Correlation between copy number variations of arm-level result and selected clinical features
Breast Invasive Carcinoma (Primary solid tumor)
21 April 2013  |  analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C1RF5RZX
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Breast Invasive Carcinoma (Primary solid tumor cohort) - 21 April 2013: Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1RF5RZX
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 9 clinical features across 857 patients, 3 significant findings detected with Q value < 0.25.

  • 4q gain cnv correlated to 'NEOPLASM.DISEASESTAGE'.

  • 11p gain cnv correlated to 'NEOPLASM.DISEASESTAGE'.

  • 14q gain cnv correlated to 'NEOPLASM.DISEASESTAGE'.

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 9 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 3 significant findings detected.

Clinical
Features 		Time
to
Death 		AGE GENDER RADIATIONS
RADIATION
REGIMENINDICATION 		DISTANT
METASTASIS 		LYMPH
NODE
METASTASIS 		NUMBER
OF
LYMPH
NODES 		TUMOR
STAGECODE 		NEOPLASM
DISEASESTAGE
nCNV (%) nWild-Type logrank test t-test Fisher's exact test Fisher's exact test Fisher's exact test Chi-square test t-test t-test Chi-square test
4q gain 0 (0%) 830 0.0247
(1.00) 		0.353
(1.00) 		1
(1.00) 		1
(1.00) 		0.141
(1.00) 		0.435
(1.00) 		0.689
(1.00) 		3.84e-12
(2.46e-09)
11p gain 0 (0%) 793 0.617
(1.00) 		0.735
(1.00) 		0.504
(1.00) 		0.763
(1.00) 		1
(1.00) 		0.209
(1.00) 		0.4
(1.00) 		0.000337
(0.215)
14q gain 0 (0%) 782 0.161
(1.00) 		0.445
(1.00) 		1
(1.00) 		0.329
(1.00) 		0.94
(1.00) 		0.142
(1.00) 		0.0333
(1.00) 		7.8e-05
(0.0498)
1p gain 0 (0%) 766 0.183
(1.00) 		0.513
(1.00) 		1
(1.00) 		0.0202
(1.00) 		1
(1.00) 		0.209
(1.00) 		0.719
(1.00) 		0.358
(1.00)
1q gain 0 (0%) 398 0.07
(1.00) 		0.241
(1.00) 		1
(1.00) 		0.427
(1.00) 		0.8
(1.00) 		0.475
(1.00) 		0.573
(1.00) 		0.273
(1.00)
2p gain 0 (0%) 809 0.784
(1.00) 		0.697
(1.00) 		1
(1.00) 		0.302
(1.00) 		0.5
(1.00) 		0.777
(1.00) 		0.401
(1.00) 		0.0598
(1.00)
2q gain 0 (0%) 832 0.97
(1.00) 		0.949
(1.00) 		1
(1.00) 		0.0158
(1.00) 		0.277
(1.00) 		0.337
(1.00) 		0.272
(1.00) 		0.625
(1.00)
3p gain 0 (0%) 803 0.534
(1.00) 		0.0359
(1.00) 		1
(1.00) 		1
(1.00) 		0.487
(1.00) 		0.4
(1.00) 		0.491
(1.00) 		0.197
(1.00)
3q gain 0 (0%) 762 0.177
(1.00) 		0.529
(1.00) 		0.608
(1.00) 		1
(1.00) 		0.499
(1.00) 		0.38
(1.00) 		0.174
(1.00) 		0.12
(1.00)
