Correlation between copy number variations of arm-level result and molecular subtypes
Pancreatic Adenocarcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1X9293C
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between copy number variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1X9293C
Overview
Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and molecular subtypes.

Summary

Testing the association between copy number variation 76 arm-level events and 8 molecular subtypes across 102 patients, 26 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 7p gain cnv correlated to 'CN_CNMF'.

  • 7q gain cnv correlated to 'CN_CNMF'.

  • 8q gain cnv correlated to 'MIRSEQ_CHIERARCHICAL'.

  • 12p gain cnv correlated to 'CN_CNMF'.

  • 12q gain cnv correlated to 'CN_CNMF'.

  • 16p gain cnv correlated to 'CN_CNMF'.

  • 16q gain cnv correlated to 'CN_CNMF'.

  • 20p gain cnv correlated to 'CN_CNMF'.

  • 20q gain cnv correlated to 'CN_CNMF'.

  • 6p loss cnv correlated to 'METHLYATION_CNMF'.

  • 6q loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF',  'MIRSEQ_CHIERARCHICAL', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 9p loss cnv correlated to 'CN_CNMF'.

  • 10q loss cnv correlated to 'CN_CNMF'.

  • 17p loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL',  'MIRSEQ_CNMF',  'MIRSEQ_CHIERARCHICAL',  'MIRSEQ_MATURE_CNMF', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 17q loss cnv correlated to 'CN_CNMF'.

  • 21q loss cnv correlated to 'CN_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 76 arm-level events and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 26 significant findings detected.

