Correlation between copy number variations of arm-level result and selected clinical features
Ovarian Serous Cystadenocarcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C1ZW1HZV
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1ZW1HZV
Overview
Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.

Summary

Testing the association between copy number variation 80 arm-level results and 7 clinical features across 562 patients, 8 significant findings detected with Q value < 0.25.

  • 2p gain cnv correlated to 'AGE'.

  • 3q gain cnv correlated to 'AGE'.

  • 10p gain cnv correlated to 'AGE'.

  • 12p gain cnv correlated to 'AGE'.

  • 12q gain cnv correlated to 'AGE'.

  • 20p gain cnv correlated to 'AGE'.

  • 20q gain cnv correlated to 'AGE'.

  • 9q loss cnv correlated to 'AGE'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 80 arm-level results and 7 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 8 significant findings detected.

Clinical
Features 		Time
to
Death 		AGE PRIMARY
SITE
OF
DISEASE 		KARNOFSKY
PERFORMANCE
SCORE 		TUMOR
STAGE 		RADIATIONS
RADIATION
REGIMENINDICATION 		COMPLETENESS
OF
RESECTION
nCNV (%) nWild-Type logrank test t-test Fisher's exact test t-test Fisher's exact test Fisher's exact test Fisher's exact test
2p gain 0 (0%) 434 0.0322
(1.00) 		2.45e-07
(0.00013) 		1
(1.00) 		0.956
(1.00) 		0.474
(1.00) 		0.54
(1.00) 		1
(1.00)
3q gain 0 (0%) 357 0.594
(1.00) 		7.84e-07
(0.000417) 		0.126
(1.00) 		0.671
(1.00) 		0.823
(1.00) 		0.557
(1.00) 		0.11
(1.00)
10p gain 0 (0%) 432 0.217
(1.00) 		1.17e-05
(0.00614) 		0.107
(1.00) 		0.184
(1.00) 		0.787
(1.00) 		1
(1.00) 		0.529
(1.00)
12p gain 0 (0%) 355 0.28
(1.00) 		3.52e-08
(1.88e-05) 		0.125
(1.00) 		0.0302
(1.00) 		0.754
(1.00) 		1
(1.00) 		0.658
(1.00)
12q gain 0 (0%) 440 0.109
(1.00) 		1.49e-06
(0.000788) 		0.615
(1.00) 		0.0312
(1.00) 		1
(1.00) 		0.521
(1.00) 		0.62
(1.00)
20p gain 0 (0%) 329 0.125
(1.00) 		2.92e-06
(0.00155) 		1
(1.00) 		0.105
(1.00) 		0.566
(1.00) 		0.573
(1.00) 		1
(1.00)
20q gain 0 (0%) 290 0.0957
(1.00) 		1.27e-06
(0.000674) 		1
(1.00) 		0.229
(1.00) 		0.466
(1.00) 		0.613
(1.00) 		1
(1.00)
9q loss 0 (0%) 322 0.507
(1.00) 		3.74e-06
(0.00198) 		0.152
(1.00) 		0.779
(1.00) 		0.787
(1.00) 		0.578
(1.00) 		0.872
(1.00)
1p gain 0 (0%) 458 0.0923
(1.00) 		0.835
(1.00) 		0.155
(1.00) 		0.126
(1.00) 		0.0648
(1.00) 		0.0896
(1.00) 		0.108
(1.00)
1q gain 0 (0%) 402 0.303
(1.00) 		0.0343
(1.00) 		0.068
(1.00) 		0.0331
(1.00) 		0.186
(1.00) 		1
(1.00) 		1
(1.00)
2q gain 0 (0%) 460 0.111
(1.00) 		0.000516
(0.272) 		1
(1.00) 		0.69
