls results/bed_file/CTCF*gene.bed); do
exon_bed=${gene_bed/gene/exon}
exon_name=(${exon_bed//\// })
full_name=${exon_name[-1]/.bed/}
full_name=${full_name/exon/gene-dup}
file_name=${exon_name[-1]/.bed/}
gene_bed=${gene_bed/.bed/-dup.bed}
python3 -m src.visu \
--design data/design_exp_all_replicates.txt \
--bw_folder data/bigwig/ \
--region_bed ${exon_bed} \
--region_name exon \
--output results/figures/ \
--border_name start_exon end_exon \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm 'None'
mv results/figures/metagene_exon_100bin_10000_nt-around-25-bin.pdf results/figures/${file_name}_metagene_exon_100bin_10000_nt-around-25-bin.pdf
python3 -m src.visu \
--design data/design_exp_all_replicates.txt \
--bw_folder data/bigwig/ \
--region_bed ${gene_bed} \
--region_name gene \
--output results/figures/ \
--border_name start_exon end_exon \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm '0'
rm results/figures/metagene_gene_100bin_10000_nt-around-25-bin_b0_norm.pdf
python3 -m src.visu \
--design data/design_exp_all_replicates.txt \
--bw_folder data/bigwig/ \
--region_bed ${exon_bed} \
--region_name exon \
--output results/figures/ \
--border_name start_exon end_exon \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "results/figures/coef_table/tmp_cov_table_design_exp_all_replicates_${full_name}_100bin_10000_nt-around-25-bin_bin0_norm.txt"
mv results/figures/metagene_exon_100bin_10000_nt-around-25-bin_file_norm.pdf results/figures/${file_name}_metagene_exon_100bin_10000_nt-around-25-bin_file_norm.pdf
done
########################################################
# Condition siPP/siCTRL - exon ddx_down vs exon ddx_down_ctcf #
########################################################
# exon ddx_down_ctcf corresponds to exons down-regulated by ddx5/17 near a ctcf site and
# exon ddx_down corresponds to exons down-regulated by ddx5/17 far from ctcf sites
exps=(siCTRL siDDX)
for exp in ${exps[*]}; do
python3 -m src.visu \
--design data/design_exp_${exp}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/CTCF_2000_both_ddx_down_with0_gene.bed results/bed_file/Far_CTCF_2000_both_ddx_down_with0_gene.bed \
--region_name ddx_down_ctcf ddx_down \
--output results/figures/ \
--border_name start_gene end_gene \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "None"
mv results/figures/metagene_ddx_down_ctcf-ddx_down_100bin_10000_nt-around-25-bin.pdf results/figures/exp_${exp}_metagene_ddx_down_ctcf-ddx_down_100bin_10000_nt-around-25-bin_gene.pdf
python3 -m src.visu \
--design data/design_exp_${exp}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/CTCF_2000_both_ddx_down_with0_gene.bed results/bed_file/Far_CTCF_2000_both_ddx_down_with0_gene.bed \
--region_name ddx_down_ctcf ddx_down \
--output results/figures/ \
--border_name start_gene end_gene \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "0"
mv results/figures/metagene_ddx_down_ctcf-ddx_down_100bin_10000_nt-around-25-bin_b0_norm.pdf results/figures/exp_${exp}_metagene_ddx_down_ctcf-ddx_down_100bin_10000_nt-around-25-bin_b0_norm_gene.pdf
python3 -m src.visu \
--design data/design_exp_${exp}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/CTCF_2000_both_ddx_down_with0_gene-dup.bed results/bed_file/Far_CTCF_2000_both_ddx_down_with0_gene-dup.bed \
--region_name ddx_down_ctcf ddx_down \
--output results/figures/ \
--border_name start_gene end_gene \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "0"
rm results/figures/metagene_ddx_down_ctcf-ddx_down_100bin_10000_nt-around-25-bin_b0_norm.pdf
python3 -m src.visu \