4p gain 0 (0%) 828 0.0662
(1.00) 		0.477
(1.00) 		1
(1.00) 		0.511
(1.00) 		0.151
(1.00) 		0.489
(1.00) 		0.852
(1.00) 		0.000609
(0.388)
5p gain 0 (0%) 695 0.173
(1.00) 		0.0573
(1.00) 		0.681
(1.00) 		0.188
(1.00) 		0.467
(1.00) 		0.3
(1.00) 		0.464
(1.00) 		0.75
(1.00)
5q gain 0 (0%) 758 0.35
(1.00) 		0.0052
(1.00) 		1
(1.00) 		0.267
(1.00) 		0.344
(1.00) 		0.792
(1.00) 		0.866
(1.00) 		0.946
(1.00)
6p gain 0 (0%) 764 0.831
(1.00) 		0.273
(1.00) 		1
(1.00) 		0.00726
(1.00) 		0.592
(1.00) 		0.9
(1.00) 		0.607
(1.00) 		0.674
(1.00)
6q gain 0 (0%) 801 0.294
(1.00) 		0.0699
(1.00) 		0.457
(1.00) 		0.522
(1.00) 		0.801
(1.00) 		0.582
(1.00) 		0.962
(1.00) 		0.933
(1.00)
7p gain 0 (0%) 705 0.859
(1.00) 		0.0902
(1.00) 		0.0113
(1.00) 		0.0127
(1.00) 		0.314
(1.00) 		0.747
(1.00) 		0.416
(1.00) 		0.377
(1.00)
7q gain 0 (0%) 747 0.496
(1.00) 		0.63
(1.00) 		0.0969
(1.00) 		0.0129
(1.00) 		0.719
(1.00) 		0.323
(1.00) 		0.383
(1.00) 		0.265
(1.00)
8p gain 0 (0%) 691 0.909
(1.00) 		0.0981
(1.00) 		0.688
(1.00) 		0.92
(1.00) 		0.949
(1.00) 		0.712
(1.00) 		0.773
(1.00) 		0.817
(1.00)
8q gain 0 (0%) 489 0.77
(1.00) 		0.032
(1.00) 		0.509
(1.00) 		0.129
(1.00) 		0.592
(1.00) 		0.0956
(1.00) 		0.917
(1.00) 		0.3
(1.00)
9p gain 0 (0%) 792 0.506
(1.00) 		0.539
(1.00) 		1
(1.00) 		0.235
(1.00) 		0.536
(1.00) 		0.143
(1.00) 		0.284
(1.00) 		0.0222
(1.00)
9q gain 0 (0%) 803 0.432
(1.00) 		0.25
(1.00) 		1
(1.00) 		0.143
(1.00) 		1
(1.00) 		0.211
(1.00) 		0.434
(1.00) 		0.0693
(1.00)
10p gain 0 (0%) 751 0.778
(1.00) 		0.838
(1.00) 		0.611
(1.00) 		0.279
(1.00) 		0.525
(1.00) 		0.664
(1.00) 		0.113
(1.00) 		0.00129
(0.818)
10q gain 0 (0%) 813 0.791
(1.00) 		0.347
(1.00) 		1
(1.00) 		0.282
(1.00) 		0.867
(1.00) 		0.983
(1.00) 		0.919
(1.00) 		0.0575
(1.00)
11q gain 0 (0%) 812 0.0481
(1.00) 		0.848
(1.00) 		1
(1.00) 		0.725
(1.00) 		0.883
(1.00) 		0.093
(1.00) 		0.998
(1.00) 		0.967
(1.00)
12p gain 0 (0%) 745 0.765
(1.00) 		0.562
(1.00) 		0.0206
(1.00) 		0.24
(1.00) 		0.132
(1.00) 		0.614
(1.00) 		0.788
(1.00) 		0.574
(1.00)
12q gain 0 (0%) 772 0.156
(1.00) 		0.198
(1.00) 		0.0509
(1.00) 		0.291
(1.00) 		0.0456
(1.00) 		0.744
(1.00) 		0.866
(1.00) 		0.572
(1.00)
13q gain 0 (0%) 812 0.825
(1.00) 		0.988
(1.00) 		1
(1.00) 		0.725
(1.00) 		0.0878
(1.00) 		0.326
(1.00) 		0.0681
(1.00) 		0.526
(1.00)
15q gain 0 (0%) 813 0.652
(1.00) 		0.625
(1.00) 		0.379
(1.00) 		0.152
(1.00) 		0.757
(1.00) 		0.98
(1.00) 		0.613
(1.00) 		0.793