(1.00) 		0.453
(1.00) 		0.0864
(1.00) 		1
(1.00)
3p gain 0 (0%) 453 0.41
(1.00) 		0.0346
(1.00) 		0.575
(1.00) 		0.73
(1.00) 		0.259
(1.00) 		1
(1.00) 		0.567
(1.00)
4p gain 0 (0%) 531 0.279
(1.00) 		0.575
(1.00) 		1
(1.00) 		0.921
(1.00) 		1
(1.00) 		1
(1.00)
4q gain 0 (0%) 546 0.235
(1.00) 		0.0444
(1.00) 		1
(1.00) 		0.921
(1.00) 		1
(1.00) 		1
(1.00)
5p gain 0 (0%) 418 0.528
(1.00) 		0.238
(1.00) 		0.124
(1.00) 		0.791
(1.00) 		0.48
(1.00) 		1
(1.00) 		0.0518
(1.00)
5q gain 0 (0%) 529 0.309
(1.00) 		0.935
(1.00) 		0.207
(1.00) 		0.137
(1.00) 		0.417
(1.00) 		1
(1.00) 		0.251
(1.00)
6p gain 0 (0%) 442 0.455
(1.00) 		0.00625
(1.00) 		0.619
(1.00) 		0.0337
(1.00) 		1
(1.00) 		1
(1.00) 		0.53
(1.00)
6q gain 0 (0%) 500 0.51
(1.00) 		0.0516
(1.00) 		1
(1.00) 		0.195
(1.00) 		0.46
(1.00) 		1
(1.00) 		0.675
(1.00)
7p gain 0 (0%) 438 0.205
(1.00) 		0.00153
(0.801) 		1
(1.00) 		0.292
(1.00) 		0.172
(1.00) 		1
(1.00) 		1
(1.00)
7q gain 0 (0%) 412 0.19
(1.00) 		0.0107
(1.00) 		0.711
(1.00) 		0.276
(1.00) 		0.0198
(1.00) 		0.568
(1.00) 		0.76
(1.00)
8p gain 0 (0%) 476 0.0823
(1.00) 		0.685
(1.00) 		1
(1.00) 		0.894
(1.00) 		0.179
(1.00) 		0.393
(1.00) 		1
(1.00)
8q gain 0 (0%) 359 0.195
(1.00) 		0.589
(1.00) 		0.249
(1.00) 		0.88
(1.00) 		0.479
(1.00) 		1
(1.00) 		0.125
(1.00)
9p gain 0 (0%) 503 0.74
(1.00) 		0.776
(1.00) 		1
(1.00) 		0.95
(1.00) 		0.764
(1.00) 		1
(1.00) 		0.675
(1.00)
9q gain 0 (0%) 535 0.947
(1.00) 		0.656
(1.00) 		1
(1.00) 		0.351
(1.00) 		1
(1.00) 		1
(1.00)
10q gain 0 (0%) 495 0.458
(1.00) 		0.0159
(1.00) 		0.405
(1.00) 		0.403
(1.00) 		0.684
(1.00) 		1
(1.00) 		0.576
(1.00)
11p gain 0 (0%) 522 0.574
(1.00) 		0.85
(1.00) 		1
(1.00) 		0.852
(1.00) 		0.417
(1.00) 		1
(1.00)
11q gain 0 (0%) 501 0.296
(1.00) 		0.471
(1.00) 		1
(1.00) 		0.566
(1.00) 		0.223
(1.00) 		1
(1.00) 		0.411
(1.00)
13q gain 0 (0%) 521 0.708
(1.00) 		0.0264
(1.00) 		1
(1.00) 		0.476
(1.00) 		0.124
(1.00) 		0.204
(1.00) 		1
(1.00)
14q gain 0 (0%) 529 0.311
(1.00) 		0.788
(1.00) 		1
(1.00) 		0.497
(1.00) 		0.532
(1.00) 		0.166
(1.00) 		0.411
(1.00)
15q gain 0 (0%) 537 0.856
(1.00) 		0.353
(1.00) 		1
(1.00) 		1
(1.00)
16p gain 0 (0%) 531 0.612
(1.00) 		0.469
(1.00) 		1
(1.00) 		0.232
(1.00) 		0.282
(1.00) 		1
(1.00) 		0.277
(1.00)
16q gain 0 (0%) 546 0.666
(1.00) 		0.751
(1.00) 		1
(1.00) 		1
(1.00) 		0.377
(1.00)
17p gain 0 (0%) 551 0.16
(1.00) 		0.0794
(1.00) 		1
(1.00) 		0.767
(1.00) 		1
(1.00)
17q gain 0 (0%) 539 0.169
(1.00) 		0.179
(1.00) 		1
(1.00) 		0.614
(1.00) 		1
(1.00) 		1
(1.00)
18p gain 0 (0%) 488 0.149
(1.00) 		0.165
(1.00) 		1
(1.00) 		0.341
