Correlation between copy number variations of arm-level result and selected clinical features
Ovarian Serous Cystadenocarcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1PV6HQS
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/C1PV6HQS
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 events and 6 clinical features across 562 patients, 14 significant findings detected with Q value < 0.25.

  • 1Q GAIN MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 2P GAIN MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 3Q GAIN MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 6P GAIN MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 6Q GAIN MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 7P GAIN MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 10P GAIN MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 12P GAIN MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 12Q GAIN MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 20P GAIN MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 20Q GAIN MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 9Q LOSS MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 15Q LOSS MUTATION ANALYSIS cnv correlated to 'AGE'.

  • 16Q LOSS MUTATION ANALYSIS 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 events and 6 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 14 significant findings detected.

Clinical
Features 		Time
to
Death 		AGE PRIMARY
SITE
OF
DISEASE 		KARNOFSKY
PERFORMANCE
SCORE 		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
1Q GAIN MUTATION ANALYSIS 215 (38%) 347 0.528
(1.00) 		0.00027
(0.124) 		0.263
(1.00) 		0.0938
(1.00) 		1
(1.00) 		1
(1.00)
2P GAIN MUTATION ANALYSIS 173 (31%) 389 0.143
(1.00) 		2.17e-06
(0.00101) 		1
(1.00) 		0.63
(1.00) 		1
(1.00) 		0.837
(1.00)
3Q GAIN MUTATION ANALYSIS 264 (47%) 298 0.673
(1.00) 		4.88e-08
(2.28e-05) 		0.173
(1.00) 		0.458
(1.00) 		0.251
(1.00) 		0.759
(1.00)
6P GAIN MUTATION ANALYSIS 159 (28%) 403 0.109
(1.00) 		0.000257
(0.118) 		0.739
(1.00) 		0.0228
(1.00) 		0.562
(1.00) 		1
(1.00)
6Q GAIN MUTATION ANALYSIS 92 (16%) 470 0.21
(1.00) 		0.000243
(0.112) 		1
(1.00) 		0.0798
(1.00) 		1
(1.00) 		0.741
(1.00)
7P GAIN MUTATION ANALYSIS 174 (31%) 388 0.57
(1.00) 		0.000412
(0.188) 		0.774
(1.00) 		0.0516