--design data/design_exp_${exp}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/CTCF_2000_both_ddx_down_with0_exon.bed results/bed_file/Far_CTCF_2000_both_ddx_down_with0_exon.bed \
--region_name ddx_down_ctcf ddx_down \
--output results/figures/ \
--border_name start_exon end_exon \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "results/figures/coef_table/tmp_cov_table_design_exp_${exp}_CTCF_2000_both_ddx_down_with0_gene-dup-Far_CTCF_2000_both_ddx_down_with0_gene-dup_100bin_10000_nt-around-25-bin_bin0_norm.txt"
mv results/figures/metagene_ddx_down_ctcf-ddx_down_100bin_10000_nt-around-25-bin_file_norm.pdf results/figures/exp_${exp}_metagene_ddx_down_ctcf-ddx_down_100bin_10000_nt-around-25-bin_file_norm_exon.pdf
done
########################################################
# Condition siPP and siCTRL - ddx_down_5-3 #
########################################################
python3 -m src.visu \
--design data/design_exp_all_replicates.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/gene_with_5-3p_loop_siPPdown.txt \
--region_name ddx_down_5-3 \
--output results/figures/ \
--border_name start_gene end_gene \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "0"
mv results/figures/metagene_ddx_down_5-3_100bin_10000_nt-around-25-bin_b0_norm.pdf results/figures/exp_all_metagene_ddx_down_5-3_100bin_10000_nt-around-25-bin_b0_norm_gene.pdf
########################################################
# Condition siPP - ddx_down_5-3 vs exon ddx_down #
########################################################
# gene ddx_down_5-3 corresponds to genes containing at least one exons down-regulated by ddx5/17 and having a 5'-3' loop and
# gene ddx_down corresponds to genes containing exons down-regulated by ddx but without a 5'-3' loop
python3 -m src.visu \
--design data/design_exp_siDDX.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/gene_with_5-3p_loop_siPPdown.txt results/bed_file/gene_without_loops_siPPdown.txt \
--region_name ddx_down_5-3 ddx_down \
--output results/figures/ \
--border_name start_gene end_gene \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "0"
mv results/figures/metagene_ddx_down_5-3-ddx_down_100bin_10000_nt-around-25-bin_b0_norm.pdf results/figures/exp_siPP_metagene_ddx_down_5-3-ddx_down_100bin_10000_nt-around-25-bin_b0_norm_gene.pdf
python3 -m src.visu \
--design data/design_exp_siDDX.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/gene_with_5-3p_loop_siPPdown.txt results/bed_file/gene_without_loops_siPPdown.txt \
--region_name ddx_down_5-3 ddx_down \
--output results/figures/ \
--border_name start_gene end_gene \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "None"
mv results/figures/metagene_ddx_down_5-3-ddx_down_100bin_10000_nt-around-25-bin.pdf results/figures/exp_siPP_metagene_ddx_down_5-3-ddx_down_100bin_10000_nt-around-25-bin_gene.pdf
rep=(1 2 3)
for i in ${rep[*]}; do
python3 -m src.visu \
--design data/design_exp_siDDX_rep${i}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/gene_with_5-3p_loop_siPPdown.txt results/bed_file/gene_without_loops_siPPdown.txt \
--region_name ddx_down_5-3 ddx_down \
--output results/figures/ \
--border_name start_gene end_gene \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "0"
mv results/figures/metagene_ddx_down_5-3-ddx_down_100bin_10000_nt-around-25-bin_b0_norm.pdf results/figures/exp_siPP_rep${i}_metagene_ddx_down_5-3-ddx_down_100bin_10000_nt-around-25-bin_b0_normgene.pdf
done
########################################################
# Condition siCTRL - ddx_down_5-3 vs exon ddx_down #
########################################################