(1.00)
16p gain 0 (0%) 612 0.626
(1.00) 		0.0278
(1.00) 		1
(1.00) 		0.19
(1.00) 		0.502
(1.00) 		0.0781
(1.00) 		0.0821
(1.00) 		0.0568
(1.00)
16q gain 0 (0%) 804 0.177
(1.00) 		0.773
(1.00) 		0.439
(1.00) 		0.87
(1.00) 		0.0906
(1.00) 		0.53
(1.00) 		0.992
(1.00) 		0.962
(1.00)
17p gain 0 (0%) 811 0.667
(1.00) 		0.483
(1.00) 		0.00969
(1.00) 		1
(1.00) 		0.881
(1.00) 		0.419
(1.00) 		0.388
(1.00) 		0.565
(1.00)
17q gain 0 (0%) 737 0.805
(1.00) 		0.655
(1.00) 		0.0262
(1.00) 		0.82
(1.00) 		0.108
(1.00) 		0.362
(1.00) 		0.58
(1.00) 		0.0198
(1.00)
18p gain 0 (0%) 774 0.0989
(1.00) 		0.0335
(1.00) 		0.602
(1.00) 		0.06
(1.00) 		0.458
(1.00) 		0.478
(1.00) 		0.685
(1.00) 		0.109
(1.00)
18q gain 0 (0%) 783 0.132
(1.00) 		0.578
(1.00) 		0.558
(1.00) 		0.204
(1.00) 		0.359
(1.00) 		0.914
(1.00) 		0.905
(1.00) 		0.139
(1.00)
19p gain 0 (0%) 789 0.0603
(1.00) 		0.211
(1.00) 		0.156
(1.00) 		0.143
(1.00) 		0.232
(1.00) 		0.641
(1.00) 		0.349
(1.00) 		0.614
(1.00)
19q gain 0 (0%) 773 0.00779
(1.00) 		0.811
(1.00) 		0.218
(1.00) 		0.424
(1.00) 		0.0228
(1.00) 		0.159
(1.00) 		0.313
(1.00) 		0.199
(1.00)
20p gain 0 (0%) 624 0.0457
(1.00) 		0.107
(1.00) 		0.067
(1.00) 		0.859
(1.00) 		0.44
(1.00) 		0.475
(1.00) 		0.026
(1.00) 		0.932
(1.00)
20q gain 0 (0%) 589 0.141
(1.00) 		0.484
(1.00) 		0.148
(1.00) 		0.67
(1.00) 		0.492
(1.00) 		0.333
(1.00) 		0.0158
(1.00) 		0.669
(1.00)
21q gain 0 (0%) 758 0.0436
(1.00) 		0.0269
(1.00) 		1
(1.00) 		0.0252
(1.00) 		0.407
(1.00) 		0.78
(1.00) 		0.0254
(1.00) 		0.182
(1.00)
22q gain 0 (0%) 817 0.808
(1.00) 		0.405
(1.00) 		1
(1.00) 		0.576
(1.00) 		1
(1.00) 		0.0559
(1.00) 		0.725
(1.00) 		0.247
(1.00)
Xq gain 0 (0%) 837 0.118
(1.00) 		0.11
(1.00) 		1
(1.00) 		0.297
(1.00) 		1
(1.00) 		0.00936
(1.00) 		0.604
(1.00) 		0.953
(1.00)
1p loss 0 (0%) 741 0.14
(1.00) 		0.00937
(1.00) 		1
(1.00) 		0.42
(1.00) 		0.881
(1.00) 		0.0136
(1.00) 		0.0687
(1.00) 		0.0486
(1.00)
1q loss 0 (0%) 836 0.627
(1.00) 		0.698
(1.00) 		1
(1.00) 		1
(1.00) 		0.784
(1.00) 		0.942
(1.00) 		0.625
(1.00) 		0.993
(1.00)
2p loss 0 (0%) 784 0.826
(1.00) 		0.458
(1.00) 		1
(1.00) 		0.159
(1.00) 		0.056
(1.00) 		0.675
(1.00) 		0.398
(1.00) 		0.11
(1.00)
2q loss 0 (0%) 770 0.642
(1.00) 		0.674
(1.00) 		0.61
(1.00) 		0.24
(1.00) 		0.133
(1.00) 		0.457
(1.00) 		0.362
(1.00) 		0.052
(1.00)
3p loss 0 (0%) 769 0.0356
(1.00) 		0.0497
(1.00) 		0.609
(1.00) 		0.434
(1.00) 		0.374
(1.00) 		0.998
