Correlation between copy number variations of arm-level result and selected clinical features
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
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 selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1G44NQK
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 events and 9 clinical features across 78 patients, 8 significant findings detected with Q value < 0.25.

  • 19q gain cnv correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

  • 2p loss cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

  • 7q loss cnv correlated to 'Time to Death'.

  • 8q loss cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

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

  • 16p loss cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

  • 16q loss cnv correlated to 'NUMBER.OF.LYMPH.NODES'.

  • 19q loss 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 events and 9 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 PATHOLOGY
T
STAGE
PATHOLOGY
N
STAGE
PATHOLOGY
M
STAGE
HISTOLOGICAL
TYPE
RADIATIONS
RADIATION
REGIMENINDICATION
NUMBERPACKYEARSSMOKED NUMBER
OF
LYMPH
NODES
nCNV (%) nWild-Type logrank test t-test Fisher's exact test Fisher's exact test Fisher's exact test Chi-square test Fisher's exact test t-test t-test
19q gain 17 (22%) 61 0.015
(1.00)
0.395
(1.00)
1
(1.00)
0.356
(1.00)
0.611
(1.00)
0.781
(1.00)
6.08e-05
(0.0375)
0.935
(1.00)
0.283
(1.00)
2p loss 4 (5%) 74 0.384
(1.00)
0.773
(1.00)
1
(1.00)
0.309
(1.00)
1
(1.00)
0.0646
(1.00)
0.525
(1.00)
0.000271
(0.166)
7q loss 10 (13%) 68 3.87e-05
(0.0239)
0.231
(1.00)
0.257
(1.00)
0.0471
(1.00)
0.154
(1.00)
0.96
(1.00)
0.00943
(1.00)
0.722
(1.00)
0.0505
(1.00)
8q loss 5 (6%) 73 0.985
(1.00)
0.183
(1.00)
0.588
(1.00)
0.309
(1.00)
0.365
(1.00)
0.914
(1.00)
1
(1.00)
0.000274
(0.167)
14q loss 5 (6%) 73 0.712
(1.00)
0.656
(1.00)
0.652
(1.00)
1
(1.00)
0.693
(1.00)
0.914
(1.00)
0.583
(1.00)
0.000271
(0.166)
16p loss 6 (8%) 72 0.936
(1.00)
0.23
(1.00)
0.17
(1.00)
0.313
(1.00)
0.264
(1.00)
0.0125
(1.00)
0.582
(1.00)
0.000271
(0.166)
16q loss 9 (12%) 69 0.652
(1.00)
0.104
(1.00)
0.422
(1.00)
0.0949
(1.00)
0.764
(1.00)
0.00122
(0.739)
0.342
(1.00)
0.000261
(0.161)
19q loss 4 (5%) 74 0.282
(1.00)
0.919
(1.00)
0.546
(1.00)
0.549
(1.00)
1
(1.00)
0.943
(1.00)
0.525
(1.00)
0.000274
(0.167)
1p gain 23 (29%) 55 0.202
(1.00)
0.793
(1.00)
0.596
(1.00)
1
(1.00)
1
(1.00)
0.516
(1.00)
0.745
(1.00)
0.497
(1.00)
0.702
(1.00)
1q gain 34 (44%) 44 0.155
(1.00)
0.652
(1.00)
0.133
(1.00)
1
(1.00)
0.903
(1.00)
0.475
(1.00)
0.221
(1.00)
0.848
(1.00)
0.424
(1.00)
2p gain 11 (14%) 67 0.312
(1.00)
0.15
(1.00)
0.454
(1.00)