# gene ddx_down_5-3 corresponds to genes containing at least one exons down-regulated by ddx5/17 and having a 5'-3' loop and
# gene ddx_down corresponds to genes containing exons down-regulated by ddx but without a 5'-3' loop
python3 -m src.visu \
--design data/design_exp_siCTRL.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/gene_with_5-3p_loop_siPPdown.txt results/bed_file/gene_without_loops_siPPdown.txt \
--region_name ddx_down_5-3 ddx_down \
--output results/figures/ \
--border_name start_gene end_gene \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "0"
mv results/figures/metagene_ddx_down_5-3-ddx_down_100bin_10000_nt-around-25-bin_b0_norm.pdf results/figures/exp_siCTRL_metagene_ddx_down_5-3-ddx_down_100bin_10000_nt-around-25-bin_b0_norm_gene.pdf
python3 -m src.visu \
--design data/design_exp_siCTRL.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/gene_with_5-3p_loop_siPPdown.txt results/bed_file/gene_without_loops_siPPdown.txt \
--region_name ddx_down_5-3 ddx_down \
--output results/figures/ \
--border_name start_gene end_gene \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "None"
mv results/figures/metagene_ddx_down_5-3-ddx_down_100bin_10000_nt-around-25-bin.pdf results/figures/exp_siCTRL_metagene_ddx_down_5-3-ddx_down_100bin_10000_nt-around-25-bin_gene.pdf
rep=(1 2 3)
for i in ${rep[*]}; do
python3 -m src.visu \
--design data/design_exp_siCTRL_rep${i}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/gene_with_5-3p_loop_siPPdown.txt results/bed_file/gene_without_loops_siPPdown.txt \
--region_name ddx_down_5-3 ddx_down \
--output results/figures/ \
--border_name start_gene end_gene \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "0"
mv results/figures/metagene_ddx_down_5-3-ddx_down_100bin_10000_nt-around-25-bin_b0_norm.pdf results/figures/exp_siCTRL_rep${i}_metagene_ddx_down_5-3-ddx_down_100bin_10000_nt-around-25-bin_b0_norm_gene.pdf
done
############################################################
# GC content exon ddx_down vs exon ddx_down_ctcf #
############################################################
python3 -m src.gc_content -B results/bed_file/Far_CTCF_2000_both_ddx_down_with0_exon.bed results/bed_file/CTCF_2000_both_ddx_down_with0_exon.bed -b ddx_down ddx_down_ctcf -g data/Homo_sapiens.GRCh37.dna.primary_assembly.fa -f "exons" -e 2000
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
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
############################################################################
# other Exon in genes containing an exon regulated by DDX
############################################################################
########################################################
# Condition siCTRL - exon ddx_down vs exon ddx_down_ctcf #
########################################################
python3 -m src.bed_handler.get_other_exon_in_same_gene -b results/bed_file/CTCF_2000_both_ddx_down_with0_exon.bed -d 2000 -o oexon_2000_CTCF_2000_both_ddx_down_with0_exon.bed
python3 -m src.bed_handler.get_other_exon_in_same_gene -b results/bed_file/Far_CTCF_2000_both_ddx_down_with0_exon.bed -d 2000 -o oexon_2000_Far_CTCF_2000_both_ddx_down_with0_exon.bed
exps=(siCTRL siDDX)
for exp in ${exps[*]}; do
python3 -m src.visu \
--design data/design_exp_${exp}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/oexon_2000_CTCF_2000_both_ddx_down_with0_gene.bed results/bed_file/oexon_2000_Far_CTCF_2000_both_ddx_down_with0_gene.bed \
--region_name other_ddx_down_ctcf other_ddx_down \
--output results/figures/ \
--border_name start_gene end_gene \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "None"