(1.00) 		0.544
(1.00) 		1
(1.00) 		0.778
(1.00)
18q gain 0 (0%) 521 0.342
(1.00) 		0.34
(1.00) 		1
(1.00) 		0.252
(1.00) 		0.385
(1.00) 		0.204
(1.00) 		1
(1.00)
19p gain 0 (0%) 464 0.333
(1.00) 		0.0145
(1.00) 		1
(1.00) 		0.996
(1.00) 		0.217
(1.00) 		0.438
(1.00) 		0.741
(1.00)
19q gain 0 (0%) 471 0.147
(1.00) 		0.0146
(1.00) 		1
(1.00) 		0.649
(1.00) 		0.339
(1.00) 		0.412
(1.00) 		0.476
(1.00)
21q gain 0 (0%) 492 0.00631
(1.00) 		0.0135
(1.00) 		0.405
(1.00) 		0.566
(1.00) 		0.243
(1.00) 		1
(1.00) 		0.576
(1.00)
22q gain 0 (0%) 553 0.599
(1.00) 		0.293
(1.00) 		1
(1.00) 		1
(1.00)
Xq gain 0 (0%) 528 0.0964
(1.00) 		0.203
(1.00) 		1
(1.00) 		0.137
(1.00) 		0.362
(1.00) 		1
(1.00)
1p loss 0 (0%) 528 0.84
(1.00) 		0.415
(1.00) 		1
(1.00) 		0.296
(1.00) 		0.599
(1.00) 		0.171
(1.00)
1q loss 0 (0%) 540 0.333
(1.00) 		0.0888
(1.00) 		1
(1.00) 		0.22
(1.00) 		0.362
(1.00) 		0.113
(1.00)
2p loss 0 (0%) 536 0.58
(1.00) 		0.839
(1.00) 		1
(1.00) 		0.0731
(1.00) 		1
(1.00) 		1
(1.00)
2q loss 0 (0%) 532 0.72
(1.00) 		0.458
(1.00) 		0.201
(1.00) 		0.0731
(1.00) 		1
(1.00) 		1
(1.00)
3p loss 0 (0%) 503 0.319
(1.00) 		0.135
(1.00) 		0.365
(1.00) 		0.321
(1.00) 		0.172
(1.00) 		0.283
(1.00) 		0.0647
(1.00)
3q loss 0 (0%) 539 0.137
(1.00) 		0.84
(1.00) 		0.157
(1.00) 		0.607
(1.00) 		0.282
(1.00) 		0.118
(1.00)
4p loss 0 (0%) 303 0.271
(1.00) 		0.332
(1.00) 		0.166
(1.00) 		0.106
(1.00) 		0.627
(1.00) 		0.597
(1.00) 		1
(1.00)
4q loss 0 (0%) 262 0.365
(1.00) 		0.188
(1.00) 		0.751
(1.00) 		0.952
(1.00) 		0.561
(1.00) 		1
(1.00) 		0.652
(1.00)
5p loss 0 (0%) 479 0.286
(1.00) 		0.0298
(1.00) 		0.475
(1.00) 		0.227
(1.00) 		0.285
(1.00) 		1
(1.00)
5q loss 0 (0%) 392 0.49
(1.00) 		0.131
(1.00) 		0.353
(1.00) 		0.42
(1.00) 		0.209
(1.00) 		1
(1.00) 		1
(1.00)
6p loss 0 (0%) 437 0.0964
(1.00) 		0.00433
(1.00) 		0.633
(1.00) 		0.647
(1.00) 		0.849
(1.00) 		0.531
(1.00) 		0.189
(1.00)
6q loss 0 (0%) 368 0.427
(1.00) 		0.00635
(1.00) 		0.116
(1.00) 		0.309
(1.00) 		0.439
(1.00) 		1
(1.00) 		1
(1.00)
7p loss 0 (0%) 472 0.121
(1.00) 		0.983
(1.00) 		0.506
(1.00) 		0.0336
(1.00) 		0.362
(1.00) 		1
(1.00) 		0.277
(1.00)
7q loss 0 (0%) 514 0.0391
(1.00) 		0.247
(1.00) 		0.306
(1.00) 		0.00339
(1.00) 		0.768
(1.00) 		0.235
(1.00)
8p loss 0 (0%) 330 0.278
(1.00) 		0.0304
(1.00) 		0.146
(1.00) 		0.0388
(1.00) 		1
(1.00) 		1
(1.00) 		0.354
(1.00)
8q loss 0 (0%) 500 0.38
(1.00) 		0.0258
(1.00) 		1
(1.00) 		0.331
(1.00) 		0.814
(1.00) 		1
(1.00) 		0.675
(1.00)
9p loss 0 (0%) 350 0.568
(1.00) 		0.0342
(1.00) 		0.13
(1.00) 		0.479
(1.00) 		1
(1.00) 		0.56
(1.00) 		0.456
(1.00)