Clinical
Features 		CN
CNMF 		METHLYATION
CNMF 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
CHIERARCHICAL 		MIRSEQ
MATURE
CNMF 		MIRSEQ
MATURE
CHIERARCHICAL
nCNV (%) nWild-Type Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
17p loss 40 (39%) 62 1e-05
(0.00608) 		1e-05
(0.00608) 		4e-05
(0.024) 		0.00031
(0.181) 		1e-05
(0.00608) 		0.00016
(0.0946) 		3e-05
(0.0181) 		0.00023
(0.135)
6q loss 47 (46%) 55 4e-05
(0.024) 		3e-05
(0.0181) 		0.00377
(1.00) 		0.00369
(1.00) 		0.013
(1.00) 		7e-05
(0.0419) 		0.0182
(1.00) 		0.0001
(0.0596)
7p gain 29 (28%) 73 1e-05
(0.00608) 		0.00546
(1.00) 		0.0116
(1.00) 		0.123
(1.00) 		0.211
(1.00) 		0.041
(1.00) 		0.0156
(1.00) 		0.00538
(1.00)
7q gain 25 (25%) 77 0.00016
(0.0946) 		0.0516
(1.00) 		0.0497
(1.00) 		0.323
(1.00) 		0.398
(1.00) 		0.157
(1.00) 		0.0329
(1.00) 		0.0446
(1.00)
8q gain 26 (25%) 76 0.00075
(0.431) 		0.00557
(1.00) 		0.533
(1.00) 		0.107
(1.00) 		0.767
(1.00) 		0.00012
(0.0713) 		0.242
(1.00) 		0.144
(1.00)
12p gain 10 (10%) 92 2e-05
(0.0121) 		0.0251
(1.00) 		0.662
(1.00) 		0.581
(1.00) 		0.959
(1.00) 		0.00053
(0.306) 		0.486
(1.00) 		0.334
(1.00)
12q gain 7 (7%) 95 0.00041
(0.239) 		0.0324
(1.00) 		0.176
(1.00) 		0.685
(1.00) 		0.857
(1.00) 		0.00732
(1.00) 		0.365
(1.00) 		0.507
(1.00)
16p gain 12 (12%) 90 0.00015
(0.0888) 		0.0603
(1.00) 		0.791
(1.00) 		0.436
(1.00) 		0.169
(1.00) 		0.0849
(1.00) 		0.213
(1.00) 		0.0461
(1.00)
16q gain 13 (13%) 89 0.00019
(0.112) 		0.0239
(1.00) 		0.684
(1.00) 		0.332
(1.00) 		0.121
(1.00) 		0.0151
(1.00) 		0.146
(1.00) 		0.0225
(1.00)
20p gain 20 (20%) 82 0.00011
(0.0654) 		0.0668
(1.00) 		0.354
(1.00) 		0.568
(1.00) 		0.951
(1.00) 		0.025
(1.00) 		0.577
(1.00) 		0.0876
(1.00)
20q gain 26 (25%) 76 1e-05
(0.00608) 		0.0921
(1.00) 		0.326
(1.00) 		0.558
(1.00) 		0.851
(1.00) 		0.00596
(1.00) 		0.243
(1.00) 		0.071
(1.00)
6p loss 37 (36%) 65 0.00053
(0.306) 		0.00021
(0.123) 		0.133
(1.00) 		0.316
(1.00) 		0.344
(1.00) 		0.0116
(1.00) 		0.273
(1.00) 		0.0236
(1.00)
9p loss 43 (42%) 59 0.00042
(0.245) 		0.59
(1.00) 		0.0283
(1.00) 		0.0737
(1.00) 		0.0944
(1.00) 		0.118
(1.00) 		0.00109
(0.622) 		0.0262
(1.00)
10q loss 18 (18%) 84 0.00012
(0.0713) 		0.15
(1.00) 		0.0876
(1.00) 		0.0215
(1.00) 		0.676
(1.00) 		0.0033
(1.00) 		0.299
(1.00) 		0.021
(1.00)
17q loss 15 (15%) 87 9e-05
(0.0537) 		0.0345
(1.00) 		0.345
(1.00) 		0.588
(1.00) 		0.537
(1.00) 		0.159
(1.00) 		0.379
(1.00) 		0.576
(1.00)
21q loss 36 (35%) 66 0.00016
(0.0946) 		0.00071
(0.409) 		0.0368
(1.00) 		0.0398
(1.00) 		0.26
(1.00) 		0.00825
(1.00) 		0.0789
(1.00) 		0.0345
(1.00)
1p gain 8 (8%) 94 0.552
(1.00) 		0.577
(1.00) 		0.598
(1.00) 		0.775
(1.00) 		0.332
(1.00) 		0.169
(1.00) 		0.274
(1.00) 		0.589
(1.00)
1q gain 29 (28%) 73 0.00924