(1.00) 		0.556
(1.00) 		1
(1.00)
10P GAIN MUTATION ANALYSIS 178 (32%) 384 0.558
(1.00) 		7.92e-08
(3.7e-05) 		0.0979
(1.00) 		0.323
(1.00) 		0.237
(1.00) 		0.664
(1.00)
12P GAIN MUTATION ANALYSIS 244 (43%) 318 0.409
(1.00) 		4.83e-10
(2.27e-07) 		0.334
(1.00) 		0.0358
(1.00) 		1
(1.00) 		0.426
(1.00)
12Q GAIN MUTATION ANALYSIS 168 (30%) 394 0.0803
(1.00) 		1.85e-08
(8.67e-06) 		0.164
(1.00) 		0.0121
(1.00) 		1
(1.00) 		0.873
(1.00)
20P GAIN MUTATION ANALYSIS 277 (49%) 285 0.0176
(1.00) 		6.96e-06
(0.00323) 		0.494
(1.00) 		0.0983
(1.00) 		0.619
(1.00) 		0.875
(1.00)
20Q GAIN MUTATION ANALYSIS 320 (57%) 242 0.0356
(1.00) 		9.22e-06
(0.00426) 		0.759
(1.00) 		0.215
(1.00) 		1
(1.00) 		1
(1.00)
9Q LOSS MUTATION ANALYSIS 284 (51%) 278 0.227
(1.00) 		1.24e-07
(5.79e-05) 		0.749
(1.00) 		0.923
(1.00) 		1
(1.00) 		0.749
(1.00)
15Q LOSS MUTATION ANALYSIS 266 (47%) 296 0.18
(1.00) 		0.000176
(0.0809) 		0.473
(1.00) 		0.892
(1.00) 		0.605
(1.00) 		0.664
(1.00)
16Q LOSS MUTATION ANALYSIS 400 (71%) 162 0.0856
(1.00) 		8.33e-06
(0.00386) 		0.749
(1.00) 		0.152
(1.00) 		0.561
(1.00) 		1
(1.00)
1P GAIN MUTATION ANALYSIS 161 (29%) 401 0.447
(1.00) 		0.0873
(1.00) 		0.321
(1.00) 		0.212
(1.00) 		0.199
(1.00) 		0.299
(1.00)
2Q GAIN MUTATION ANALYSIS 142 (25%) 420 0.161
(1.00) 		0.000842
(0.384) 		1
(1.00) 		0.935
(1.00) 		0.159
(1.00) 		1
(1.00)
3P GAIN MUTATION ANALYSIS 155 (28%) 407 0.949
(1.00) 		0.008
(1.00) 		0.725
(1.00) 		0.485
(1.00) 		0.565
(1.00) 		0.217
(1.00)
4P GAIN MUTATION ANALYSIS 51 (9%) 511 0.0467
(1.00) 		0.117
(1.00) 		1
(1.00) 		0.515
(1.00) 		1
(1.00)
4Q GAIN MUTATION ANALYSIS 31 (6%) 531 0.0996
(1.00) 		0.0361
(1.00) 		1
(1.00) 		0.497
(1.00) 		1
(1.00)
5P GAIN MUTATION ANALYSIS 190 (34%) 372 0.226
(1.00) 		0.00648
(1.00) 		0.113
(1.00) 		0.607
(1.00) 		1
(1.00) 		0.0616
(1.00)
5Q GAIN MUTATION ANALYSIS 53 (9%) 509 0.382
(1.00) 		0.249
(1.00) 		0.322
(1.00) 		0.824
(1.00) 		1
(1.00) 		0.108
(1.00)
7Q GAIN MUTATION ANALYSIS 193 (34%) 369 0.317
(1.00) 		0.00274
(1.00) 		1
(1.00) 		0.0736
(1.00) 		0.555
(1.00) 		0.658
(1.00)
8P GAIN MUTATION ANALYSIS 119 (21%) 443 0.944
(1.00) 		0.899
(1.00) 		0.619
(1.00) 		0.91
(1.00) 		0.511
(1.00) 		0.797
(1.00)
8Q GAIN MUTATION ANALYSIS 238 (42%) 324 0.238
(1.00) 		0.165
(1.00) 		0.332
(1.00) 		0.41
