Correlation between copy number variations of arm-level result and selected clinical features
Bladder Urothelial Carcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C1M906NR
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/C1M906NR
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 75 arm-level results and 10 clinical features across 134 patients, 8 significant findings detected with Q value < 0.25.

  • 2p gain cnv correlated to 'GENDER'.

  • 4p gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

  • 5q gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

  • 9q gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

  • 14q gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

  • 16p gain cnv correlated to 'Time to Death'.

  • 16q gain cnv correlated to 'Time to Death'.

  • 17p gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 75 arm-level results and 10 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 GENDER KARNOFSKY
PERFORMANCE
SCORE 		NUMBERPACKYEARSSMOKED DISTANT
METASTASIS 		LYMPH
NODE
METASTASIS 		NUMBER
OF
LYMPH
NODES 		TUMOR
STAGECODE 		NEOPLASM
DISEASESTAGE
nCNV (%) nWild-Type logrank test t-test Fisher's exact test t-test t-test Fisher's exact test Chi-square test t-test t-test Fisher's exact test
2p gain 0 (0%) 107 0.735
(1.00) 		0.328
(1.00) 		0.000283
(0.182) 		0.936
(1.00) 		0.841
(1.00) 		0.675
(1.00) 		0.469
(1.00) 		0.556
(1.00) 		0.642
(1.00)
4p gain 0 (0%) 126 0.0898
(1.00) 		0.784
(1.00) 		0.679
(1.00) 		0.369
(1.00) 		0.239
(1.00) 		0.39
(1.00) 		0.000194
(0.125) 		0.263
(1.00)
5q gain 0 (0%) 117 0.355
(1.00) 		0.511
(1.00) 		0.237
(1.00) 		0.273
(1.00) 		0.886
(1.00) 		1
(1.00) 		0.0776
(1.00) 		9.26e-05
(0.0598) 		0.0512
(1.00)
9q gain 0 (0%) 122 0.0822
(1.00) 		0.169
(1.00) 		0.499
(1.00) 		0.796
(1.00) 		0.182
(1.00) 		0.203
(1.00) 		0.117
(1.00) 		2.3e-06
(0.00149) 		0.00102
(0.651)
14q gain 0 (0%) 123 0.946
(1.00) 		0.591
(1.00) 		0.469
(1.00) 		0.487
(1.00) 		0.32
(1.00) 		0.483
(1.00) 		0.393
(1.00) 		6.54e-05
(0.0423) 		0.437
(1.00)
16p gain 0 (0%) 125 6.44e-07
(0.000419) 		0.454
(1.00) 		0.231
(1.00) 		0.458
(1.00) 		0.207
(1.00) 		0.0949
(1.00) 		0.816
(1.00) 		0.0707
(1.00) 		0.554
(1.00)
16q gain 0 (0%) 122 6.18e-05
(0.04) 		0.292
(1.00) 		0.0745
(1.00) 		0.48
(1.00) 		0.424
(1.00) 		0.404
(1.00) 		0.688
(1.00) 		0.0545
(1.00) 		0.768
(1.00)
17p gain 0 (0%) 127 0.0468
(1.00) 		0.946
(1.00) 		0.369
(1.00) 		0.992
(1.00) 		0.327
(1.00) 		0.63
(1.00) 		2.43e-06