(1.00) 		0.116
(1.00) 		0.0352
(1.00) 		0.471
(1.00) 		0.159
(1.00) 		0.0623
(1.00) 		0.0113
(1.00) 		0.162
(1.00)
2p gain 7 (7%) 95 0.0885
(1.00) 		0.0329
(1.00) 		0.887
(1.00) 		0.0132
(1.00) 		1
(1.00) 		0.00808
(1.00) 		1
(1.00) 		0.183
(1.00)
2q gain 8 (8%) 94 0.261
(1.00) 		0.0956
(1.00) 		0.725
(1.00) 		0.0281
(1.00) 		1
(1.00) 		0.0343
(1.00) 		1
(1.00) 		0.493
(1.00)
3p gain 5 (5%) 97 0.431
(1.00) 		0.442
(1.00) 		1
(1.00) 		1
(1.00) 		0.0419
(1.00) 		0.0341
(1.00) 		0.437
(1.00) 		0.839
(1.00)
3q gain 10 (10%) 92 0.0356
(1.00) 		0.0253
(1.00) 		0.35
(1.00) 		0.137
(1.00) 		0.555
(1.00) 		0.027
(1.00) 		0.635
(1.00) 		0.493
(1.00)
4p gain 3 (3%) 99 0.382
(1.00) 		0.8
(1.00) 		0.216
(1.00) 		0.102
(1.00) 		0.0361
(1.00) 		0.163
(1.00) 		0.332
(1.00) 		0.77
(1.00)
4q gain 3 (3%) 99 0.379
(1.00) 		0.803
(1.00) 		0.216
(1.00) 		0.101
(1.00) 		0.0352
(1.00) 		0.16
(1.00) 		0.327
(1.00) 		0.773
(1.00)
5p gain 13 (13%) 89 0.0132
(1.00) 		0.203
(1.00) 		0.685
(1.00) 		0.741
(1.00) 		0.538
(1.00) 		0.0976
(1.00) 		0.147
(1.00) 		0.789
(1.00)
5q gain 10 (10%) 92 0.0226
(1.00) 		0.574
(1.00) 		0.831
(1.00) 		0.342
(1.00) 		0.822
(1.00) 		0.355
(1.00) 		0.585
(1.00) 		0.905
(1.00)
8p gain 14 (14%) 88 0.00523
(1.00) 		0.105
(1.00) 		0.796
(1.00) 		0.367
(1.00) 		0.975
(1.00) 		0.00871
(1.00) 		1
(1.00) 		0.578
(1.00)
9p gain 3 (3%) 99 0.212
(1.00) 		0.434
(1.00) 		0.802
(1.00) 		0.94
(1.00) 		0.152
(1.00) 		0.0427
(1.00) 		0.333
(1.00) 		1
(1.00)
9q gain 4 (4%) 98 0.139
(1.00) 		0.177
(1.00) 		0.466
(1.00) 		0.933
(1.00) 		0.558
(1.00) 		0.208
(1.00) 		0.815
(1.00) 		0.811
(1.00)
10p gain 5 (5%) 97 0.0999
(1.00) 		0.442
(1.00) 		0.464
(1.00) 		0.932
(1.00) 		0.682
(1.00) 		0.426
(1.00) 		0.276
(1.00) 		0.812
(1.00)
10q gain 7 (7%) 95 0.0773
(1.00) 		0.343
(1.00) 		0.593
(1.00) 		0.604
(1.00) 		0.598
(1.00) 		0.37
(1.00) 		0.247
(1.00) 		0.588
(1.00)
11p gain 10 (10%) 92 0.0157
(1.00) 		0.14
(1.00) 		0.834
(1.00) 		0.838
(1.00) 		0.707
(1.00) 		0.427
(1.00) 		0.532
(1.00) 		0.407
(1.00)
11q gain 8 (8%) 94 0.0801
(1.00) 		0.17
(1.00) 		0.89
(1.00) 		0.612
(1.00) 		0.954
(1.00) 		0.437
(1.00) 		0.645
(1.00) 		0.492
(1.00)
13q gain 11 (11%) 91 0.615
(1.00) 		0.755
(1.00) 		0.313
(1.00) 		0.286
(1.00) 		0.316
(1.00) 		0.316
(1.00) 		0.695
(1.00) 		0.197
(1.00)
14q gain 13 (13%) 89 0.00707
(1.00) 		0.206
(1.00) 		0.503
(1.00) 		0.0883
(1.00) 		0.112
(1.00) 		0.491
(1.00) 		0.438
(1.00) 		0.788
(1.00)
15q gain 8 (8%) 94 0.259
(1.00) 		0.343
(1.00) 		0.303
(1.00) 		0.0571
(1.00) 		0.706
(1.00) 		0.74
(1.00) 		0.605
(1.00) 		0.446
(1.00)
17q gain 5 (5%) 97 0.14
(1.00) 		1
(1.00) 		0.509
(1.00) 		0.394
(1.00) 		0.854
(1.00) 		0.0869
(1.00) 		0.848
(1.00) 		0.589
(1.00)
18p gain 15 (15%) 87 0.00144