mv results/figures/metagene_other_ddx_down_ctcf-other_ddx_down_100bin_10000_nt-around-25-bin.pdf results/figures/exp_${exp}_metagene_other_ddx_down_ctcf-other_ddx_down_100bin_10000_nt-around-25-bin_gene.pdf
python3 -m src.visu \
--design data/design_exp_${exp}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/oexon_2000_CTCF_2000_both_ddx_down_with0_gene.bed results/bed_file/oexon_2000_Far_CTCF_2000_both_ddx_down_with0_gene.bed \
--region_name other_ddx_down_ctcf other_ddx_down \
--output results/figures/ \
--border_name start_gene end_gene \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "0"
mv results/figures/metagene_other_ddx_down_ctcf-other_ddx_down_100bin_10000_nt-around-25-bin_b0_norm.pdf results/figures/exp_${exp}_metagene_other_ddx_down_ctcf-other_ddx_down_100bin_10000_nt-around-25-bin_gene_b0_norm.pdf
python3 -m src.visu \
--design data/design_exp_${exp}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/oexon_2000_CTCF_2000_both_ddx_down_with0_gene-dup.bed results/bed_file/oexon_2000_Far_CTCF_2000_both_ddx_down_with0_gene-dup.bed \
--region_name other_ddx_down_ctcf other_ddx_down \
--output results/figures/ \
--border_name start_gene end_gene \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "0"
rm results/figures/metagene_other_ddx_down_ctcf-other_ddx_down_100bin_10000_nt-around-25-bin_b0_norm.pdf
python3 -m src.visu \
--design data/design_exp_${exp}.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/oexon_2000_CTCF_2000_both_ddx_down_with0_exon.bed results/bed_file/oexon_2000_Far_CTCF_2000_both_ddx_down_with0_exon.bed \
--region_name other_ddx_down_ctcf other_ddx_down \
--output results/figures/ \
--border_name start_exon end_exon \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm "results/figures/coef_table/tmp_cov_table_design_exp_${exp}_oexon_2000_CTCF_2000_both_ddx_down_with0_gene-gene-dup-oexon_2000_Far_CTCF_2000_both_ddx_down_with0_exon-gene-dup_100bin_10000_nt-around-25-bin_bin0_norm.txt"
mv results/figures/metagene_other_ddx_down_ctcf-other_ddx_down_100bin_10000_nt-around-25-bin_file_norm.pdf results/figures/exp_${exp}_metagene_other_ddx_down_ctcf-other_ddx_down_100bin_10000_nt-around-25-bin_file_norm_exon.pdf
done
###########################################################
# Figures siPP vs siCTRL pour ddx_down_ctcf,
# other_ddx_down_ctcf, ddx_down
###########################################################
list_names=(ddx_down_ctcf other_ddx_down_ctcf ddx_down)
bed_names=(CTCF_2000_both_ddx_down_with0_exon.bed oexon_2000_CTCF_2000_both_ddx_down_with0_exon.bed Far_CTCF_2000_both_ddx_down_with0_exon.bed)
for i in ${!list_names[*]}; do
cname=${list_names[i]}
bed=${bed_names[i]}
gbed=${bed/exon\.bed/gene-dup.bed}
nbed=${gbed/\.bed/}
python3 -m src.visu \
--design data/design_exp_all_replicates.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/${gbed} \
--region_name ${cname} \
--output results/figures/ \
--border_name TSS TTS \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm '0'
rm results/figures/metagene_${cname}_100bin_10000_nt-around-25-bin_b0_norm.pdf
python3 -m src.visu \
--design data/design_exp_all_replicates.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/${bed} \
--region_name ${cname} \
--output results/figures/ \
nfontrod
committed
--border_name " " " " \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
nfontrod
committed
--nb_bin 30 \
-y 0.15 0.4 \
--norm "results/figures/coef_table/tmp_cov_table_design_exp_all_replicates_${nbed}_100bin_10000_nt-around-25-bin_bin0_norm.txt"
nfontrod
committed