(0.00158) 		0.0206
(1.00)
1p gain 0 (0%) 118 0.0182
(1.00) 		0.82
(1.00) 		0.551
(1.00) 		0.731
(1.00) 		0.517
(1.00) 		0.698
(1.00) 		0.0776
(1.00) 		0.539
(1.00) 		0.29
(1.00)
1q gain 0 (0%) 103 0.00755
(1.00) 		0.0539
(1.00) 		1
(1.00) 		0.408
(1.00) 		0.692
(1.00) 		0.149
(1.00) 		0.0693
(1.00) 		0.821
(1.00) 		0.162
(1.00)
2q gain 0 (0%) 124 0.596
(1.00) 		0.594
(1.00) 		0.714
(1.00) 		0.238
(1.00) 		0.426
(1.00) 		0.637
(1.00) 		0.315
(1.00) 		0.314
(1.00) 		0.12
(1.00)
3p gain 0 (0%) 106 0.994
(1.00) 		0.407
(1.00) 		0.634
(1.00) 		0.514
(1.00) 		0.907
(1.00) 		0.927
(1.00) 		0.115
(1.00) 		0.248
(1.00) 		0.0213
(1.00)
3q gain 0 (0%) 95 0.279
(1.00) 		0.325
(1.00) 		0.194
(1.00) 		0.778
(1.00) 		0.86
(1.00) 		0.272
(1.00) 		0.107
(1.00) 		0.255
(1.00) 		0.099
(1.00)
4q gain 0 (0%) 131 0.301
(1.00) 		0.53
(1.00) 		1
(1.00) 		0.274
(1.00) 		1
(1.00) 		0.682
(1.00) 		0.394
(1.00)
5p gain 0 (0%) 95 0.549
(1.00) 		0.414
(1.00) 		0.514
(1.00) 		0.161
(1.00) 		0.642
(1.00) 		1
(1.00) 		0.0036
(1.00) 		0.324
(1.00) 		0.421
(1.00)
6p gain 0 (0%) 124 0.492
(1.00) 		0.605
(1.00) 		1
(1.00) 		0.63
(1.00) 		0.701
(1.00) 		1
(1.00) 		0.197
(1.00) 		0.127
(1.00) 		0.789
(1.00)
6q gain 0 (0%) 129 0.104
(1.00) 		0.927
(1.00) 		0.329
(1.00) 		0.807
(1.00) 		0.71
(1.00) 		0.00808
(1.00) 		0.0065
(1.00) 		0.46
(1.00)
7p gain 0 (0%) 94 0.436
(1.00) 		0.201
(1.00) 		0.516
(1.00) 		0.111
(1.00) 		0.45
(1.00) 		0.38
(1.00) 		0.637
(1.00) 		0.847
(1.00) 		0.217
(1.00)
7q gain 0 (0%) 98 0.273
(1.00) 		0.508
(1.00) 		0.0428
(1.00) 		0.111
(1.00) 		0.219
(1.00) 		0.528
(1.00) 		0.427
(1.00) 		0.565
(1.00) 		0.275
(1.00)
8p gain 0 (0%) 119 0.728
(1.00) 		0.325
(1.00) 		0.76
(1.00) 		0.7
(1.00) 		0.182
(1.00) 		0.88
(1.00) 		0.678
(1.00) 		0.00571
(1.00) 		0.756
(1.00)
8q gain 0 (0%) 93 0.672
(1.00) 		0.832
(1.00) 		1
(1.00) 		0.818
(1.00) 		0.347
(1.00) 		0.484
(1.00) 		0.912
(1.00) 		0.148
(1.00) 		0.317
(1.00)
9p gain 0 (0%) 121 0.0366
(1.00) 		0.0212
(1.00) 		0.183
(1.00) 		0.825
(1.00) 		0.0302
(1.00) 		0.398
(1.00) 		0.695
(1.00) 		0.0016
(1.00) 		0.0944
(1.00)
10p gain 0 (0%) 109 0.83
(1.00) 		0.939
(1.00) 		0.615
(1.00) 		0.76
(1.00) 		0.524
(1.00) 		0.556
(1.00) 		0.358
(1.00) 		0.65
(1.00) 		0.0713
(1.00)
10q gain 0 (0%) 127 0.423
(1.00) 		0.108
(1.00) 		1
(1.00) 		0.672
(1.00) 		0.424
(1.00) 		0.207
(1.00) 		0.532
(1.00) 		0.274
(1.00)
11p gain 0 (0%) 128 0.0631
(1.00) 		0.102
(1.00) 		0.337
(1.00) 		0.0776
(1.00) 		0.602