0.437
(1.00)
0.782
(1.00)
0.835
(1.00)
0.38
(1.00)
0.42
(1.00)
2q gain 6 (8%) 72 0.254
(1.00)
0.269
(1.00)
0.652
(1.00)
0.155
(1.00)
1
(1.00)
0.964
(1.00)
1
(1.00)
0.25
(1.00)
3p gain 12 (15%) 66 0.313
(1.00)
0.892
(1.00)
0.736
(1.00)
0.286
(1.00)
0.809
(1.00)
0.108
(1.00)
1
(1.00)
0.224
(1.00)
3q gain 46 (59%) 32 0.48
(1.00)
0.858
(1.00)
0.799
(1.00)
0.191
(1.00)
0.271
(1.00)
0.00809
(1.00)
0.219
(1.00)
0.751
(1.00)
0.0892
(1.00)
4p gain 3 (4%) 75 0.177
(1.00)
0.3
(1.00)
0.967
(1.00)
1
(1.00)
5p gain 24 (31%) 54 0.701
(1.00)
0.707
(1.00)
0.58
(1.00)
1
(1.00)
0.72
(1.00)
0.178
(1.00)
0.744
(1.00)
0.681
(1.00)
0.577
(1.00)
5q gain 9 (12%) 69 0.24
(1.00)
0.609
(1.00)
1
(1.00)
1
(1.00)
0.567
(1.00)
0.763
(1.00)
1
(1.00)
0.529
(1.00)
0.727
(1.00)
6p gain 15 (19%) 63 0.888
(1.00)
0.362
(1.00)
1
(1.00)
0.741
(1.00)
0.708
(1.00)
0.272
(1.00)
0.707
(1.00)
0.86
(1.00)
0.0168
(1.00)
6q gain 6 (8%) 72 0.916
(1.00)
0.598
(1.00)
1
(1.00)
0.661
(1.00)
0.171
(1.00)
0.881
(1.00)
1
(1.00)
0.118
(1.00)
7p gain 7 (9%) 71 0.174
(1.00)
0.431
(1.00)
0.319
(1.00)
0.632
(1.00)
0.716
(1.00)
0.972
(1.00)
0.33
(1.00)
0.3
(1.00)
7q gain 8 (10%) 70 0.582
(1.00)
0.307
(1.00)
1
(1.00)
1
(1.00)
0.756
(1.00)
0.805
(1.00)
0.0232
(1.00)
0.568
(1.00)
8p gain 13 (17%) 65 0.258
(1.00)
0.242
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.878
(1.00)
0.446
(1.00)
0.593
(1.00)
0.895
(1.00)
8q gain 22 (28%) 56 0.64
(1.00)
0.145
(1.00)
1
(1.00)
1
(1.00)
0.898
(1.00)
0.781
(1.00)
0.749
(1.00)
0.39
(1.00)
0.909
(1.00)
9p gain 8 (10%) 70 0.501
(1.00)
0.559
(1.00)
0.257
(1.00)
0.689
(1.00)
1
(1.00)
0.973
(1.00)
1
(1.00)
0.727
(1.00)
9q gain 10 (13%) 68 0.495
(1.00)
0.863
(1.00)
0.454
(1.00)
1
(1.00)
1
(1.00)
0.96
(1.00)
1
(1.00)
0.727
(1.00)
10p gain 5 (6%) 73 0.596
(1.00)
0.347
(1.00)
0.17
(1.00)
0.155
(1.00)
1
(1.00)
0.914
(1.00)
0.583
(1.00)
0.253
(1.00)
11p gain 3 (4%) 75 0.0823
(1.00)
0.513
(1.00)
0.754
(1.00)
1
(1.00)
12p gain 10 (13%) 68 0.928
(1.00)
0.082
(1.00)
0.273
(1.00)
1
(1.00)
0.614
(1.00)
0.96
(1.00)
0.357
(1.00)
0.322
(1.00)
0.703
(1.00)
12q gain 10 (13%) 68 0.94
(1.00)
0.123
(1.00)
0.716
(1.00)
1
(1.00)
1
(1.00)
0.72
(1.00)
0.357
(1.00)
0.703
(1.00)
13q gain 3 (4%) 75 0.865
(1.00)
0.866
(1.00)
1
(1.00)
1
(1.00)
0.586
(1.00)
0.754
(1.00)
1
(1.00)
14q gain 9 (12%) 69 0.758
(1.00)
0.857
(1.00)
0.673
(1.00)
0.421
(1.00)
1
(1.00)
0.763
(1.00)
1
(1.00)
0.87
(1.00)
15q gain 10 (13%) 68 0.0395
(1.00)
0.671
(1.00)
0.1
(1.00)
0.689
(1.00)
0.764
(1.00)
0.72
(1.00)
0.67
(1.00)
0.128
(1.00)
0.284
(1.00)
16p gain 9 (12%) 69 0.615
(1.00)
0.692
(1.00)
0.133
(1.00)
0.437
(1.00)
1
(1.00)
0.968
(1.00)
0.64
(1.00)
0.42
(1.00)
16q gain 8 (10%) 70 0.651