mv results/figures/metagene_${cname}_30bin_10000_nt-around-25-bin_file_norm.pdf results/figures/all_replicates_metagene_${cname}_100bin_10000_nt-around-25-bin_file_norm.pdf
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
done
## Recap
python3 -m src.visu \
--design data/design_exp_all_replicates.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/CTCF_2000_both_ddx_down_with0_gene-dup.bed results/bed_file/oexon_2000_CTCF_2000_both_ddx_down_with0_gene-dup.bed results/bed_file/Far_CTCF_2000_both_ddx_down_with0_gene-dup.bed \
--region_name ddx_down_ctcf other_ddx_down_ctcf ddx_down \
--output results/figures/ \
--border_name TSS TTS \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm '0'
rm results/figures/metagene_ddx_down_ctcf-other_ddx_down_ctcf-ddx_down_100bin_10000_nt-around-25-bin_b0_norm.pdf
python3 -m src.visu \
--design data/design_exp_all_replicates.txt \
--bw_folder data/bigwig/ \
--region_bed results/bed_file/CTCF_2000_both_ddx_down_with0_exon.bed results/bed_file/oexon_2000_CTCF_2000_both_ddx_down_with0_exon.bed results/bed_file/Far_CTCF_2000_both_ddx_down_with0_exon.bed \
--region_name ddx_down_ctcf other_ddx_down_ctcf ddx_down \
--output results/figures/ \
--border_name exon_start exon_stop \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm 'results/figures/coef_table/tmp_cov_table_design_exp_all_replicates_CTCF_2000_both_ddx_down_with0_gene-dup-oexon_2000_CTCF_2000_both_ddx_down_with0_gene-dup-Far_CTCF_2000_both_ddx_down_with0_gene-dup_100bin_10000_nt-around-25-bin_bin0_norm.txt'
mv results/figures/metagene_ddx_down_ctcf-other_ddx_down_ctcf-ddx_down_100bin_10000_nt-around-25-bin_file_norm.pdf results/figures/all_replicates_metagene_ddx_down_ctcf-other_ddx_down_ctcf-ddx_down_100bin_10000_nt-around-25-bin_file_norm.pdf
###############################################################################
# Bigwig from MCF7 rnaseq
###############################################################################
# Create a bed file containing all gene containing one DDX-down exons
echo -e "#ref\tstart\tend\tid\tscore\tstrand" > results/bed_file/ddx_down_gene.bed
cat results/bed_file/CTCF_2000_both_ddx_down_with0_gene.bed \
results/bed_file/Far_CTCF_2000_both_ddx_down_with0_gene.bed | \
sort -u | \
grep -v "#ref" >> results/bed_file/ddx_down_gene.bed
# Zoom on the 1500 pb at the beginning of the exons.
python3 -m src.bed_handler.bed_resize \
-b results/bed_file/ddx_down_gene.bed \
-s 1500 \
-o ddx_down_gene_size1500.bed
python3 -m src.visu \
--design data/bam_mcf7_rnaseq/design_exp_all_replicates.txt \
--bw_folder data/bam_mcf7_rnaseq \
--region_bed results/bed_file/ddx_down_gene.bed \
--region_name all_ddx_down \
--output results/figures/ \
--border_name TSS TTS \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm 'None'
mv results/figures/metagene_all_ddx_down_100bin_10000_nt-around-25-bin.pdf results/figures/metagene_MCF_rnaseq_all_ddx_down.pdf
python3 -m src.visu \
--design data/bam_mcf7_rnaseq/design_exp_all_replicates.txt \
--bw_folder data/bam_mcf7_rnaseq \
--region_bed results/bed_file/ddx_down_gene_size1500.bed \
--region_name all_ddx_down \
--output results/figures/ \
--border_name TSS TSS_1.5kb \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm 'None'
mv results/figures/metagene_all_ddx_down_100bin_10000_nt-around-25-bin.pdf results/figures/metagene_MCF_rnaseq_all_ddx_down_tss1.5kb.pdf
#### Readthrough
# Create readthrough bed files
python3 -m src.bed_handler.filter_bed -b data/bed/gene.bed -f data/readthrough_gene.txt -c score -o readthrough_gene.bed
python3 -m src.bed_handler.filter_bed -b data/bed/gene.bed -f data/readthrough_gene.txt -c score -o no_readthrough_gene.bed -k 'n'