(1.00) 		0.748
(1.00) 		0.384
(1.00) 		0.104
(1.00) 		0.529
(1.00)
11q gain 0 (0%) 126 0.264
(1.00) 		0.645
(1.00) 		0.202
(1.00) 		0.663
(1.00) 		0.918
(1.00) 		1
(1.00) 		0.116
(1.00) 		0.305
(1.00) 		0.383
(1.00)
12p gain 0 (0%) 109 0.786
(1.00) 		0.641
(1.00) 		0.8
(1.00) 		0.26
(1.00) 		0.862
(1.00) 		0.785
(1.00) 		0.861
(1.00) 		0.00736
(1.00) 		0.166
(1.00)
12q gain 0 (0%) 116 0.198
(1.00) 		0.559
(1.00) 		0.561
(1.00) 		0.358
(1.00) 		0.415
(1.00) 		0.32
(1.00) 		0.747
(1.00) 		0.0542
(1.00) 		0.0445
(1.00)
13q gain 0 (0%) 112 0.773
(1.00) 		0.707
(1.00) 		0.794
(1.00) 		0.602
(1.00) 		0.189
(1.00) 		0.28
(1.00) 		0.661
(1.00) 		0.975
(1.00) 		0.778
(1.00)
15q gain 0 (0%) 130 0.0949
(1.00) 		0.846
(1.00) 		1
(1.00) 		0.272
(1.00) 		0.613
(1.00) 		0.911
(1.00) 		1
(1.00)
17q gain 0 (0%) 111 0.805
(1.00) 		0.853
(1.00) 		1
(1.00) 		0.217
(1.00) 		0.504
(1.00) 		0.36
(1.00) 		0.104
(1.00) 		0.908
(1.00) 		0.0503
(1.00)
18p gain 0 (0%) 112 0.723
(1.00) 		0.879
(1.00) 		0.434
(1.00) 		0.451
(1.00) 		0.467
(1.00) 		0.449
(1.00) 		0.458
(1.00) 		0.739
(1.00) 		0.828
(1.00)
18q gain 0 (0%) 127 0.0328
(1.00) 		0.755
(1.00) 		1
(1.00) 		0.815
(1.00) 		0.257
(1.00) 		0.884
(1.00) 		0.276
(1.00) 		0.803
(1.00)
19p gain 0 (0%) 123 0.108
(1.00) 		0.853
(1.00) 		0.729
(1.00) 		0.238
(1.00) 		0.362
(1.00) 		1
(1.00) 		0.845
(1.00) 		0.0498
(1.00) 		0.314
(1.00)
19q gain 0 (0%) 109 0.345
(1.00) 		0.951
(1.00) 		0.205
(1.00) 		0.319
(1.00) 		0.473
(1.00) 		0.852
(1.00) 		0.992
(1.00) 		0.635
(1.00) 		0.582
(1.00)
20p gain 0 (0%) 84 0.157
(1.00) 		0.917
(1.00) 		0.219
(1.00) 		0.693
(1.00) 		0.428
(1.00) 		0.0958
(1.00) 		0.762
(1.00) 		0.396
(1.00) 		0.471
(1.00)
20q gain 0 (0%) 79 0.931
(1.00) 		0.441
(1.00) 		0.84
(1.00) 		0.533
(1.00) 		0.269
(1.00) 		0.704
(1.00) 		0.925
(1.00) 		0.431
(1.00) 		0.315
(1.00)
21q gain 0 (0%) 108 0.341
(1.00) 		0.535
(1.00) 		0.807
(1.00) 		0.981
(1.00) 		0.693
(1.00) 		0.729
(1.00) 		0.13
(1.00) 		0.834
(1.00) 		0.0409
(1.00)
22q gain 0 (0%) 123 0.0752
(1.00) 		0.518
(1.00) 		0.729
(1.00) 		0.584
(1.00) 		0.466
(1.00) 		0.841
(1.00) 		0.293
(1.00) 		0.555
(1.00) 		0.789
(1.00)
Xq gain 0 (0%) 128 0.0344
(1.00) 		0.737
(1.00) 		0.643
(1.00) 		0.492
(1.00) 		0.379
(1.00) 		0.161
(1.00) 		0.0968
(1.00) 		0.529
(1.00)
1p loss 0 (0%) 131 0.66
(1.00) 		0.826
(1.00) 		0.571
(1.00) 		0.184
(1.00) 		0.109
(1.00) 		0.0873
(1.00) 		0.782
(1.00)
2p loss 0 (0%) 126 0.622
(1.00) 		0.581
(1.00) 		0.679
(1.00) 		0.86