10p loss 0 (0%) 496 0.659
(1.00) 		0.179
(1.00) 		1
(1.00) 		0.753
(1.00) 		0.242
(1.00) 		0.313
(1.00) 		0.778
(1.00)
10q loss 0 (0%) 472 0.988
(1.00) 		0.331
(1.00) 		1
(1.00) 		0.809
(1.00) 		0.349
(1.00) 		0.00399
(1.00) 		1
(1.00)
11p loss 0 (0%) 418 0.66
(1.00) 		0.0347
(1.00) 		1
(1.00) 		0.741
(1.00) 		0.313
(1.00) 		1
(1.00) 		1
(1.00)
11q loss 0 (0%) 454 0.85
(1.00) 		0.143
(1.00) 		0.575
(1.00) 		0.17
(1.00) 		0.234
(1.00) 		0.473
(1.00) 		0.722
(1.00)
12p loss 0 (0%) 512 0.815
(1.00) 		0.117
(1.00) 		1
(1.00) 		0.113
(1.00) 		0.46
(1.00) 		1
(1.00)
12q loss 0 (0%) 488 0.295
(1.00) 		0.434
(1.00) 		1
(1.00) 		0.695
(1.00) 		0.348
(1.00) 		1
(1.00) 		1
(1.00)
13q loss 0 (0%) 305 0.302
(1.00) 		0.849
(1.00) 		0.458
(1.00) 		0.683
(1.00) 		0.00742
(1.00) 		1
(1.00) 		1
(1.00)
14q loss 0 (0%) 400 0.384
(1.00) 		0.123
(1.00) 		1
(1.00) 		0.706
(1.00) 		0.0695
(1.00) 		0.561
(1.00) 		0.457
(1.00)
15q loss 0 (0%) 346 0.77
(1.00) 		0.0496
(1.00) 		0.273
(1.00) 		0.65
(1.00) 		0.114
(1.00) 		0.562
(1.00) 		1
(1.00)
16p loss 0 (0%) 294 0.117
(1.00) 		0.97
(1.00) 		0.473
(1.00) 		0.259
(1.00) 		0.561
(1.00) 		0.608
(1.00) 		0.662
(1.00)
16q loss 0 (0%) 206 0.18
(1.00) 		0.00336
(1.00) 		0.782
(1.00) 		0.0536
(1.00) 		0.285
(1.00) 		1
(1.00) 		1
(1.00)
17p loss 0 (0%) 138 0.977
(1.00) 		0.0143
(1.00) 		0.255
(1.00) 		0.883
(1.00) 		0.486
(1.00) 		0.571
(1.00) 		0.47
(1.00)
17q loss 0 (0%) 234 0.45
(1.00) 		0.0573
(1.00) 		1
(1.00) 		0.0547
(1.00) 		0.747
(1.00) 		0.27
(1.00) 		0.584
(1.00)
18p loss 0 (0%) 379 0.433
(1.00) 		0.858
(1.00) 		0.795
(1.00) 		0.752
(1.00) 		1
(1.00) 		0.249
(1.00) 		0.875
(1.00)
18q loss 0 (0%) 329 0.467
(1.00) 		0.819
(1.00) 		0.765
(1.00) 		0.65
(1.00) 		0.377
(1.00) 		0.573
(1.00) 		0.869
(1.00)
19p loss 0 (0%) 419 0.907
(1.00) 		0.121
(1.00) 		0.691
(1.00) 		0.485
(1.00) 		0.583
(1.00) 		1
(1.00) 		0.139
(1.00)
19q loss 0 (0%) 419 0.732
(1.00) 		0.747
(1.00) 		0.691
(1.00) 		0.407
(1.00) 		0.507
(1.00) 		0.574
(1.00) 		0.195
(1.00)
20p loss 0 (0%) 525 0.0298
(1.00) 		0.205
(1.00) 		1
(1.00) 		0.00339
(1.00) 		0.819
(1.00) 		0.185
(1.00)
20q loss 0 (0%) 540 0.0399
(1.00) 		0.789
(1.00) 		1
(1.00) 		0.00339
(1.00) 		0.749
(1.00) 		1
(1.00)
21q loss 0 (0%) 414 0.75
(1.00) 		0.932
(1.00) 		1
(1.00) 		0.508
(1.00) 		0.867
(1.00) 		1
(1.00) 		0.423
(1.00)
22q loss 0 (0%) 177 0.231
(1.00) 		0.217
(1.00) 		0.382
(1.00) 		0.954
(1.00) 		0.86
(1.00) 		0.555
(1.00) 		0.179
(1.00)
Xq loss 0 (0%) 462 0.297
(1.00) 		0.72
(1.00) 		0.548
(1.00) 		0.485
(1.00) 		0.185
(1.00) 		1
(1.00) 		0.167
(1.00)
'2p gain' versus 'AGE'