nfontrod
committed
# Filtering only expressed genes with basemean > 5.
python3 -m src.bed_handler.filter_bed -b results/bed_file/readthrough_gene.bed -f data/5y_expressed_genes_basemean\>5.txt -c id -o readthrough_expressed_gene.bed
python3 -m src.bed_handler.filter_bed -b results/bed_file/no_readthrough_gene.bed -f data/5y_expressed_genes_basemean\>5.txt -c id -o no_readthrough_expressed_gene.bed
# Create bed file corresponding to the 10kb downstream regions of the previous beds
python3 -m src.bed_handler.bed_resize \
nfontrod
committed
-b results/bed_file/no_readthrough_expressed_gene.bed \
-s 10000 \
-r "end" \
-t "outer" \
nfontrod
committed
-o no_readthrough_expressed_gene_10kb.bed
python3 -m src.bed_handler.bed_resize \
nfontrod
committed
-b results/bed_file/readthrough_expressed_gene.bed \
-s 10000 \
-r "end" \
-t "outer" \
nfontrod
committed
-o readthrough_expressed_gene_10kb.bed
exps=(all_replicates siCTRL siDDX)
bins=(0 99)
for exp in ${exps[*]}; do
for bin in ${bins[*]}; do
python3 -m src.visu \
--design data/design_exp_${exp}.txt \
--bw_folder data/bigwig/ \
nfontrod
committed
--region_bed results/bed_file/readthrough_expressed_gene.bed results/bed_file/no_readthrough_expressed_gene.bed \
--region_name readthrough no_readthrough \
--output results/figures/ \
--border_name TSS TTS \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm ${bin}
mv results/figures/metagene_readthrough-no_readthrough_100bin_10000_nt-around-25-bin_b${bin}_norm.pdf results/figures/${exp}_metagene_readthrough-no_readthrough_100bin_10000_nt-around-25-bin_b${bin}_norm.pdf
done
done
exps=(all_replicates siCTRL siDDX)
bins=(0 99)
loc=(TSS TTS)
for exp in ${exps[*]}; do
for i in ${!bins[@]}; do
python3 -m src.visu \
--design data/design_exp_${exp}.txt \
--bw_folder data/bigwig/ \
nfontrod
committed
--region_bed results/bed_file/readthrough_expressed_gene_10kb.bed results/bed_file/no_readthrough_expressed_gene_10kb.bed \
--region_name readthrough no_readthrough \
--output results/figures/ \
--border_name TTS '' \
--environment 0 0 \
--show_replicate n \
--figure_type metagene \
--nb_bin 25 \
nfontrod
committed
--norm "results/figures/coef_table/tmp_cov_table_design_exp_${exp}_readthrough_expressed_gene-no_readthrough_expressed_gene_100bin_10000_nt-around-25-bin_bin${bins[$i]}_norm.txt"
nfontrod
committed
mv results/figures/metagene_readthrough-no_readthrough_25bin_0_nt-around-0-bin_file_norm.pdf results/figures/${exp}_TTS10kb_readthrough-no_readthrough_${loc[$i]}_norm.pdf
nfontrod
committed
# Figure 1C
names=(IP)
designs=(data/designnew_exp_all_replicates_IP.txt)
bins=(99) # 0)
beds=(readthrough) # no_readthrough)
for bed in ${beds[*]}; do
for bin in ${bins[*]}; do
nfontrod
committed
for i in ${!designs[@]}; do
python3 -m src.visu \
--design ${designs[i]} \
--bw_folder data/bigwig_newnorm/ \
--region_bed results/bed_file/${bed}_expressed_gene.bed \
--region_name ${bed} \
--output results/figures/ \
--border_name TSS TTS \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
nfontrod
committed
mv results/figures/metagene_${bed}_100bin_10000_nt-around-25-bin_b${bin}_norm.pdf results/figures/Fig1C_${bed}_b${bin}_norm_${names[$i]}.pdf
done
nfontrod
committed
names=(IP)
designs=(data/designnew_exp_all_replicates_IP.txt)
beds=(readthrough) # no_readthrough)
bins=(99) # 0)
loc=(TTS) # TSS)
for bed in ${beds[*]}; do
for i in ${!bins[@]}; do
nfontrod
committed
for j in ${!designs[@]}; do
python3 -m src.visu \
--design ${designs[i]} \
--bw_folder data/bigwig_newnorm/ \
--region_bed results/bed_file/${bed}_expressed_gene_10kb.bed \
--region_name ${bed} \
--output results/figures/ \
--border_name TTS '' \
--environment 0 0 \
--show_replicate n \
--figure_type metagene \
--nb_bin 25 \