(1.00) 		0.302
(1.00) 		0.303
(1.00) 		0.205
(1.00) 		0.322
(1.00)
2q loss 0 (0%) 118 0.0294
(1.00) 		0.791
(1.00) 		0.357
(1.00) 		0.912
(1.00) 		0.191
(1.00) 		0.89
(1.00) 		0.0155
(1.00) 		0.123
(1.00) 		0.2
(1.00)
3p loss 0 (0%) 125 0.968
(1.00) 		0.603
(1.00) 		0.231
(1.00) 		0.475
(1.00) 		1
(1.00) 		0.676
(1.00) 		0.852
(1.00) 		0.92
(1.00)
4p loss 0 (0%) 108 0.427
(1.00) 		0.835
(1.00) 		1
(1.00) 		0.205
(1.00) 		0.473
(1.00) 		0.343
(1.00) 		0.0423
(1.00) 		0.25
(1.00) 		0.273
(1.00)
4q loss 0 (0%) 110 0.729
(1.00) 		0.828
(1.00) 		0.796
(1.00) 		0.0822
(1.00) 		0.854
(1.00) 		0.283
(1.00) 		0.891
(1.00) 		0.793
(1.00) 		0.567
(1.00)
5p loss 0 (0%) 121 0.109
(1.00) 		0.368
(1.00) 		0.0927
(1.00) 		0.0916
(1.00) 		0.849
(1.00) 		0.517
(1.00) 		0.927
(1.00) 		0.799
(1.00) 		0.436
(1.00)
5q loss 0 (0%) 102 0.537
(1.00) 		0.587
(1.00) 		0.816
(1.00) 		0.285
(1.00) 		0.243
(1.00) 		0.0541
(1.00) 		0.133
(1.00) 		0.325
(1.00) 		0.227
(1.00)
6p loss 0 (0%) 115 0.859
(1.00) 		0.594
(1.00) 		1
(1.00) 		0.0916
(1.00) 		0.599
(1.00) 		0.743
(1.00) 		0.0159
(1.00) 		0.269
(1.00) 		0.00639
(1.00)
6q loss 0 (0%) 106 0.44
(1.00) 		0.723
(1.00) 		0.634
(1.00) 		0.204
(1.00) 		0.329
(1.00) 		0.243
(1.00) 		0.146
(1.00) 		0.272
(1.00) 		0.0447
(1.00)
8p loss 0 (0%) 88 0.317
(1.00) 		0.57
(1.00) 		0.302
(1.00) 		0.37
(1.00) 		0.13
(1.00) 		0.246
(1.00) 		0.369
(1.00) 		0.891
(1.00) 		0.352
(1.00)
8q loss 0 (0%) 128 0.913
(1.00) 		0.0889
(1.00) 		0.643
(1.00) 		0.835
(1.00) 		0.273
(1.00) 		0.691
(1.00) 		0.908
(1.00) 		0.252
(1.00)
9p loss 0 (0%) 95 0.673
(1.00) 		0.546
(1.00) 		0.514
(1.00) 		0.403
(1.00) 		0.36
(1.00) 		0.14
(1.00) 		0.636
(1.00) 		0.972
(1.00) 		0.787
(1.00)
9q loss 0 (0%) 98 0.777
(1.00) 		0.974
(1.00) 		0.185
(1.00) 		0.694
(1.00) 		0.179
(1.00) 		0.601
(1.00) 		0.529
(1.00) 		0.07
(1.00) 		0.576
(1.00)
10p loss 0 (0%) 115 0.453
(1.00) 		0.992
(1.00) 		0.78
(1.00) 		0.0143
(1.00) 		0.887
(1.00) 		0.103
(1.00) 		0.898
(1.00) 		0.0426
(1.00) 		0.78
(1.00)
10q loss 0 (0%) 106 0.212
(1.00) 		0.0214
(1.00) 		0.634
(1.00) 		0.12
(1.00) 		0.923
(1.00) 		0.498
(1.00) 		0.944
(1.00) 		0.763
(1.00) 		0.798
(1.00)
11p loss 0 (0%) 90 0.716
(1.00) 		0.232
(1.00) 		1
(1.00) 		0.106
(1.00) 		0.992
(1.00) 		0.0242
(1.00) 		0.583
(1.00) 		0.228
(1.00) 		0.0167
(1.00)
11q loss 0 (0%) 103 0.911
(1.00) 		0.549
(1.00) 		0.816
(1.00) 		0.75
(1.00) 		0.301
(1.00) 		0.401
(1.00) 		0.212
(1.00) 		0.269
(1.00) 		0.387
(1.00)