(0.819) 		0.0128
(1.00) 		0.00133
(0.758) 		0.117
(1.00) 		0.0113
(1.00) 		0.00568
(1.00) 		0.00249
(1.00) 		0.00242
(1.00)
18q gain 5 (5%) 97 0.0646
(1.00) 		0.182
(1.00) 		0.18
(1.00) 		0.614
(1.00) 		0.451
(1.00) 		0.301
(1.00) 		0.56
(1.00) 		0.241
(1.00)
19p gain 5 (5%) 97 0.21
(1.00) 		0.44
(1.00) 		1
(1.00) 		0.0271
(1.00) 		0.641
(1.00) 		0.53
(1.00) 		0.847
(1.00) 		0.589
(1.00)
19q gain 13 (13%) 89 0.0767
(1.00) 		0.107
(1.00) 		0.688
(1.00) 		0.273
(1.00) 		0.534
(1.00) 		0.544
(1.00) 		0.327
(1.00) 		0.578
(1.00)
22q gain 6 (6%) 96 0.00293
(1.00) 		0.0749
(1.00) 		0.0746
(1.00) 		0.227
(1.00) 		0.856
(1.00) 		0.0875
(1.00) 		0.846
(1.00) 		0.59
(1.00)
xq gain 4 (4%) 98 1
(1.00) 		0.367
(1.00) 		0.36
(1.00) 		0.596
(1.00) 		0.503
(1.00) 		0.194
(1.00) 		0.68
(1.00) 		0.313
(1.00)
1p loss 19 (19%) 83 0.0263
(1.00) 		0.0265
(1.00) 		0.0173
(1.00) 		0.071
(1.00) 		0.119
(1.00) 		0.0291
(1.00) 		0.0837
(1.00) 		0.306
(1.00)
1q loss 5 (5%) 97 0.208
(1.00) 		0.44
(1.00) 		0.466
(1.00) 		0.932
(1.00) 		0.819
(1.00) 		0.429
(1.00) 		1
(1.00) 		0.809
(1.00)
2p loss 7 (7%) 95 0.177
(1.00) 		0.677
(1.00) 		0.6
(1.00) 		0.677
(1.00) 		0.819
(1.00) 		0.726
(1.00) 		0.785
(1.00) 		0.592
(1.00)
2q loss 3 (3%) 99 0.0764
(1.00) 		0.433
(1.00) 		0.433
(1.00) 		0.595
(1.00) 		0.747
(1.00) 		0.367
(1.00) 		0.789
(1.00) 		0.302
(1.00)
3p loss 17 (17%) 85 0.0179
(1.00) 		0.7
(1.00) 		0.491
(1.00) 		0.811
(1.00) 		0.875
(1.00) 		0.166
(1.00) 		0.137
(1.00) 		0.254
(1.00)
3q loss 13 (13%) 89 0.263
(1.00) 		0.642
(1.00) 		0.407
(1.00) 		0.863
(1.00) 		0.657
(1.00) 		0.361
(1.00) 		0.127
(1.00) 		0.513
(1.00)
4p loss 13 (13%) 89 0.285
(1.00) 		0.317
(1.00) 		0.185
(1.00) 		0.546
(1.00) 		0.326
(1.00) 		0.266
(1.00) 		0.214
(1.00) 		0.208
(1.00)
4q loss 13 (13%) 89 0.285
(1.00) 		0.048
(1.00) 		0.131
(1.00) 		0.0997
(1.00) 		0.359
(1.00) 		0.472
(1.00) 		0.191
(1.00) 		0.0307
(1.00)
5p loss 6 (6%) 96 0.0146
(1.00) 		0.0318
(1.00) 		0.475
(1.00) 		0.514
(1.00) 		0.198
(1.00) 		0.311
(1.00) 		0.0874
(1.00) 		0.33
(1.00)
5q loss 9 (9%) 93 0.00051
(0.296) 		0.00431
(1.00) 		0.221
(1.00) 		0.687
(1.00) 		0.417
(1.00) 		0.0684
(1.00) 		0.0122
(1.00) 		0.209
(1.00)
7p loss 3 (3%) 99 0.0735
(1.00) 		0.437
(1.00) 		0.801
(1.00) 		0.94
(1.00) 		0.562
(1.00) 		0.00762
(1.00) 		0.177
(1.00) 		0.433
(1.00)
7q loss 4 (4%) 98 0.0248
(1.00) 		0.181
(1.00) 		0.808
(1.00) 		0.933
(1.00) 		0.681
(1.00) 		0.0561
(1.00) 		0.277
(1.00) 		0.658
(1.00)
8p loss 19 (19%) 83 0.0333
(1.00) 		0.0672
(1.00) 		0.0949
(1.00) 		0.268
(1.00) 		0.337
(1.00) 		0.0497
(1.00) 		0.102
(1.00) 		0.0477
(1.00)
8q loss 7 (7%) 95 0.528
(1.00) 		0.679
(1.00) 		0.344
(1.00) 		0.291
(1.00) 		0.675
(1.00) 		0.683
(1.00) 		0.367
(1.00) 		0.589
(1.00)