(1.00) 		1
(1.00) 		0.152
(1.00)
9P GAIN MUTATION ANALYSIS 87 (15%) 475 0.825
(1.00) 		0.935
(1.00) 		1
(1.00) 		0.824
(1.00) 		0.397
(1.00) 		1
(1.00)
9Q GAIN MUTATION ANALYSIS 41 (7%) 521 0.715
(1.00) 		0.174
(1.00) 		1
(1.00) 		0.22
(1.00) 		0.204
(1.00) 		1
(1.00)
10Q GAIN MUTATION ANALYSIS 101 (18%) 461 0.745
(1.00) 		0.0024
(1.00) 		0.152
(1.00) 		0.809
(1.00) 		1
(1.00) 		1
(1.00)
11P GAIN MUTATION ANALYSIS 71 (13%) 491 0.0998
(1.00) 		0.242
(1.00) 		1
(1.00) 		0.341
(1.00) 		1
(1.00)
11Q GAIN MUTATION ANALYSIS 103 (18%) 459 0.992
(1.00) 		0.665
(1.00) 		1
(1.00) 		0.283
(1.00) 		1
(1.00) 		0.108
(1.00)
13Q GAIN MUTATION ANALYSIS 57 (10%) 505 0.662
(1.00) 		0.0108
(1.00) 		1
(1.00) 		0.296
(1.00) 		0.275
(1.00) 		0.675
(1.00)
14Q GAIN MUTATION ANALYSIS 56 (10%) 506 0.265
(1.00) 		0.319
(1.00) 		1
(1.00) 		0.742
(1.00) 		0.271
(1.00) 		0.722
(1.00)
15Q GAIN MUTATION ANALYSIS 39 (7%) 523 0.116
(1.00) 		0.744
(1.00) 		1
(1.00) 		0.0326
(1.00) 		1
(1.00) 		1
(1.00)
16P GAIN MUTATION ANALYSIS 58 (10%) 504 0.487
(1.00) 		0.332
(1.00) 		1
(1.00) 		0.181
(1.00) 		1
(1.00) 		0.277
(1.00)
16Q GAIN MUTATION ANALYSIS 31 (6%) 531 0.746
(1.00) 		0.675
(1.00) 		1
(1.00) 		1
(1.00) 		0.377
(1.00)
17P GAIN MUTATION ANALYSIS 21 (4%) 541 0.108
(1.00) 		0.848
(1.00) 		1
(1.00) 		0.921
(1.00) 		1
(1.00)
17Q GAIN MUTATION ANALYSIS 46 (8%) 516 0.436
(1.00) 		0.256
(1.00) 		1
(1.00) 		0.417
(1.00) 		1
(1.00) 		0.00697
(1.00)
18P GAIN MUTATION ANALYSIS 111 (20%) 451 0.129
(1.00) 		0.0128
(1.00) 		1
(1.00) 		0.733
(1.00) 		0.484
(1.00) 		1
(1.00)
18Q GAIN MUTATION ANALYSIS 65 (12%) 497 0.331
(1.00) 		0.241
(1.00) 		1
(1.00) 		0.69
(1.00) 		0.309
(1.00) 		0.722
(1.00)
19P GAIN MUTATION ANALYSIS 159 (28%) 403 0.469
(1.00) 		0.0673
(1.00) 		0.736
(1.00) 		0.662
(1.00) 		1
(1.00) 		0.859
(1.00)
19Q GAIN MUTATION ANALYSIS 153 (27%) 409 0.471
(1.00) 		0.00253
(1.00) 		0.144
(1.00) 		0.832
(1.00) 		1
(1.00) 		0.601
(1.00)
21Q GAIN MUTATION ANALYSIS 109 (19%) 453 0.44
(1.00) 		0.00147
(0.669) 		0.0719
(1.00) 		0.377
(1.00) 		1
(1.00) 		0.299
(1.00)
22Q GAIN MUTATION ANALYSIS 22 (4%) 540 0.109
(1.00) 		0.494
(1.00) 		1
(1.00) 		0.00338
(1.00) 		1
(1.00) 		1
(1.00)
XQ GAIN MUTATION ANALYSIS 117 (21%) 445 0.459
(1.00) 		0.0416
(1.00) 		0.0858
(1.00) 		0.918
(1.00) 		1
(1.00) 		1