--norm "results/figures/coef_table/tmp_cov_table_designnew_exp_all_replicates_${names[$j]}_${bed}_expressed_gene_100bin_10000_nt-around-25-bin_bin${bins[$i]}_norm.txt" \
--stat True
nfontrod
committed
mv results/figures/metagene_${bed}_25bin_0_nt-around-0-bin_file_norm.pdf results/figures/Fig_1C_TTS10kb_${bed}_${loc[$i]}-bin_norm_${names[$j]}.pdf
done
done
done
# Graphics
##############################
# SHY5Y #
##############################
# Creating a bed file only containing expressed gene in 5y cells
python3 -m src.bed_handler.filter_bed \
-b data/bed/gene.bed \
-f data/5y_expressed_genes_basemean\>5.txt \
-c id \
-o 5y_expressed_gene.bed
# Create a bed file containing
bins=('None' 0 99)
bin_names=('' '_b0_norm' '_b99_norm')
for i in ${!bins[@]}; do
python3 -m src.visu \
--design data/bigwig_SHY5Y/design_exp_all_replicates.txt \
--bw_folder data/bigwig_SHY5Y/ \
--region_bed results/bed_file/5y_expressed_gene.bed \
--region_name all_expressed_gene \
--output results/figures/ \
--border_name TSS TTS \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm ${bins[$i]}
mv results/figures/metagene_all_expressed_gene_100bin_10000_nt-around-25-bin${bin_names[$i]}.pdf results/figures/metagene_5y_rnaseq_all_expressed_gene${bin_names[$i]}.pdf
bins=(25 25)
for i in ${!tts_sizes[@]}; do
size=${tts_sizes[$i]}
bin=${bins[$i]}
kb_size=$(python -c "print(int(${size}/1000)) if ${size}/1000 == int(${size}/1000) else print(${size}/1000)")
# Create a bed file containing all gene containing one DDX-down exons
python3 -m src.bed_handler.bed_resize \
-b results/bed_file/5y_expressed_gene.bed \
-s ${size} \
-r "end" \
-t "outer" \
-o all_expressed_gene_end${size}.bed
python3 -m src.visu \
--design data/bigwig_SHY5Y/design_exp_all_replicates.txt \
--bw_folder data/bigwig_SHY5Y/ \
--region_bed results/bed_file/all_expressed_gene_end${size}.bed \
--region_name all_expressed_gene \
--output results/figures/ \
--border_name TTS '' \
--environment 0 0 \
--show_replicate n \
--figure_type metagene \
--nb_bin ${bin} \
--norm "results/figures/coef_table/tmp_cov_table_design_exp_all_replicates_5y_expressed_gene_100bin_10000_nt-around-25-bin_bin99_norm.txt"
mv results/figures/metagene_all_expressed_gene_${bin}bin_0_nt-around-0-bin_file_norm.pdf results/figures/metagene_5y_rnaseq_TTS2${kb_size}kb_expressed_gene_${bin}bin_bin_TTS_norm.pdf
done
# 2kb region after TSS
python3 -m src.bed_handler.bed_resize \
-b data/bed/gene.bed \
-s 2000 \
-r "start" \
-o all_gene_TSS-2kb.bed
python3 -m src.visu \
--design data/bigwig_SHY5Y/design_exp_all_replicates.txt \
--bw_folder data/bigwig_SHY5Y/ \
--region_bed results/bed_file/all_gene_TSS-2kb.bed \
--region_name all_gene \
--output results/figures/ \
--border_name TSS '' \
--environment 0 0 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
mv results/figures/metagene_all_gene_100bin_0_nt-around-0-bin.pdf results/figures/metagene_5y_rnaseq_TSS-2kb_all_gene.pdf
#####################################################
# Metagene figure of last exons in readthrough genes near (<=2000 nt) or far (> 2000nt) from a CTCF file and last exons from non readthrough genes
#####################################################
# Bed file containing the last exons of expressed gene with readthrough
python3 -m src.bed_handler.get_last_exons -g results/bed_file/readthrough_expressed_gene.bed -o results/bed_file/readthrough_expressed_last_exon.bed
# Bed file containing the last exons of expressed gene without readthrough
python3 -m src.bed_handler.get_last_exons -g results/bed_file/no_readthrough_expressed_gene.bed -o results/bed_file/no_readthrough_expressed_last_exon.bed
# Bed file containing the last exon in expressed genes with readthrough near CTCF (<=2000nt)
python3 -m src.bed_handler.select_regulated_near_ctcf_exons -e results/bed_file/readthrough_expressed_last_exon.bed -t 2000 -l both -i True -N True -n readthrough_last_exon