9q loss 28 (27%) 74 0.0808
(1.00) 		0.805
(1.00) 		0.372
(1.00) 		0.892
(1.00) 		0.252
(1.00) 		0.521
(1.00) 		0.066
(1.00) 		0.7
(1.00)
10p loss 19 (19%) 83 0.00646
(1.00) 		0.102
(1.00) 		0.161
(1.00) 		0.322
(1.00) 		0.382
(1.00) 		0.00052
(0.301) 		0.126
(1.00) 		0.0686
(1.00)
11p loss 9 (9%) 93 0.213
(1.00) 		0.133
(1.00) 		0.0433
(1.00) 		0.196
(1.00) 		0.0716
(1.00) 		0.251
(1.00) 		0.18
(1.00) 		0.0971
(1.00)
11q loss 11 (11%) 91 0.465
(1.00) 		0.653
(1.00) 		0.227
(1.00) 		0.292
(1.00) 		0.821
(1.00) 		0.564
(1.00) 		0.755
(1.00) 		0.751
(1.00)
12p loss 9 (9%) 93 0.0184
(1.00) 		0.0432
(1.00) 		0.0834
(1.00) 		0.104
(1.00) 		0.469
(1.00) 		0.227
(1.00) 		0.901
(1.00) 		0.0574
(1.00)
12q loss 12 (12%) 90 0.0182
(1.00) 		0.561
(1.00) 		0.388
(1.00) 		0.361
(1.00) 		0.963
(1.00) 		0.495
(1.00) 		0.53
(1.00) 		0.493
(1.00)
13q loss 13 (13%) 89 0.0024
(1.00) 		0.0239
(1.00) 		0.00573
(1.00) 		0.12
(1.00) 		0.106
(1.00) 		0.0421
(1.00) 		0.0713
(1.00) 		0.00991
(1.00)
14q loss 8 (8%) 94 1
(1.00) 		0.575
(1.00) 		0.643
(1.00) 		0.611
(1.00) 		0.646
(1.00) 		0.838
(1.00) 		0.804
(1.00) 		0.341
(1.00)
15q loss 17 (17%) 85 0.00084
(0.481) 		0.00076
(0.436) 		0.0106
(1.00) 		0.00532
(1.00) 		0.0495
(1.00) 		0.00919
(1.00) 		0.055
(1.00) 		0.0025
(1.00)
16p loss 5 (5%) 97 0.0585
(1.00) 		0.074
(1.00) 		0.508
(1.00) 		0.771
(1.00) 		0.418
(1.00) 		0.312
(1.00) 		0.2
(1.00) 		0.589
(1.00)
16q loss 5 (5%) 97 0.0578
(1.00) 		0.074
(1.00) 		0.508
(1.00) 		0.771
(1.00) 		0.417
(1.00) 		0.371
(1.00) 		0.198
(1.00) 		0.591
(1.00)
18p loss 34 (33%) 68 0.353
(1.00) 		0.0983
(1.00) 		0.426
(1.00) 		0.802
(1.00) 		0.559
(1.00) 		0.495
(1.00) 		0.0569
(1.00) 		0.151
(1.00)
18q loss 58 (57%) 44 0.00432
(1.00) 		0.104
(1.00) 		0.116
(1.00) 		0.166
(1.00) 		0.257
(1.00) 		0.59
(1.00) 		0.192
(1.00) 		0.405
(1.00)
19p loss 14 (14%) 88 0.00044
(0.256) 		0.00103
(0.589) 		0.0191
(1.00) 		0.0573
(1.00) 		0.346
(1.00) 		0.00049
(0.285) 		0.0872
(1.00) 		0.0845
(1.00)
19q loss 9 (9%) 93 0.0324
(1.00) 		0.0426
(1.00) 		0.0487
(1.00) 		0.0539
(1.00) 		0.232
(1.00) 		0.0236
(1.00) 		0.483
(1.00) 		0.0608
(1.00)
20p loss 12 (12%) 90 0.0139
(1.00) 		0.174
(1.00) 		0.119
(1.00) 		0.244
(1.00) 		0.0168
(1.00) 		0.0893
(1.00) 		0.0094
(1.00) 		0.227
(1.00)
20q loss 5 (5%) 97 0.058
(1.00) 		0.0738
(1.00) 		0.506
(1.00) 		0.495
(1.00) 		0.415
(1.00) 		0.131
(1.00) 		0.2
(1.00) 		0.588
(1.00)
22q loss 26 (25%) 76 0.00178
(1.00) 		0.0166
(1.00) 		0.107
(1.00) 		0.11
(1.00) 		0.301
(1.00) 		0.00449
(1.00) 		0.183
(1.00) 		0.189
(1.00)
xq loss 9 (9%) 93 0.00657
(1.00) 		0.11
(1.00) 		0.275
(1.00) 		0.5
(1.00) 		0.241
(1.00) 		0.383
(1.00) 		0.0652
(1.00) 		0.385
(1.00)
'7p gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0061