(1.00)
1P LOSS MUTATION ANALYSIS 62 (11%) 500 0.987
(1.00) 		0.352
(1.00) 		1
(1.00) 		0.331
(1.00) 		0.296
(1.00) 		1
(1.00)
1Q LOSS MUTATION ANALYSIS 39 (7%) 523 0.766
(1.00) 		0.318
(1.00) 		1
(1.00) 		0.498
(1.00) 		0.194
(1.00)
2P LOSS MUTATION ANALYSIS 52 (9%) 510 0.77
(1.00) 		0.731
(1.00) 		1
(1.00) 		0.05
(1.00) 		1
(1.00)
2Q LOSS MUTATION ANALYSIS 59 (10%) 503 0.94
(1.00) 		0.0813
(1.00) 		0.359
(1.00) 		0.05
(1.00) 		1
(1.00) 		1
(1.00)
3P LOSS MUTATION ANALYSIS 98 (17%) 464 0.988
(1.00) 		0.00263
(1.00) 		0.539
(1.00) 		0.386
(1.00) 		0.438
(1.00) 		0.0386
(1.00)
3Q LOSS MUTATION ANALYSIS 44 (8%) 518 0.703
(1.00) 		0.351
(1.00) 		0.283
(1.00) 		0.753
(1.00) 		0.217
(1.00)
4P LOSS MUTATION ANALYSIS 304 (54%) 258 0.784
(1.00) 		0.932
(1.00) 		0.171
(1.00) 		0.244
(1.00) 		1
(1.00) 		0.293
(1.00)
4Q LOSS MUTATION ANALYSIS 345 (61%) 217 0.626
(1.00) 		0.496
(1.00) 		0.772
(1.00) 		0.832
(1.00) 		1
(1.00) 		0.349
(1.00)
5P LOSS MUTATION ANALYSIS 128 (23%) 434 0.803
(1.00) 		0.0129
(1.00) 		0.646
(1.00) 		0.0397
(1.00) 		1
(1.00) 		0.741
(1.00)
5Q LOSS MUTATION ANALYSIS 215 (38%) 347 0.519
(1.00) 		0.0131
(1.00) 		1
(1.00) 		0.144
(1.00) 		1
(1.00) 		0.741
(1.00)
6P LOSS MUTATION ANALYSIS 162 (29%) 400 0.219
(1.00) 		0.201
(1.00) 		0.744
(1.00) 		0.853
(1.00) 		1
(1.00) 		0.493
(1.00)
6Q LOSS MUTATION ANALYSIS 236 (42%) 326 0.654
(1.00) 		0.154
(1.00) 		0.15
(1.00) 		0.68
(1.00) 		1
(1.00) 		1
(1.00)
7P LOSS MUTATION ANALYSIS 113 (20%) 449 0.792
(1.00) 		0.759
(1.00) 		0.594
(1.00) 		0.0604
(1.00) 		1
(1.00) 		0.0692
(1.00)
7Q LOSS MUTATION ANALYSIS 77 (14%) 485 0.264
(1.00) 		0.2
(1.00) 		0.453
(1.00) 		0.0326
(1.00) 		0.358
(1.00) 		0.051
(1.00)
8P LOSS MUTATION ANALYSIS 264 (47%) 298 0.0823
(1.00) 		0.0691
(1.00) 		0.172
(1.00) 		0.0977
(1.00) 		1
(1.00) 		0.339
(1.00)
8Q LOSS MUTATION ANALYSIS 85 (15%) 477 0.0846
(1.00) 		0.11
(1.00) 		1
(1.00) 		0.126
(1.00) 		1
(1.00) 		0.741
(1.00)
9P LOSS MUTATION ANALYSIS 259 (46%) 303 0.573
(1.00) 		0.00707
(1.00) 		0.461
(1.00) 		0.351
(1.00) 		0.597
(1.00) 		0.382
(1.00)
10P LOSS MUTATION ANALYSIS 95 (17%) 467 0.862
(1.00) 		0.261
(1.00) 		1
(1.00) 		0.876
(1.00) 		0.427
(1.00) 		0.62
(1.00)
10Q LOSS MUTATION ANALYSIS 123 (22%) 439 0.901
(1.00) 		0.135
(1.00) 		0.623
(1.00) 		0.948
(1.00) 		0.0103