(1.00)
0.535
(1.00)
0.1
(1.00)
0.689
(1.00)
0.764
(1.00)
0.973
(1.00)
0.614
(1.00)
0.645
(1.00)
17p gain 4 (5%) 74 0.195
(1.00)
0.972
(1.00)
0.093
(1.00)
0.0776
(1.00)
1
(1.00)
0.885
(1.00)
0.127
(1.00)
0.355
(1.00)
17q gain 8 (10%) 70 0.51
(1.00)
0.143
(1.00)
0.00104
(0.635)
0.229
(1.00)
0.764
(1.00)
0.973
(1.00)
0.614
(1.00)
0.535
(1.00)
18p gain 6 (8%) 72 0.36
(1.00)
0.0443
(1.00)
0.0779
(1.00)
1
(1.00)
1
(1.00)
0.881
(1.00)
0.26
(1.00)
0.467
(1.00)
18q gain 4 (5%) 74 0.606
(1.00)
0.182
(1.00)
0.093
(1.00)
0.578
(1.00)
1
(1.00)
0.943
(1.00)
0.127
(1.00)
0.882
(1.00)
19p gain 10 (13%) 68 0.688
(1.00)
0.337
(1.00)
0.716
(1.00)
0.154
(1.00)
1
(1.00)
0.96
(1.00)
0.00943
(1.00)
0.565
(1.00)
20p gain 21 (27%) 57 0.145
(1.00)
0.796
(1.00)
0.562
(1.00)
0.143
(1.00)
0.23
(1.00)
0.45
(1.00)
0.74
(1.00)
0.478
(1.00)
0.321
(1.00)
20q gain 26 (33%) 52 0.572
(1.00)
0.401
(1.00)
0.289
(1.00)
0.575
(1.00)
0.645
(1.00)
0.357
(1.00)
0.751
(1.00)
0.654
(1.00)
0.965
(1.00)
21q gain 9 (12%) 69 0.0525
(1.00)
0.0805
(1.00)
0.673
(1.00)
0.421
(1.00)
1
(1.00)
0.763
(1.00)
0.167
(1.00)
0.467
(1.00)
22q gain 10 (13%) 68 0.337
(1.00)
0.0385
(1.00)
0.133
(1.00)
0.437
(1.00)
0.782
(1.00)
0.96
(1.00)
0.67
(1.00)
0.489
(1.00)
xq gain 7 (9%) 71 0.995
(1.00)
0.682
(1.00)
0.418
(1.00)
1
(1.00)
0.756
(1.00)
0.972
(1.00)
0.33
(1.00)
0.568
(1.00)
1p loss 3 (4%) 75 0.797
(1.00)
0.513
(1.00)
0.967
(1.00)
0.0704
(1.00)
1q loss 3 (4%) 75 0.183
(1.00)
0.587
(1.00)
0.546
(1.00)
0.212
(1.00)
1
(1.00)
0.967
(1.00)
0.00376
(1.00)
0.454
(1.00)
2q loss 9 (12%) 69 0.894
(1.00)
0.372
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.376
(1.00)
0.167
(1.00)
0.526
(1.00)
3p loss 19 (24%) 59 0.404
(1.00)
0.425
(1.00)
0.554
(1.00)
0.0138
(1.00)
0.868
(1.00)
0.335
(1.00)
0.0726
(1.00)
0.748
(1.00)
0.26
(1.00)
4p loss 31 (40%) 47 0.619
(1.00)
0.207
(1.00)
0.798
(1.00)
0.292
(1.00)
0.665
(1.00)
0.0528
(1.00)
0.12
(1.00)
0.972
(1.00)
0.352
(1.00)
4q loss 14 (18%) 64 0.0415
(1.00)
0.307
(1.00)
0.324
(1.00)
0.0494
(1.00)
1
(1.00)
0.541
(1.00)
0.0499
(1.00)
0.784
(1.00)
0.131
(1.00)
5p loss 3 (4%) 75 0.000892
(0.543)
0.409
(1.00)
0.546
(1.00)
0.0243
(1.00)
1
(1.00)
0.967
(1.00)
0.0704
(1.00)
0.131
(1.00)
5q loss 15 (19%) 63 0.0227
(1.00)
0.123
(1.00)
0.525
(1.00)
0.745
(1.00)
0.561
(1.00)
0.497
(1.00)
0.262
(1.00)
0.759
(1.00)
0.666
(1.00)
6p loss 7 (9%) 71 0.871
(1.00)
0.0878
(1.00)
1
(1.00)
0.0617
(1.00)
1
(1.00)
0.972
(1.00)
0.594
(1.00)
0.238
(1.00)
0.363
(1.00)
6q loss 14 (18%) 64 0.245
(1.00)
0.155
(1.00)
1
(1.00)
0.489
(1.00)
0.321
(1.00)
0.554
(1.00)
0.443
(1.00)
0.0491
(1.00)
0.568
(1.00)
7p loss 6 (8%) 72 0.513
(1.00)
0.886
(1.00)
1
(1.00)