Table S1.  Gene #11: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
7P GAIN MUTATED 14 4 4 7
7P GAIN WILD-TYPE 15 42 14 2

Figure S1.  Get High-res Image Gene #11: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

'7q gain' versus 'CN_CNMF'

P value = 0.00016 (Fisher's exact test), Q value = 0.095

Table S2.  Gene #12: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
7Q GAIN MUTATED 12 4 3 6
7Q GAIN WILD-TYPE 17 42 15 3

Figure S2.  Get High-res Image Gene #12: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

'8q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00012 (Fisher's exact test), Q value = 0.071

Table S3.  Gene #14: '8q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 17 20 18 8 20 12
8Q GAIN MUTATED 7 0 2 6 4 5
8Q GAIN WILD-TYPE 10 20 16 2 16 7

Figure S3.  Get High-res Image Gene #14: '8q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'12p gain' versus 'CN_CNMF'

P value = 2e-05 (Fisher's exact test), Q value = 0.012

Table S4.  Gene #21: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
12P GAIN MUTATED 10 0 0 0
12P GAIN WILD-TYPE 19 46 18 9

Figure S4.  Get High-res Image Gene #21: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

'12q gain' versus 'CN_CNMF'

P value = 0.00041 (Fisher's exact test), Q value = 0.24

Table S5.  Gene #22: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
12Q GAIN MUTATED 7 0 0 0
12Q GAIN WILD-TYPE 22 46 18 9

Figure S5.  Get High-res Image Gene #22: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

'16p gain' versus 'CN_CNMF'

P value = 0.00015 (Fisher's exact test), Q value = 0.089

Table S6.  Gene #26: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
16P GAIN MUTATED 8 0 1 3
16P GAIN WILD-TYPE 21 46 17 6

Figure S6.  Get High-res Image Gene #26: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

'16q gain' versus 'CN_CNMF'

P value = 0.00019 (Fisher's exact test), Q value = 0.11

Table S7.  Gene #27: '16q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
16Q GAIN MUTATED 8 0 2 3
16Q GAIN WILD-TYPE 21 46 16 6

Figure S7.  Get High-res Image Gene #27: '16q gain' versus Molecular Subtype #1: 'CN_CNMF'

'20p gain' versus 'CN_CNMF'

P value = 0.00011 (Fisher's exact test), Q value = 0.065

Table S8.  Gene #33: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
20P GAIN MUTATED 12 4 0 4
20P GAIN WILD-TYPE 17 42 18 5

Figure S8.  Get High-res Image Gene #33: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

'20q gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0061

Table S9.  Gene #34: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
20Q GAIN MUTATED 17 5 0 4
20Q GAIN WILD-TYPE 12 41 18 5

Figure S9.  Get High-res Image Gene #34: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

'6p loss' versus 'METHLYATION_CNMF'

P value = 0.00021 (Fisher's exact test), Q value = 0.12

Table S10.  Gene #47: '6p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 49 26 26
6P LOSS MUTATED 27 3 6
6P LOSS WILD-TYPE 22 23 20

Figure S10.  Get High-res Image Gene #47: '6p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'6q loss' versus 'CN_CNMF'

P value = 4e-05 (Fisher's exact test), Q value = 0.024

Table S11.  Gene #48: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
6Q LOSS MUTATED 21 10 9 7
6Q LOSS WILD-TYPE 8 36 9 2

Figure S11.  Get High-res Image Gene #48: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

'6q loss' versus 'METHLYATION_CNMF'

P value = 3e-05 (Fisher's exact test), Q value = 0.018

Table S12.  Gene #48: '6q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 49 26 26
6Q LOSS MUTATED 33 4 9
6Q LOSS WILD-TYPE 16 22 17

Figure S12.  Get High-res Image Gene #48: '6q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'6q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 7e-05 (Fisher's exact test), Q value = 0.042

Table S13.  Gene #48: '6q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 17 20 18 8 20 12
6Q LOSS MUTATED 13 3 3 5 9 9
6Q LOSS WILD-TYPE 4 17 15 3 11 3

Figure S13.  Get High-res Image Gene #48: '6q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'6q loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 1e-04 (Fisher's exact test), Q value = 0.06

Table S14.  Gene #48: '6q loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 28 19
6Q LOSS MUTATED 31 8 3
6Q LOSS WILD-TYPE 17 20 16

Figure S14.  Get High-res Image Gene #48: '6q loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'9p loss' versus 'CN_CNMF'

