Correlation between copy number variations of arm-level result and selected clinical features
Testicular Germ Cell Tumors (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C1FT8K5P
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1FT8K5P
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 74 arm-level events and 8 clinical features across 133 patients, 10 significant findings detected with Q value < 0.25.

  • 7q gain cnv correlated to 'ETHNICITY'.

  • 10p gain cnv correlated to 'YEARS_TO_BIRTH'.

  • 15q gain cnv correlated to 'YEARS_TO_BIRTH'.

  • 19p gain cnv correlated to 'YEARS_TO_BIRTH'.

  • 19q gain cnv correlated to 'YEARS_TO_BIRTH'.

  • 10p loss cnv correlated to 'YEARS_TO_BIRTH'.

  • 10q loss cnv correlated to 'YEARS_TO_BIRTH'.

  • 14q loss cnv correlated to 'YEARS_TO_BIRTH'.

  • 19q loss cnv correlated to 'YEARS_TO_BIRTH' and 'NEOPLASM_DISEASESTAGE'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 74 arm-level events and 8 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 10 significant findings detected.

Clinical
Features 		Time
to
Death 		YEARS
TO
BIRTH 		NEOPLASM
DISEASESTAGE 		PATHOLOGY
T
STAGE 		PATHOLOGY
N
STAGE 		PATHOLOGY
M
STAGE 		RACE ETHNICITY
nCNV (%) nWild-Type logrank test Wilcoxon-test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
19q loss 42 (32%) 91 0.905
(1.00) 		0.0019
(0.125) 		0.00022
(0.0824) 		0.158
(1.00) 		0.105
(0.957) 		0.598
(1.00) 		1
(1.00) 		1
(1.00)
7q gain 96 (72%) 37 0.825
(1.00) 		0.938
(1.00) 		0.275
(1.00) 		0.059
(0.76) 		1
(1.00) 		1
(1.00) 		0.859
(1.00) 		0.00124
(0.0997)
10p gain 6 (5%) 127 0.769
(1.00) 		0.000606
(0.0882) 		0.95
(1.00) 		0.174
(1.00) 		1
(1.00) 		0.337
(1.00) 		1
(1.00)
15q gain 47 (35%) 86 0.928
(1.00) 		0.000278
(0.0824) 		0.217
(1.00) 		0.95
(1.00) 		1
(1.00) 		0.295
(1.00) 		1
(1.00) 		0.325
(1.00)
19p gain 32 (24%) 101 0.353
(1.00) 		0.000861
(0.0882) 		0.153
(1.00) 		0.467
(1.00) 		0.668
(1.00) 		0.571
(1.00) 		1
(1.00) 		0.461
(1.00)
19q gain 26 (20%) 107 0.432
(1.00) 		0.00135
(0.0997) 		0.181
(1.00) 		0.296
(1.00) 		1
(1.00) 		1
(1.00) 		0.827
(1.00) 		0.224
(1.00)
10p loss 67 (50%) 66 0.589
(1.00) 		0.000894
(0.0882) 		0.0532
(0.76) 		0.307
(1.00) 		0.0575
(0.76) 		0.619
(1.00) 		0.0889
(0.903) 		0.758
(1.00)
10q loss 63 (47%) 70 0.524
(1.00) 		0.00307
(0.181) 		0.0584
(0.76) 		0.408
(1.00) 		0.0303
(0.718) 		0.337
(1.00) 		0.697
(1.00) 		0.0571
(0.76)
14q loss 17 (13%) 116 0.489
(1.00) 		0.000683
(0.0882) 		0.222
(1.00) 		0.524
(1.00) 		0.0623
(0.768) 		0.377
(1.00) 		1
(1.00) 		0.614
(1.00)
1p gain 32 (24%) 101 0.339
(1.00) 		0.123
(1.00) 		0.4
(1.00) 		0.0691
(0.786) 		0.187
(1.00) 		1
(1.00) 		0.713
(1.00) 		0.468
(1.00)
1q gain 54 (41%) 79 0.774
(1.00) 		0.364
(1.00) 		0.249
(1.00) 		0.0169
(0.543) 		0.362
(1.00) 		0.636
(1.00) 		0.516