(1.00) 		0.837
(1.00)
11P LOSS MUTATION ANALYSIS 191 (34%) 371 0.73
(1.00) 		0.00606
(1.00) 		1
(1.00) 		0.72
(1.00) 		1
(1.00) 		0.44
(1.00)
11Q LOSS MUTATION ANALYSIS 151 (27%) 411 0.949
(1.00) 		0.0355
(1.00) 		0.292
(1.00) 		0.588
(1.00) 		1
(1.00) 		0.47
(1.00)
12P LOSS MUTATION ANALYSIS 81 (14%) 481 0.817
(1.00) 		0.0697
(1.00) 		1
(1.00) 		0.287
(1.00) 		1
(1.00) 		0.722
(1.00)
12Q LOSS MUTATION ANALYSIS 103 (18%) 459 0.265
(1.00) 		0.371
(1.00) 		1
(1.00) 		0.903
(1.00) 		1
(1.00) 		1
(1.00)
13Q LOSS MUTATION ANALYSIS 299 (53%) 263 0.45
(1.00) 		0.291
(1.00) 		0.751
(1.00) 		0.622
(1.00) 		0.602
(1.00) 		0.645
(1.00)
14Q LOSS MUTATION ANALYSIS 205 (36%) 357 0.555
(1.00) 		0.00286
(1.00) 		0.786
(1.00) 		0.348
(1.00) 		0.557
(1.00) 		0.253
(1.00)
16P LOSS MUTATION ANALYSIS 323 (57%) 239 0.241
(1.00) 		0.145
(1.00) 		0.759
(1.00) 		0.866
(1.00) 		0.265
(1.00) 		0.87
(1.00)
17P LOSS MUTATION ANALYSIS 465 (83%) 97 0.782
(1.00) 		0.354
(1.00) 		0.531
(1.00) 		0.862
(1.00) 		0.434
(1.00) 		0.329
(1.00)
17Q LOSS MUTATION ANALYSIS 364 (65%) 198 0.591
(1.00) 		0.604
(1.00) 		0.79
(1.00) 		0.0108
(1.00) 		0.555
(1.00) 		0.443
(1.00)
18P LOSS MUTATION ANALYSIS 225 (40%) 337 0.0193
(1.00) 		0.884
(1.00) 		0.768
(1.00) 		0.918
(1.00) 		0.567
(1.00) 		1
(1.00)
18Q LOSS MUTATION ANALYSIS 280 (50%) 282 0.0668
(1.00) 		0.516
(1.00) 		0.749
(1.00) 		0.952
(1.00) 		0.623
(1.00) 		1
(1.00)
19P LOSS MUTATION ANALYSIS 181 (32%) 381 0.321
(1.00) 		0.00691
(1.00) 		0.79
(1.00) 		0.774
(1.00) 		1
(1.00) 		0.363
(1.00)
19Q LOSS MUTATION ANALYSIS 170 (30%) 392 0.967
(1.00) 		0.296
(1.00) 		0.174
(1.00) 		0.232
(1.00) 		0.557
(1.00) 		0.217
(1.00)
20P LOSS MUTATION ANALYSIS 50 (9%) 512 0.102
(1.00) 		0.321
(1.00) 		1
(1.00) 		0.0528
(1.00) 		0.244
(1.00)
20Q LOSS MUTATION ANALYSIS 31 (6%) 531 0.0955
(1.00) 		0.845
(1.00) 		1
(1.00) 		0.0851
(1.00) 		1
(1.00)
21Q LOSS MUTATION ANALYSIS 189 (34%) 373 0.825
(1.00) 		0.293
(1.00) 		0.8
(1.00) 		0.365
(1.00) 		1
(1.00) 		1
(1.00)
22Q LOSS MUTATION ANALYSIS 416 (74%) 146 0.144
(1.00) 		0.0598
(1.00) 		0.283
(1.00) 		0.862
(1.00) 		0.572
(1.00) 		0.133
(1.00)
XQ LOSS MUTATION ANALYSIS 281 (50%) 281 0.814
(1.00) 		0.00357
(1.00) 		0.749
(1.00) 		0.738
(1.00) 		0.249
(1.00) 		0.867
(1.00)
'1Q GAIN MUTATION STATUS' versus 'AGE'