P value = 0.00042 (Fisher's exact test), Q value = 0.24

Table S15.  Gene #53: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
9P LOSS MUTATED 20 11 6 6
9P LOSS WILD-TYPE 9 35 12 3

Figure S15.  Get High-res Image Gene #53: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'10q loss' versus 'CN_CNMF'

P value = 0.00012 (Fisher's exact test), Q value = 0.071

Table S16.  Gene #56: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
10Q LOSS MUTATED 12 2 1 3
10Q LOSS WILD-TYPE 17 44 17 6

Figure S16.  Get High-res Image Gene #56: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

'17p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0061

Table S17.  Gene #66: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
17P LOSS MUTATED 22 2 13 3
17P LOSS WILD-TYPE 7 44 5 6

Figure S17.  Get High-res Image Gene #66: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

'17p loss' versus 'METHLYATION_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0061

Table S18.  Gene #66: '17p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 49 26 26
17P LOSS MUTATED 33 3 4
17P LOSS WILD-TYPE 16 23 22

Figure S18.  Get High-res Image Gene #66: '17p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'17p loss' versus 'MRNASEQ_CNMF'

P value = 4e-05 (Fisher's exact test), Q value = 0.024

Table S19.  Gene #66: '17p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 46 26 23
17P LOSS MUTATED 26 10 1
17P LOSS WILD-TYPE 20 16 22

Figure S19.  Get High-res Image Gene #66: '17p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'17p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00031 (Fisher's exact test), Q value = 0.18

Table S20.  Gene #66: '17p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 27 13 14 12 22 7
17P LOSS MUTATED 17 8 0 4 7 1
17P LOSS WILD-TYPE 10 5 14 8 15 6

Figure S20.  Get High-res Image Gene #66: '17p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'17p loss' versus 'MIRSEQ_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0061

Table S21.  Gene #66: '17p loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 37 25 13 20
17P LOSS MUTATED 26 8 1 2
17P LOSS WILD-TYPE 11 17 12 18

Figure S21.  Get High-res Image Gene #66: '17p loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'17p loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00016 (Fisher's exact test), Q value = 0.095

Table S22.  Gene #66: '17p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 17 20 18 8 20 12
17P LOSS MUTATED 12 4 1 5 8 7
17P LOSS WILD-TYPE 5 16 17 3 12 5

Figure S22.  Get High-res Image Gene #66: '17p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'17p loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 3e-05 (Fisher's exact test), Q value = 0.018

Table S23.  Gene #66: '17p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 41 23 31
17P LOSS MUTATED 26 8 3
17P LOSS WILD-TYPE 15 15 28

Figure S23.  Get High-res Image Gene #66: '17p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'17p loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.00023 (Fisher's exact test), Q value = 0.13

Table S24.  Gene #66: '17p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 28 19
17P LOSS MUTATED 27 9 1
17P LOSS WILD-TYPE 21 19 18

Figure S24.  Get High-res Image Gene #66: '17p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'17q loss' versus 'CN_CNMF'

P value = 9e-05 (Fisher's exact test), Q value = 0.054

Table S25.  Gene #67: '17q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
17Q LOSS MUTATED 10 0 3 2
17Q LOSS WILD-TYPE 19 46 15 7

Figure S25.  Get High-res Image Gene #67: '17q loss' versus Molecular Subtype #1: 'CN_CNMF'

'21q loss' versus 'CN_CNMF'

P value = 0.00016 (Fisher's exact test), Q value = 0.095

Table S26.  Gene #74: '21q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 29 46 18 9
21Q LOSS MUTATED 16 6 9 5
21Q LOSS WILD-TYPE 13 40 9 4

Figure S26.  Get High-res Image Gene #74: '21q loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data
Input

  • Copy number data file = transformed.cor.cli.txt

  • Molecular subtypes file = PAAD-TP.transferedmergedcluster.txt

  • Number of patients = 102

  • Number of significantly arm-level cnvs = 76

  • Number of molecular subtypes = 8

  • Exclude genes that fewer than K tumors have mutations, K = 3

Fisher's exact test

For binary or multi-class clinical features (nominal or ordinal), two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R

Q value calculation

For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References
[1] Fisher, R.A., On the interpretation of chi-square from contingency tables, and the calculation of P, Journal of the Royal Statistical Society 85(1):87-94 (1922)
[2] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)
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