0.355
(1.00)
0.716
(1.00)
0.881
(1.00)
0.00612
(1.00)
0.902
(1.00)
0.32
(1.00)
8p loss 22 (28%) 56 0.246
(1.00)
0.833
(1.00)
0.562
(1.00)
1
(1.00)
0.881
(1.00)
0.121
(1.00)
1
(1.00)
0.104
(1.00)
0.73
(1.00)
9p loss 15 (19%) 63 0.0459
(1.00)
0.966
(1.00)
0.529
(1.00)
1
(1.00)
1
(1.00)
0.438
(1.00)
1
(1.00)
0.736
(1.00)
0.63
(1.00)
9q loss 10 (13%) 68 0.391
(1.00)
0.24
(1.00)
0.485
(1.00)
0.714
(1.00)
0.804
(1.00)
0.0311
(1.00)
0.67
(1.00)
0.772
(1.00)
10p loss 14 (18%) 64 0.0869
(1.00)
0.347
(1.00)
0.312
(1.00)
0.0746
(1.00)
0.42
(1.00)
0.887
(1.00)
0.235
(1.00)
0.953
(1.00)
0.144
(1.00)
10q loss 17 (22%) 61 0.0265
(1.00)
0.395
(1.00)
0.537
(1.00)
0.00892
(1.00)
0.248
(1.00)
0.879
(1.00)
0.143
(1.00)
0.442
(1.00)
0.0303
(1.00)
11p loss 23 (29%) 55 0.911
(1.00)
0.738
(1.00)
0.289
(1.00)
0.575
(1.00)
1
(1.00)
0.113
(1.00)
0.745
(1.00)
0.328
(1.00)
0.179
(1.00)
11q loss 32 (41%) 46 0.923
(1.00)
0.053
(1.00)
0.311
(1.00)
0.789
(1.00)
0.812
(1.00)
0.33
(1.00)
1
(1.00)
0.479
(1.00)
0.601
(1.00)
12p loss 12 (15%) 66 0.367
(1.00)
0.218
(1.00)
0.485
(1.00)
0.712
(1.00)
0.804
(1.00)
0.93
(1.00)
0.2
(1.00)
0.604
(1.00)
0.772
(1.00)
13q loss 20 (26%) 58 0.0699
(1.00)
0.72
(1.00)
0.562
(1.00)
0.143
(1.00)
0.881
(1.00)
0.299
(1.00)
1
(1.00)
0.715
(1.00)
0.281
(1.00)
15q loss 7 (9%) 71 0.717
(1.00)
0.436
(1.00)
1
(1.00)
0.666
(1.00)
1
(1.00)
0.276
(1.00)
1
(1.00)
0.93
(1.00)
17p loss 20 (26%) 58 0.235
(1.00)
0.74
(1.00)
0.771
(1.00)
1
(1.00)
0.249
(1.00)
0.299
(1.00)
1
(1.00)
0.506
(1.00)
0.606
(1.00)
17q loss 5 (6%) 73 0.412
(1.00)
0.788
(1.00)
0.299
(1.00)
1
(1.00)
0.365
(1.00)
0.914
(1.00)
1
(1.00)
0.248
(1.00)
18p loss 12 (15%) 66 0.34
(1.00)
0.0306
(1.00)
0.0927
(1.00)
0.485
(1.00)
1
(1.00)
0.57
(1.00)
0.107
(1.00)
0.0285
(1.00)
0.652
(1.00)
18q loss 18 (23%) 60 0.886
(1.00)
0.378
(1.00)
0.239
(1.00)
0.121
(1.00)
0.749
(1.00)
0.214
(1.00)
0.483
(1.00)
0.282
(1.00)
0.284
(1.00)
19p loss 13 (17%) 65 0.3
(1.00)
0.0967
(1.00)
0.709
(1.00)
0.261
(1.00)
0.804
(1.00)
0.586
(1.00)
0.446
(1.00)
0.2
(1.00)
20p loss 7 (9%) 71 0.826
(1.00)
0.822
(1.00)
0.657
(1.00)
1
(1.00)
1
(1.00)
0.547
(1.00)
0.594
(1.00)
0.187
(1.00)
0.467
(1.00)
20q loss 3 (4%) 75 0.0259
(1.00)
0.513
(1.00)
0.754
(1.00)
1
(1.00)
21q loss 10 (13%) 68 0.36
(1.00)
0.274
(1.00)
0.716
(1.00)
1
(1.00)
1
(1.00)
0.72
(1.00)
0.67
(1.00)
0.54
(1.00)
22q loss 11 (14%) 67 0.573
(1.00)
0.236
(1.00)
0.709
(1.00)
0.714
(1.00)
0.804
(1.00)
0.0715
(1.00)
0.38
(1.00)
0.526
(1.00)
xq loss 15 (19%) 63 0.0051
(1.00)
0.699
(1.00)
0.529
(1.00)
0.511
(1.00)
0.825
(1.00)
0.852
(1.00)
0.262
(1.00)
0.411
(1.00)
0.327
(1.00)
'19q gain' versus 'RADIATIONS.RADIATION.REGIMENINDICATION'