12p loss 0 (0%) 129 0.974
(1.00) 		0.279
(1.00) 		0.329
(1.00) 		0.708
(1.00) 		1
(1.00) 		0.748
(1.00) 		0.887
(1.00) 		0.86
(1.00)
12q loss 0 (0%) 128 0.155
(1.00) 		0.283
(1.00) 		0.337
(1.00) 		0.886
(1.00) 		0.748
(1.00) 		0.0801
(1.00) 		0.461
(1.00) 		0.193
(1.00)
13q loss 0 (0%) 116 0.852
(1.00) 		0.744
(1.00) 		0.159
(1.00) 		0.0136
(1.00) 		0.686
(1.00) 		0.815
(1.00) 		0.787
(1.00) 		0.595
(1.00) 		0.533
(1.00)
14q loss 0 (0%) 111 0.109
(1.00) 		0.196
(1.00) 		0.435
(1.00) 		0.748
(1.00) 		0.624
(1.00) 		0.518
(1.00) 		0.609
(1.00) 		0.757
(1.00) 		0.318
(1.00)
15q loss 0 (0%) 119 0.46
(1.00) 		0.891
(1.00) 		0.53
(1.00) 		0.738
(1.00) 		0.849
(1.00) 		0.151
(1.00) 		0.938
(1.00) 		0.958
(1.00) 		0.673
(1.00)
16p loss 0 (0%) 119 0.643
(1.00) 		0.485
(1.00) 		0.114
(1.00) 		0.217
(1.00) 		0.509
(1.00) 		0.88
(1.00) 		0.568
(1.00) 		0.952
(1.00) 		0.673
(1.00)
16q loss 0 (0%) 118 0.566
(1.00) 		0.657
(1.00) 		0.357
(1.00) 		0.36
(1.00) 		0.876
(1.00) 		0.89
(1.00) 		0.107
(1.00) 		0.33
(1.00) 		0.427
(1.00)
17p loss 0 (0%) 96 0.373
(1.00) 		0.485
(1.00) 		1
(1.00) 		0.8
(1.00) 		0.366
(1.00) 		0.537
(1.00) 		0.864
(1.00) 		0.792
(1.00) 		0.687
(1.00)
17q loss 0 (0%) 128 0.845
(1.00) 		0.323
(1.00) 		1
(1.00) 		0.745
(1.00) 		0.349
(1.00) 		0.273
(1.00) 		0.0134
(1.00) 		0.529
(1.00)
18p loss 0 (0%) 115 0.454
(1.00) 		0.0309
(1.00) 		0.571
(1.00) 		0.228
(1.00) 		0.615
(1.00) 		0.6
(1.00) 		0.704
(1.00) 		0.873
(1.00) 		0.476
(1.00)
18q loss 0 (0%) 99 0.046
(1.00) 		0.033
(1.00) 		0.0733
(1.00) 		0.608
(1.00) 		0.292
(1.00) 		0.639
(1.00) 		0.848
(1.00) 		0.883
(1.00) 		0.379
(1.00)
19p loss 0 (0%) 125 0.374
(1.00) 		0.727
(1.00) 		1
(1.00) 		0.941
(1.00) 		0.000749
(0.481) 		0.00196
(1.00) 		0.263
(1.00) 		0.00884
(1.00)
19q loss 0 (0%) 130 0.00146
(0.935) 		0.934
(1.00) 		0.572
(1.00) 		0.402
(1.00) 		0.104
(1.00) 		0.15
(1.00) 		0.688
(1.00) 		0.471
(1.00)
20p loss 0 (0%) 128 0.607
(1.00) 		0.275
(1.00) 		0.643
(1.00) 		0.00282
(1.00) 		0.71
(1.00) 		0.882
(1.00) 		0.72
(1.00) 		0.599
(1.00)
21q loss 0 (0%) 121 0.975
(1.00) 		0.000675
(0.434) 		1
(1.00) 		0.000926
(0.594) 		0.869
(1.00) 		0.471
(1.00) 		0.114
(1.00) 		0.609
(1.00) 		0.433
(1.00)
22q loss 0 (0%) 108 0.101
(1.00) 		0.757
(1.00) 		0.807
(1.00) 		0.34
(1.00) 		0.726
(1.00) 		0.268
(1.00) 		0.398
(1.00) 		0.653
(1.00) 		0.499
(1.00)
Xq loss 0 (0%) 131 0.332
(1.00) 		0.886
(1.00) 		1
(1.00) 		0.344
(1.00) 		0.611
(1.00) 		0.0437
(1.00)
'2p gain' versus 'GENDER'