(1.00) 		0.453
(1.00) 		0.787
(1.00)
3q loss 0 (0%) 814 0.231
(1.00) 		0.0868
(1.00) 		1
(1.00) 		0.068
(1.00) 		0.125
(1.00) 		0.681
(1.00) 		0.699
(1.00) 		0.0809
(1.00)
4p loss 0 (0%) 679 0.45
(1.00) 		0.252
(1.00) 		1
(1.00) 		0.12
(1.00) 		0.89
(1.00) 		0.466
(1.00) 		0.53
(1.00) 		0.439
(1.00)
4q loss 0 (0%) 707 0.477
(1.00) 		0.966
(1.00) 		0.373
(1.00) 		0.466
(1.00) 		0.916
(1.00) 		0.288
(1.00) 		0.938
(1.00) 		0.435
(1.00)
5p loss 0 (0%) 789 0.139
(1.00) 		0.106
(1.00) 		0.527
(1.00) 		0.884
(1.00) 		0.419
(1.00) 		0.949
(1.00) 		0.818
(1.00) 		0.671
(1.00)
5q loss 0 (0%) 738 0.306
(1.00) 		0.118
(1.00) 		0.621
(1.00) 		0.647
(1.00) 		0.958
(1.00) 		0.385
(1.00) 		0.206
(1.00) 		0.277
(1.00)
6p loss 0 (0%) 748 0.254
(1.00) 		0.128
(1.00) 		0.613
(1.00) 		0.343
(1.00) 		0.118
(1.00) 		0.844
(1.00) 		0.942
(1.00) 		0.836
(1.00)
6q loss 0 (0%) 691 0.952
(1.00) 		0.00697
(1.00) 		0.219
(1.00) 		0.133
(1.00) 		0.3
(1.00) 		0.984
(1.00) 		0.644
(1.00) 		0.778
(1.00)
7p loss 0 (0%) 810 0.526
(1.00) 		0.566
(1.00) 		1
(1.00) 		0.296
(1.00) 		0.888
(1.00) 		0.643
(1.00) 		0.582
(1.00) 		0.0371
(1.00)
7q loss 0 (0%) 794 0.132
(1.00) 		0.259
(1.00) 		1
(1.00) 		0.651
(1.00) 		0.206
(1.00) 		0.75
(1.00) 		0.301
(1.00) 		0.0349
(1.00)
8p loss 0 (0%) 600 0.00387
(1.00) 		0.538
(1.00) 		1
(1.00) 		0.863
(1.00) 		0.496
(1.00) 		0.21
(1.00) 		0.176
(1.00) 		0.807
(1.00)
8q loss 0 (0%) 812 0.00592
(1.00) 		0.931
(1.00) 		1
(1.00) 		0.594
(1.00) 		0.336
(1.00) 		0.602
(1.00) 		0.424
(1.00) 		0.635
(1.00)
9p loss 0 (0%) 673 0.0158
(1.00) 		0.958
(1.00) 		0.413
(1.00) 		0.441
(1.00) 		0.63
(1.00) 		0.377
(1.00) 		0.675
(1.00) 		0.295
(1.00)
9q loss 0 (0%) 717 0.0163
(1.00) 		0.539
(1.00) 		0.17
(1.00) 		0.915
(1.00) 		0.277
(1.00) 		0.304
(1.00) 		0.994
(1.00) 		0.344
(1.00)
10p loss 0 (0%) 785 0.0778
(1.00) 		0.53
(1.00) 		1
(1.00) 		0.67
(1.00) 		0.0687
(1.00) 		0.439
(1.00) 		0.496
(1.00) 		0.356
(1.00)
10q loss 0 (0%) 751 0.00376
(1.00) 		0.692
(1.00) 		0.611
(1.00) 		0.473
(1.00) 		0.356
(1.00) 		0.31
(1.00) 		0.737
(1.00) 		0.38
(1.00)
11p loss 0 (0%) 719 0.0149
(1.00) 		0.383
(1.00) 		0.369
(1.00) 		0.59
(1.00) 		0.934
(1.00) 		0.934
(1.00) 		0.0374
(1.00) 		0.333
(1.00)
11q loss 0 (0%) 637 0.156
(1.00) 		0.617
(1.00) 		0.0534
(1.00) 		0.469
(1.00) 		0.398
(1.00) 		0.714
(1.00) 		0.151
(1.00) 		0.036
(1.00)
12p loss 0 (0%) 792 0.0972
(1.00) 		0.995
(1.00) 		0.51
(1.00) 		0.455
(1.00) 		1