P value = 6.08e-05 (Fisher's exact test), Q value = 0.037

Table S1.  Gene #32: '19q gain' versus Clinical Feature #7: 'RADIATIONS.RADIATION.REGIMENINDICATION'

nPatients NO YES
ALL 13 65
19Q GAIN MUTATED 9 8
19Q GAIN WILD-TYPE 4 57

Figure S1.  Get High-res Image Gene #32: '19q gain' versus Clinical Feature #7: 'RADIATIONS.RADIATION.REGIMENINDICATION'

'2p loss' versus 'NUMBER.OF.LYMPH.NODES'

P value = 0.000271 (t-test), Q value = 0.17

Table S2.  Gene #40: '2p loss' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 64 0.6 (1.3)
2P LOSS MUTATED 4 0.0 (0.0)
2P LOSS WILD-TYPE 60 0.7 (1.3)

Figure S2.  Get High-res Image Gene #40: '2p loss' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'7q loss' versus 'Time to Death'

P value = 3.87e-05 (logrank test), Q value = 0.024

Table S3.  Gene #50: '7q loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 76 11 0.0 - 177.0 (6.0)
7Q LOSS MUTATED 10 5 1.0 - 40.9 (13.0)
7Q LOSS WILD-TYPE 66 6 0.0 - 177.0 (5.9)

Figure S3.  Get High-res Image Gene #50: '7q loss' versus Clinical Feature #1: 'Time to Death'

'8q loss' versus 'NUMBER.OF.LYMPH.NODES'

P value = 0.000274 (t-test), Q value = 0.17

Table S4.  Gene #52: '8q loss' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 64 0.6 (1.3)
8Q LOSS MUTATED 3 0.0 (0.0)
8Q LOSS WILD-TYPE 61 0.6 (1.3)

Figure S4.  Get High-res Image Gene #52: '8q loss' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

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

P value = 0.000271 (t-test), Q value = 0.17

Table S5.  Gene #61: '14q loss' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 64 0.6 (1.3)
14Q LOSS MUTATED 4 0.0 (0.0)
14Q LOSS WILD-TYPE 60 0.7 (1.3)

Figure S5.  Get High-res Image Gene #61: '14q loss' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'16p loss' versus 'NUMBER.OF.LYMPH.NODES'

P value = 0.000271 (t-test), Q value = 0.17

Table S6.  Gene #63: '16p loss' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 64 0.6 (1.3)
16P LOSS MUTATED 4 0.0 (0.0)
16P LOSS WILD-TYPE 60 0.7 (1.3)

Figure S6.  Get High-res Image Gene #63: '16p loss' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'16q loss' versus 'NUMBER.OF.LYMPH.NODES'

P value = 0.000261 (t-test), Q value = 0.16

Table S7.  Gene #64: '16q loss' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 64 0.6 (1.3)
16Q LOSS MUTATED 7 0.0 (0.0)
16Q LOSS WILD-TYPE 57 0.7 (1.3)

Figure S7.  Get High-res Image Gene #64: '16q loss' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

'19q loss' versus 'NUMBER.OF.LYMPH.NODES'

P value = 0.000274 (t-test), Q value = 0.17

Table S8.  Gene #70: '19q loss' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

nPatients Mean (Std.Dev)
ALL 64 0.6 (1.3)
19Q LOSS MUTATED 3 0.0 (0.0)
19Q LOSS WILD-TYPE 61 0.6 (1.3)

Figure S8.  Get High-res Image Gene #70: '19q loss' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'

Methods & Data
Input
  • Copy number data file = transformed.cor.cli.txt

  • Clinical data file = CESC-TP.merged_data.txt

  • Number of patients = 78

  • Number of significantly arm-level cnvs = 75

  • Number of selected clinical features = 9

  • 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

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

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] 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)