P value = 0.000283 (Fisher's exact test), Q value = 0.18

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

nPatients FEMALE MALE
ALL 34 100
2P GAIN CNV 15 12
2P GAIN WILD-TYPE 19 88

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

'4p gain' versus 'NUMBER.OF.LYMPH.NODES'

P value = 0.000194 (t-test), Q value = 0.13

Table S2.  Gene #7: '4p gain' versus Clinical Feature #8: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 100 1.9 (3.7)
4P GAIN CNV 5 0.2 (0.4)
4P GAIN WILD-TYPE 95 1.9 (3.8)

Figure S2.  Get High-res Image Gene #7: '4p gain' versus Clinical Feature #8: 'NUMBER.OF.LYMPH.NODES'

'5q gain' versus 'NUMBER.OF.LYMPH.NODES'

P value = 9.26e-05 (t-test), Q value = 0.06

Table S3.  Gene #10: '5q gain' versus Clinical Feature #8: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 100 1.9 (3.7)
5Q GAIN CNV 11 0.3 (0.5)
5Q GAIN WILD-TYPE 89 2.1 (3.9)

Figure S3.  Get High-res Image Gene #10: '5q gain' versus Clinical Feature #8: 'NUMBER.OF.LYMPH.NODES'

'9q gain' versus 'NUMBER.OF.LYMPH.NODES'

P value = 2.3e-06 (t-test), Q value = 0.0015

Table S4.  Gene #18: '9q gain' versus Clinical Feature #8: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 100 1.9 (3.7)
9Q GAIN CNV 9 0.0 (0.0)
9Q GAIN WILD-TYPE 91 2.0 (3.9)

Figure S4.  Get High-res Image Gene #18: '9q gain' versus Clinical Feature #8: 'NUMBER.OF.LYMPH.NODES'

'14q gain' versus 'NUMBER.OF.LYMPH.NODES'

P value = 6.54e-05 (t-test), Q value = 0.042

Table S5.  Gene #26: '14q gain' versus Clinical Feature #8: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 100 1.9 (3.7)
14Q GAIN CNV 6 0.2 (0.4)
14Q GAIN WILD-TYPE 94 2.0 (3.8)

Figure S5.  Get High-res Image Gene #26: '14q gain' versus Clinical Feature #8: 'NUMBER.OF.LYMPH.NODES'

'16p gain' versus 'Time to Death'

P value = 6.44e-07 (logrank test), Q value = 0.00042

Table S6.  Gene #28: '16p gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 127 34 0.1 - 131.2 (7.0)
16P GAIN CNV 9 6 2.2 - 9.7 (5.1)
16P GAIN WILD-TYPE 118 28 0.1 - 131.2 (7.1)

Figure S6.  Get High-res Image Gene #28: '16p gain' versus Clinical Feature #1: 'Time to Death'

'16q gain' versus 'Time to Death'

P value = 6.18e-05 (logrank test), Q value = 0.04

Table S7.  Gene #29: '16q gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 127 34 0.1 - 131.2 (7.0)
16Q GAIN CNV 12 5 0.8 - 9.0 (5.3)
16Q GAIN WILD-TYPE 115 29 0.1 - 131.2 (7.2)

Figure S7.  Get High-res Image Gene #29: '16q gain' versus Clinical Feature #1: 'Time to Death'

'17p gain' versus 'NUMBER.OF.LYMPH.NODES'

P value = 2.43e-06 (t-test), Q value = 0.0016

Table S8.  Gene #30: '17p gain' versus Clinical Feature #8: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 100 1.9 (3.7)
17P GAIN CNV 5 0.0 (0.0)
17P GAIN WILD-TYPE 95 2.0 (3.8)

Figure S8.  Get High-res Image Gene #30: '17p gain' versus Clinical Feature #8: 'NUMBER.OF.LYMPH.NODES'

Methods & Data
Input

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

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

  • Number of patients = 134

  • Number of significantly arm-level cnvs = 75

  • Number of selected clinical features = 10

  • 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

Chi-square test

For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[5] 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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