# Bed file containing the last exon in expressed genes with readthrough near CTCF (>2000nt)
python3 -m src.bed_handler.select_regulated_near_ctcf_exons -e results/bed_file/readthrough_expressed_last_exon.bed -t 2000 -l both -i True -N False -n readthrough_last_exon
cp results/bed_file/no_readthrough_expressed_gene.bed results/bed_file/no_readthrough_expressed_last_gene-dup.bed
list_names=(readthrough_ctcf readthrough no_readthrough)
bed_names=(readthrough_last_exon_near_CTCF_2000_both_ddx_with0_exon.bed readthrough_last_exon_far_CTCF_2000_both_ddx_with0_exon.bed no_readthrough_expressed_last_exon.bed)
for i in ${!list_names[*]}; do
cname=${list_names[i]}
bed=${bed_names[i]}
gbed=${bed/exon\.bed/gene-dup.bed}
nbed=${gbed/\.bed/}
python3 -m src.visu \
nfontrod
committed
--design data/designnew_exp_all_replicates_IP.txt \
--bw_folder data/bigwig_newnorm \
--region_bed results/bed_file/${gbed} \
--region_name ${cname} \
--output results/figures/ \
--border_name TSS TTS \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm '0'
rm results/figures/metagene_${cname}_100bin_10000_nt-around-25-bin_b0_norm.pdf
python3 -m src.visu \
nfontrod
committed
--design data/designnew_exp_all_replicates_IP.txt \
--bw_folder data/bigwig_newnorm \
--region_bed results/bed_file/${bed} \
--region_name ${cname} \
--output results/figures/ \
--border_name " " " " \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 30 \
nfontrod
committed
--stat True \
-y 0.15 0.4 \
--norm "results/figures/coef_table/tmp_cov_table_designnew_exp_all_replicates_IP_${nbed}_100bin_10000_nt-around-25-bin_bin0_norm.txt" \
--stat True
mv results/figures/metagene_${cname}_30bin_10000_nt-around-25-bin_file_norm.pdf results/figures/all_replicates_metaexon_${cname}_30bin_10000_nt-around-25-bin_file_norm.pdf
done
###########################################################
# Figures siPP vs siCTRL pour ddx_down_ctcf,
# , ddx_down figure 5B
###########################################################
list_names=(ddx_down_ctcf ddx_down)
bed_names=(CTCF_2000_both_ddx_down_with0_exon.bed Far_CTCF_2000_both_ddx_down_with0_exon.bed)
for i in ${!list_names[*]}; do
cname=${list_names[i]}
bed=${bed_names[i]}
gbed=${bed/exon\.bed/gene-dup.bed}
nbed=${gbed/\.bed/}
python3 -m src.visu \
nfontrod
committed
--design data/designnew_exp_all_replicates_IP.txt \
--bw_folder data/bigwig_newnorm/ \
--region_bed results/bed_file/${gbed} \
--region_name ${cname} \
--output results/figures/ \
--border_name TSS TTS \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 100 \
--norm '0'
rm results/figures/metagene_${cname}_100bin_10000_nt-around-25-bin_b0_norm.pdf
python3 -m src.visu \
nfontrod
committed
--design data/designnew_exp_all_replicates_IP.txt \
--bw_folder data/bigwig_newnorm/ \
--region_bed results/bed_file/${bed} \
--region_name ${cname} \
--output results/figures/ \
--border_name " " " " \
--environment 10000 25 \
--show_replicate n \
--figure_type metagene \
--nb_bin 30 \
-y 0.15 0.4 \
nfontrod
committed
--stat True \
--norm "results/figures/coef_table/tmp_cov_table_designnew_exp_all_replicates_IP_${nbed}_100bin_10000_nt-around-25-bin_bin0_norm.txt" \
--stat True
mv results/figures/metagene_${cname}_30bin_10000_nt-around-25-bin_file_norm.pdf results/figures/all_replicates_metagene_${cname}_100bin_10000_nt-around-25-bin_file_norm.pdf
done
python3 -m src.gc_content -B results/bed_file/readthrough_last_exon_near_CTCF_2000_both_ddx_with0_exon.bed results/bed_file/readthrough_last_exon_far_CTCF_2000_both_ddx_with0_exon.bed results/bed_file/no_readthrough_expressed_last_exon.bed -b readthrough_ctcf readthrough no_readthrough -g data/Homo_sapiens.GRCh37.dna.primary_assembly.fa -f "exons" -e 2000