(1.00) 		0.0506
(0.76)
2p gain 39 (29%) 94 0.889
(1.00) 		0.791
(1.00) 		0.982
(1.00) 		0.453
(1.00) 		0.517
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
2q gain 38 (29%) 95 0.841
(1.00) 		0.213
(1.00) 		0.995
(1.00) 		0.42
(1.00) 		0.735
(1.00) 		1
(1.00) 		0.858
(1.00) 		0.725
(1.00)
3p gain 23 (17%) 110 0.447
(1.00) 		0.299
(1.00) 		0.928
(1.00) 		0.443
(1.00) 		1
(1.00) 		0.133
(1.00) 		0.64
(1.00) 		0.4
(1.00)
3q gain 31 (23%) 102 0.635
(1.00) 		0.831
(1.00) 		0.454
(1.00) 		0.0336
(0.76) 		0.481
(1.00) 		0.21
(1.00) 		0.838
(1.00) 		1
(1.00)
4p gain 3 (2%) 130 0.804
(1.00) 		0.611
(1.00) 		0.861
(1.00) 		0.366
(1.00) 		1
(1.00) 		0.219
(1.00) 		1
(1.00)
5p gain 6 (5%) 127 0.694
(1.00) 		0.0205
(0.579) 		0.447
(1.00) 		0.413
(1.00) 		0.533
(1.00) 		1
(1.00) 		1
(1.00) 		0.44
(1.00)
5q gain 3 (2%) 130 0.81
(1.00) 		0.103
(0.953) 		0.124
(1.00) 		1
(1.00) 		1
(1.00) 		0.249
(1.00)
6p gain 21 (16%) 112 0.449
(1.00) 		0.345
(1.00) 		0.68
(1.00) 		0.594
(1.00) 		1
(1.00) 		0.529
(1.00) 		0.466
(1.00) 		0.386
(1.00)
6q gain 17 (13%) 116 0.494
(1.00) 		0.613
(1.00) 		0.277
(1.00) 		0.326
(1.00) 		0.643
(1.00) 		0.468
(1.00) 		0.547
(1.00) 		0.182
(1.00)
7p gain 110 (83%) 23 0.433
(1.00) 		0.981
(1.00) 		0.679
(1.00) 		1
(1.00) 		1
(1.00) 		0.529
(1.00) 		0.807
(1.00) 		0.0174
(0.543)
8p gain 101 (76%) 32 0.339
(1.00) 		0.487
(1.00) 		0.708
(1.00) 		1
(1.00) 		1
(1.00) 		0.037
(0.76) 		0.843
(1.00) 		1
(1.00)
8q gain 103 (77%) 30 0.333
(1.00) 		0.242
(1.00) 		0.393
(1.00) 		0.521
(1.00) 		1
(1.00) 		0.0295
(0.718) 		0.705
(1.00) 		0.245
(1.00)
9p gain 14 (11%) 119 0.573
(1.00) 		0.552
(1.00) 		0.607
(1.00) 		0.335
(1.00) 		1
(1.00) 		1
(1.00) 		0.0767
(0.826)
9q gain 15 (11%) 118 0.506
(1.00) 		0.279
(1.00) 		0.235
(1.00) 		0.896
(1.00) 		1
(1.00) 		0.353
(1.00) 		0.331
(1.00) 		1
(1.00)
10q gain 8 (6%) 125 0.689
(1.00) 		0.00745
(0.314) 		0.927
(1.00) 		0.261
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.493
(1.00)
11p gain 9 (7%) 124 0.62
(1.00) 		0.693
(1.00) 		0.327
(1.00) 		0.666
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
11q gain 4 (3%) 129 0.75
(1.00) 		0.678
(1.00) 		0.149
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
12p gain 129 (97%) 4 0.765
(1.00) 		0.958
(1.00) 		0.173
(1.00) 		0.709
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
12q gain 90 (68%) 43 0.166
(1.00) 		0.0529
(0.76) 		0.239
(1.00) 		0.468
(1.00) 		0.738
(1.00) 		1
(1.00) 		0.571
(1.00) 		0.5
(1.00)
14q gain 45 (34%) 88 0.182
(1.00) 		0.092
(0.908) 		0.186
(1.00) 		0.95
(1.00) 		0.307
(1.00) 		1
(1.00) 		1
(1.00) 		0.325
(1.00)
16p gain 13 (10%) 120 0.195
(1.00) 		0.585
(1.00) 		0.684
(1.00) 		0.0891
(0.903) 		0.643
(1.00) 		0.328
(1.00) 		0.671
(1.00) 		0.259
(1.00)
16q gain 13 (10%) 120 0.224
(1.00) 		0.262
(1.00) 		0.682
(1.00) 		0.168