(1.00) 		0.45
(1.00) 		0.866
(1.00) 		0.764
(1.00)
12q loss 0 (0%) 807 0.229
(1.00) 		0.218
(1.00) 		1
(1.00) 		0.613
(1.00) 		0.786
(1.00) 		0.82
(1.00) 		0.604
(1.00) 		0.418
(1.00)
13q loss 0 (0%) 600 0.0791
(1.00) 		0.176
(1.00) 		0.464
(1.00) 		1
(1.00) 		0.39
(1.00) 		0.0928
(1.00) 		0.613
(1.00) 		0.921
(1.00)
14q loss 0 (0%) 730 0.00846
(1.00) 		0.217
(1.00) 		0.37
(1.00) 		1
(1.00) 		0.585
(1.00) 		0.444
(1.00) 		0.862
(1.00) 		0.812
(1.00)
15q loss 0 (0%) 701 0.234
(1.00) 		0.174
(1.00) 		0.377
(1.00) 		0.475
(1.00) 		0.246
(1.00) 		0.872
(1.00) 		0.452
(1.00) 		0.267
(1.00)
16p loss 0 (0%) 804 0.962
(1.00) 		0.657
(1.00) 		0.102
(1.00) 		0.87
(1.00) 		0.471
(1.00) 		0.552
(1.00) 		0.435
(1.00) 		0.408
(1.00)
16q loss 0 (0%) 491 0.0272
(1.00) 		0.00135
(0.852) 		1
(1.00) 		0.473
(1.00) 		0.638
(1.00) 		0.792
(1.00) 		0.0564
(1.00) 		0.928
(1.00)
17p loss 0 (0%) 500 0.338
(1.00) 		0.0245
(1.00) 		0.742
(1.00) 		0.0773
(1.00) 		0.544
(1.00) 		0.383
(1.00) 		0.331
(1.00) 		0.502
(1.00)
17q loss 0 (0%) 720 0.598
(1.00) 		0.238
(1.00) 		0.368
(1.00) 		0.914
(1.00) 		0.934
(1.00) 		0.659
(1.00) 		0.213
(1.00) 		0.872
(1.00)
18p loss 0 (0%) 690 0.00592
(1.00) 		0.00127
(0.804) 		1
(1.00) 		0.425
(1.00) 		0.593
(1.00) 		0.681
(1.00) 		0.27
(1.00) 		0.445
(1.00)
18q loss 0 (0%) 691 0.0396
(1.00) 		0.00111
(0.707) 		1
(1.00) 		0.483
(1.00) 		0.292
(1.00) 		0.581
(1.00) 		0.149
(1.00) 		0.0271
(1.00)
19p loss 0 (0%) 791 0.533
(1.00) 		0.318
(1.00) 		1
(1.00) 		0.236
(1.00) 		0.194
(1.00) 		0.0903
(1.00) 		0.538
(1.00) 		0.231
(1.00)
19q loss 0 (0%) 805 0.632
(1.00) 		0.991
(1.00) 		1
(1.00) 		0.621
(1.00) 		0.724
(1.00) 		0.0377
(1.00) 		0.846
(1.00) 		0.0419
(1.00)
20p loss 0 (0%) 807 0.00351
(1.00) 		0.944
(1.00) 		0.419
(1.00) 		0.866
(1.00) 		0.537
(1.00) 		0.223
(1.00) 		0.317
(1.00) 		0.475
(1.00)
20q loss 0 (0%) 830 0.576
(1.00) 		0.865
(1.00) 		1
(1.00) 		0.65
(1.00) 		0.277
(1.00) 		0.57
(1.00) 		0.754
(1.00) 		0.679
(1.00)
21q loss 0 (0%) 774 0.961
(1.00) 		0.661
(1.00) 		1
(1.00) 		0.789
(1.00) 		0.0863
(1.00) 		0.728
(1.00) 		0.459
(1.00) 		0.0257
(1.00)
22q loss 0 (0%) 569 0.124
(1.00) 		0.845
(1.00) 		0.172
(1.00) 		0.111
(1.00) 		0.41
(1.00) 		0.0533
(1.00) 		0.097
(1.00) 		0.48
(1.00)
Xq loss 0 (0%) 826 0.0537
(1.00) 		0.722
(1.00) 		0.0389
(1.00) 		0.297
(1.00) 		0.578
(1.00) 		0.931
(1.00) 		0.377
(1.00) 		0.791
(1.00)
'4q gain' versus 'NEOPLASM.DISEASESTAGE'