P value = 0.00027 (t-test), Q value = 0.12

Table S1.  Gene #2: '1Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
1Q GAIN MUTATED 205 62.1 (10.9)
1Q GAIN WILD-TYPE 336 58.4 (11.8)

Figure S1.  Get High-res Image Gene #2: '1Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'2P GAIN MUTATION STATUS' versus 'AGE'

P value = 2.17e-06 (t-test), Q value = 0.001

Table S2.  Gene #3: '2P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
2P GAIN MUTATED 164 63.3 (11.1)
2P GAIN WILD-TYPE 377 58.3 (11.5)

Figure S2.  Get High-res Image Gene #3: '2P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'3Q GAIN MUTATION STATUS' versus 'AGE'

P value = 4.88e-08 (t-test), Q value = 2.3e-05

Table S3.  Gene #6: '3Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
3Q GAIN MUTATED 256 62.6 (11.2)
3Q GAIN WILD-TYPE 285 57.2 (11.4)

Figure S3.  Get High-res Image Gene #6: '3Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'6P GAIN MUTATION STATUS' versus 'AGE'

P value = 0.000257 (t-test), Q value = 0.12

Table S4.  Gene #11: '6P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
6P GAIN MUTATED 156 62.6 (11.1)
6P GAIN WILD-TYPE 385 58.6 (11.6)

Figure S4.  Get High-res Image Gene #11: '6P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'6Q GAIN MUTATION STATUS' versus 'AGE'

P value = 0.000243 (t-test), Q value = 0.11

Table S5.  Gene #12: '6Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
6Q GAIN MUTATED 89 63.8 (10.7)
6Q GAIN WILD-TYPE 452 59.0 (11.6)

Figure S5.  Get High-res Image Gene #12: '6Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'7P GAIN MUTATION STATUS' versus 'AGE'

P value = 0.000412 (t-test), Q value = 0.19

Table S6.  Gene #13: '7P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
7P GAIN MUTATED 166 62.4 (11.0)
7P GAIN WILD-TYPE 375 58.6 (11.7)

Figure S6.  Get High-res Image Gene #13: '7P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'10P GAIN MUTATION STATUS' versus 'AGE'

P value = 7.92e-08 (t-test), Q value = 3.7e-05

Table S7.  Gene #19: '10P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
10P GAIN MUTATED 172 63.6 (11.0)
10P GAIN WILD-TYPE 369 58.0 (11.5)

Figure S7.  Get High-res Image Gene #19: '10P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'12P GAIN MUTATION STATUS' versus 'AGE'

P value = 4.83e-10 (t-test), Q value = 2.3e-07

Table S8.  Gene #23: '12P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
12P GAIN MUTATED 231 63.3 (11.1)
12P GAIN WILD-TYPE 310 57.2 (11.3)

Figure S8.  Get High-res Image Gene #23: '12P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'12Q GAIN MUTATION STATUS' versus 'AGE'

P value = 1.85e-08 (t-test), Q value = 8.7e-06

Table S9.  Gene #24: '12Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
12Q GAIN MUTATED 158 63.9 (10.4)
12Q GAIN WILD-TYPE 383 58.1 (11.7)

Figure S9.  Get High-res Image Gene #24: '12Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'20P GAIN MUTATION STATUS' versus 'AGE'

P value = 6.96e-06 (t-test), Q value = 0.0032

Table S10.  Gene #36: '20P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
20P GAIN MUTATED 268 62.0 (11.6)
20P GAIN WILD-TYPE 273 57.6 (11.2)

Figure S10.  Get High-res Image Gene #36: '20P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'20Q GAIN MUTATION STATUS' versus 'AGE'

P value = 9.22e-06 (t-test), Q value = 0.0043

Table S11.  Gene #37: '20Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
20Q GAIN MUTATED 309 61.7 (11.9)
20Q GAIN WILD-TYPE 232 57.3 (10.8)

Figure S11.  Get High-res Image Gene #37: '20Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'9Q LOSS MUTATION STATUS' versus 'AGE'

P value = 1.24e-07 (t-test), Q value = 5.8e-05

Table S12.  Gene #58: '9Q LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
9Q LOSS MUTATED 270 62.4 (11.3)
9Q LOSS WILD-TYPE 271 57.2 (11.4)

Figure S12.  Get High-res Image Gene #58: '9Q LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'15Q LOSS MUTATION STATUS' versus 'AGE'

P value = 0.000176 (t-test), Q value = 0.081

Table S13.  Gene #67: '15Q LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
15Q LOSS MUTATED 258 61.7 (11.4)
15Q LOSS WILD-TYPE 283 58.0 (11.5)

Figure S13.  Get High-res Image Gene #67: '15Q LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'16Q LOSS MUTATION STATUS' versus 'AGE'

P value = 8.33e-06 (t-test), Q value = 0.0039

Table S14.  Gene #69: '16Q LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 541 59.8 (11.6)
16Q LOSS MUTATED 385 61.2 (11.4)
16Q LOSS WILD-TYPE 156 56.3 (11.3)

Figure S14.  Get High-res Image Gene #69: '16Q LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

Methods & Data
Input

  • Copy number data file = transformed.cor.cli.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 = 6

  • Exclude regions 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

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] 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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