(1.00) 		0.643
(1.00) 		0.328
(1.00) 		0.673
(1.00) 		0.259
(1.00)
17p gain 32 (24%) 101 0.84
(1.00) 		0.216
(1.00) 		0.143
(1.00) 		0.164
(1.00) 		0.513
(1.00) 		0.282
(1.00) 		0.608
(1.00) 		0.728
(1.00)
17q gain 43 (32%) 90 0.259
(1.00) 		0.355
(1.00) 		0.27
(1.00) 		0.337
(1.00) 		1
(1.00) 		0.598
(1.00) 		0.314
(1.00) 		1
(1.00)
18p gain 4 (3%) 129 0.815
(1.00) 		0.812
(1.00) 		0.371
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.129
(1.00) 		1
(1.00)
20p gain 30 (23%) 103 0.678
(1.00) 		0.614
(1.00) 		0.144
(1.00) 		0.00795
(0.314) 		0.426
(1.00) 		0.197
(1.00) 		0.839
(1.00) 		1
(1.00)
20q gain 33 (25%) 100 0.804
(1.00) 		0.673
(1.00) 		0.0567
(0.76) 		0.0364
(0.76) 		0.712
(1.00) 		0.224
(1.00) 		0.604
(1.00) 		0.454
(1.00)
21q gain 112 (84%) 21 0.0291
(0.718) 		0.0454
(0.76) 		0.467
(1.00) 		0.307
(1.00) 		0.713
(1.00) 		0.489
(1.00) 		0.325
(1.00) 		1
(1.00)
22q gain 34 (26%) 99 0.321
(1.00) 		0.0661
(0.777) 		0.388
(1.00) 		0.217
(1.00) 		0.426
(1.00) 		0.572
(1.00) 		0.716
(1.00) 		0.726
(1.00)
xp gain 18 (14%) 115 0.469
(1.00) 		0.153
(1.00) 		0.732
(1.00) 		0.681
(1.00) 		0.185
(1.00) 		0.11
(0.984) 		1
(1.00) 		0.665
(1.00)
xq gain 18 (14%) 115 0.469
(1.00) 		0.09
(0.903) 		0.622
(1.00) 		0.431
(1.00) 		0.0979
(0.934) 		0.489
(1.00) 		1
(1.00) 		0.665
(1.00)
1p loss 17 (13%) 116 0.00484
(0.26) 		0.713
(1.00) 		0.905
(1.00) 		0.361
(1.00) 		0.671
(1.00) 		1
(1.00) 		0.229
(1.00) 		1
(1.00)
1q loss 8 (6%) 125 0.061
(0.768) 		0.529
(1.00) 		0.908
(1.00) 		0.15
(1.00) 		0.576
(1.00) 		1
(1.00) 		0.0503
(0.76) 		1
(1.00)
2p loss 5 (4%) 128 0.741
(1.00) 		0.749
(1.00) 		0.255
(1.00) 		0.266
(1.00) 		1
(1.00) 		1
(1.00) 		0.382
(1.00)
2q loss 6 (5%) 127 0.683
(1.00) 		1
(1.00) 		0.103
(0.953) 		0.549
(1.00) 		0.119
(1.00) 		1
(1.00) 		1
(1.00) 		0.44
(1.00)
3p loss 30 (23%) 103 0.691
(1.00) 		0.0537
(0.76) 		0.397
(1.00) 		0.592
(1.00) 		0.712
(1.00) 		0.577
(1.00) 		0.168
(1.00) 		0.706
(1.00)
3q loss 22 (17%) 111 0.429
(1.00) 		0.146
(1.00) 		0.557
(1.00) 		0.553
(1.00) 		0.268
(1.00) 		1
(1.00) 		0.276
(1.00) 		1
(1.00)
4p loss 83 (62%) 50 0.193
(1.00) 		0.174
(1.00) 		0.312
(1.00) 		0.137
(1.00) 		0.334
(1.00) 		1
(1.00) 		0.875
(1.00) 		0.532
(1.00)
4q loss 98 (74%) 35 0.301
(1.00) 		0.183
(1.00) 		0.32
(1.00) 		0.0457
(0.76) 		0.0259
(0.698) 		1
(1.00) 		0.117
(1.00) 		1
(1.00)
5p loss 92 (69%) 41 0.983
(1.00) 		0.729
(1.00) 		0.398
(1.00) 		0.0184
(0.545) 		1
(1.00) 		0.585
(1.00) 		0.648
(1.00) 		0.734
(1.00)
5q loss 90 (68%) 43 0.958
(1.00) 		0.763
(1.00) 		0.0506
(0.76) 		0.0076
(0.314) 		0.334
(1.00) 		0.598
(1.00) 		0.571
(1.00) 		0.749
(1.00)
6p loss 11 (8%) 122 0.59
(1.00) 		0.0443
(0.76) 		0.872
(1.00) 		0.857
(1.00) 		0.322
(1.00) 		1
(1.00) 		0.608
(1.00) 		0.586
(1.00)
6q loss 14 (11%) 119 0.54
(1.00) 		0.0866
(0.903) 		0.407