P value = 3.84e-12 (Chi-square test), Q value = 2.5e-09

Table S1.  Gene #8: '4q gain' versus Clinical Feature #9: 'NEOPLASM.DISEASESTAGE'

nPatients STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE X
ALL 71 45 2 8 246 165 2 107 22 36 9 12
4Q GAIN CNV 3 0 2 0 9 2 0 1 3 2 1 0
4Q GAIN WILD-TYPE 68 45 0 8 237 163 2 106 19 34 8 12

Figure S1.  Get High-res Image Gene #8: '4q gain' versus Clinical Feature #9: 'NEOPLASM.DISEASESTAGE'

'11p gain' versus 'NEOPLASM.DISEASESTAGE'

P value = 0.000337 (Chi-square test), Q value = 0.21

Table S2.  Gene #21: '11p gain' versus Clinical Feature #9: 'NEOPLASM.DISEASESTAGE'

nPatients STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE X
ALL 71 45 2 8 246 165 2 107 22 36 9 12
11P GAIN CNV 4 4 2 0 26 8 0 10 0 1 0 1
11P GAIN WILD-TYPE 67 41 0 8 220 157 2 97 22 35 9 11

Figure S2.  Get High-res Image Gene #21: '11p gain' versus Clinical Feature #9: 'NEOPLASM.DISEASESTAGE'

'14q gain' versus 'NEOPLASM.DISEASESTAGE'

P value = 7.8e-05 (Chi-square test), Q value = 0.05

Table S3.  Gene #26: '14q gain' versus Clinical Feature #9: 'NEOPLASM.DISEASESTAGE'

nPatients STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE X
ALL 71 45 2 8 246 165 2 107 22 36 9 12
14Q GAIN CNV 3 1 2 0 23 11 1 15 1 5 0 2
14Q GAIN WILD-TYPE 68 44 0 8 223 154 1 92 21 31 9 10

Figure S3.  Get High-res Image Gene #26: '14q gain' versus Clinical Feature #9: 'NEOPLASM.DISEASESTAGE'

Methods & Data
Input

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

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

  • Number of patients = 857

  • Number of significantly arm-level cnvs = 80

  • Number of selected clinical features = 9

  • 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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