P value = 2.45e-07 (t-test), Q value = 0.00013

Table S1.  Gene #3: '2p gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
2P GAIN CNV 122 64.5 (11.0)
2P GAIN WILD-TYPE 419 58.4 (11.4)

Figure S1.  Get High-res Image Gene #3: '2p gain' versus Clinical Feature #2: 'AGE'

'3q gain' versus 'AGE'

P value = 7.84e-07 (t-test), Q value = 0.00042

Table S2.  Gene #6: '3q gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
3Q GAIN CNV 199 63.0 (11.1)
3Q GAIN WILD-TYPE 342 57.9 (11.5)

Figure S2.  Get High-res Image Gene #6: '3q gain' versus Clinical Feature #2: 'AGE'

'10p gain' versus 'AGE'

P value = 1.17e-05 (t-test), Q value = 0.0061

Table S3.  Gene #19: '10p gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
10P GAIN CNV 126 63.6 (10.6)
10P GAIN WILD-TYPE 415 58.6 (11.7)

Figure S3.  Get High-res Image Gene #19: '10p gain' versus Clinical Feature #2: 'AGE'

'12p gain' versus 'AGE'

P value = 3.52e-08 (t-test), Q value = 1.9e-05

Table S4.  Gene #23: '12p gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
12P GAIN CNV 196 63.4 (11.2)
12P GAIN WILD-TYPE 345 57.7 (11.4)

Figure S4.  Get High-res Image Gene #23: '12p gain' versus Clinical Feature #2: 'AGE'

'12q gain' versus 'AGE'

P value = 1.49e-06 (t-test), Q value = 0.00079

Table S5.  Gene #24: '12q gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
12Q GAIN CNV 113 64.3 (10.7)
12Q GAIN WILD-TYPE 428 58.6 (11.6)

Figure S5.  Get High-res Image Gene #24: '12q gain' versus Clinical Feature #2: 'AGE'

'20p gain' versus 'AGE'

P value = 2.92e-06 (t-test), Q value = 0.0015

Table S6.  Gene #36: '20p gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
20P GAIN CNV 225 62.5 (11.4)
20P GAIN WILD-TYPE 316 57.8 (11.4)

Figure S6.  Get High-res Image Gene #36: '20p gain' versus Clinical Feature #2: 'AGE'

'20q gain' versus 'AGE'

P value = 1.27e-06 (t-test), Q value = 0.00067

Table S7.  Gene #37: '20q gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
20Q GAIN CNV 262 62.3 (11.7)
20Q GAIN WILD-TYPE 279 57.5 (11.0)

Figure S7.  Get High-res Image Gene #37: '20q gain' versus Clinical Feature #2: 'AGE'

'9q loss' versus 'AGE'

P value = 3.74e-06 (t-test), Q value = 0.002

Table S8.  Gene #58: '9q loss' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
9Q LOSS CNV 229 62.5 (11.3)
9Q LOSS WILD-TYPE 312 57.8 (11.5)

Figure S8.  Get High-res Image Gene #58: '9q loss' versus Clinical Feature #2: 'AGE'

Methods & Data
Input

  • Mutation data file = broad_values_by_arm.mutsig.cluster.txt

  • Clinical data file = OV-TP.clin.merged.picked.txt

  • Number of patients = 562

  • Number of significantly arm-level cnvs = 80

  • Number of selected clinical features = 7

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

Survival analysis

For survival clinical features, the Kaplan-Meier survival curves of tumors with and without gene mutations were plotted and the statistical significance P values were estimated by logrank test (Bland and Altman 2004) using the 'survdiff' function in R

Student's t-test analysis

For continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between tumors with and without gene mutations using 't.test' function in R

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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References
[1] Bland and Altman, Statistics notes: The logrank test, BMJ 328(7447):1073 (2004)
[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[3] 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)
[4] 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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