(1.00) 		0.696
(1.00) 		1
(1.00) 		0.328
(1.00) 		0.671
(1.00) 		1
(1.00)
8p loss 10 (8%) 123 0.62
(1.00) 		0.642
(1.00) 		0.0582
(0.76) 		0.576
(1.00) 		0.119
(1.00) 		0.0172
(0.543) 		0.529
(1.00) 		1
(1.00)
8q loss 4 (3%) 129 0.75
(1.00) 		0.854
(1.00) 		0.0661
(0.777) 		0.0725
(0.795) 		0.0669
(0.777) 		0.218
(1.00) 		1
(1.00)
9p loss 55 (41%) 78 0.754
(1.00) 		0.371
(1.00) 		0.302
(1.00) 		0.617
(1.00) 		1
(1.00) 		0.306
(1.00) 		0.466
(1.00) 		0.356
(1.00)
9q loss 50 (38%) 83 0.859
(1.00) 		0.688
(1.00) 		0.499
(1.00) 		0.904
(1.00) 		1
(1.00) 		0.635
(1.00) 		0.768
(1.00) 		0.528
(1.00)
11p loss 88 (66%) 45 0.94
(1.00) 		0.156
(1.00) 		0.953
(1.00) 		0.482
(1.00) 		0.189
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
11q loss 104 (78%) 29 0.343
(1.00) 		0.565
(1.00) 		0.751
(1.00) 		0.515
(1.00) 		0.0523
(0.76) 		1
(1.00) 		0.133
(1.00) 		0.451
(1.00)
13q loss 103 (77%) 30 0.341
(1.00) 		0.295
(1.00) 		0.886
(1.00) 		0.134
(1.00) 		0.26
(1.00) 		1
(1.00) 		0.379
(1.00) 		1
(1.00)
15q loss 22 (17%) 111 0.393
(1.00) 		0.223
(1.00) 		0.118
(1.00) 		0.725
(1.00) 		0.455
(1.00) 		0.121
(1.00) 		0.353
(1.00) 		0.69
(1.00)
16p loss 43 (32%) 90 0.273
(1.00) 		1
(1.00) 		0.665
(1.00) 		0.528
(1.00) 		0.721
(1.00) 		0.304
(1.00) 		0.866
(1.00) 		0.749
(1.00)
16q loss 46 (35%) 87 0.247
(1.00) 		0.923
(1.00) 		0.711
(1.00) 		0.273
(1.00) 		1
(1.00) 		0.297
(1.00) 		0.671
(1.00) 		1
(1.00)
17p loss 34 (26%) 99 0.704
(1.00) 		0.194
(1.00) 		0.771
(1.00) 		0.838
(1.00) 		0.693
(1.00) 		0.571
(1.00) 		0.199
(1.00) 		0.468
(1.00)
17q loss 14 (11%) 119 0.554
(1.00) 		0.357
(1.00) 		0.594
(1.00) 		0.386
(1.00) 		0.605
(1.00) 		1
(1.00) 		0.699
(1.00) 		0.605
(1.00)
18p loss 103 (77%) 30 0.361
(1.00) 		0.259
(1.00) 		0.844
(1.00) 		0.241
(1.00) 		0.26
(1.00) 		1
(1.00) 		0.477
(1.00) 		1
(1.00)
18q loss 109 (82%) 24 0.395
(1.00) 		0.151
(1.00) 		0.618
(1.00) 		0.0939
(0.911) 		0.432
(1.00) 		0.567
(1.00) 		0.646
(1.00) 		1
(1.00)
19p loss 40 (30%) 93 0.984
(1.00) 		0.0133
(0.493) 		0.0071
(0.314) 		0.185
(1.00) 		0.0549
(0.76) 		0.585
(1.00) 		1
(1.00) 		1
(1.00)
20p loss 28 (21%) 105 0.376
(1.00) 		0.697
(1.00) 		0.259
(1.00) 		0.583
(1.00) 		0.135
(1.00) 		0.21
(1.00) 		0.578
(1.00) 		0.706
(1.00)
20q loss 15 (11%) 118 0.583
(1.00) 		0.237
(1.00) 		0.457
(1.00) 		0.273
(1.00) 		0.605
(1.00) 		0.424
(1.00) 		1
(1.00) 		0.624
(1.00)
22q loss 38 (29%) 95 0.824
(1.00) 		0.512
(1.00) 		0.0388
(0.76) 		0.0714
(0.795) 		0.509
(1.00) 		0.311
(1.00) 		0.231
(1.00) 		0.497
(1.00)
xp loss 23 (17%) 110 0.449
(1.00) 		0.71
(1.00) 		0.23
(1.00) 		0.617
(1.00) 		0.185
(1.00) 		1
(1.00) 		0.808
(1.00) 		0.4
(1.00)
xq loss 23 (17%) 110 0.449
(1.00) 		0.896
(1.00) 		0.327
(1.00) 		0.404
(1.00) 		0.18
(1.00) 		0.529
(1.00) 		0.808
(1.00) 		0.4
(1.00)
'7q gain' versus 'ETHNICITY'

P value = 0.00124 (Fisher's exact test), Q value = 0.1

Table S1.  Gene #13: '7q gain' versus Clinical Feature #8: 'ETHNICITY'

nPatients HISPANIC OR LATINO NOT HISPANIC OR LATINO
ALL 11 111
7Q GAIN MUTATED 3 86
7Q GAIN WILD-TYPE 8 25

Figure S1.  Get High-res Image Gene #13: '7q gain' versus Clinical Feature #8: 'ETHNICITY'

'10p gain' versus 'YEARS_TO_BIRTH'

P value = 0.000606 (Wilcoxon-test), Q value = 0.088

Table S2.  Gene #18: '10p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 133 32.0 (9.3)
10P GAIN MUTATED 6 48.3 (10.7)
10P GAIN WILD-TYPE 127 31.2 (8.6)

Figure S2.  Get High-res Image Gene #18: '10p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'15q gain' versus 'YEARS_TO_BIRTH'

P value = 0.000278 (Wilcoxon-test), Q value = 0.082

Table S3.  Gene #25: '15q gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 133 32.0 (9.3)
15Q GAIN MUTATED 47 35.9 (10.3)
15Q GAIN WILD-TYPE 86 29.8 (8.1)

Figure S3.  Get High-res Image Gene #25: '15q gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'19p gain' versus 'YEARS_TO_BIRTH'

P value = 0.000861 (Wilcoxon-test), Q value = 0.088

Table S4.  Gene #31: '19p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 133 32.0 (9.3)
19P GAIN MUTATED 32 35.9 (8.4)
19P GAIN WILD-TYPE 101 30.7 (9.3)

Figure S4.  Get High-res Image Gene #31: '19p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'19q gain' versus 'YEARS_TO_BIRTH'

P value = 0.00135 (Wilcoxon-test), Q value = 0.1

Table S5.  Gene #32: '19q gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 133 32.0 (9.3)
19Q GAIN MUTATED 26 36.3 (8.5)
19Q GAIN WILD-TYPE 107 30.9 (9.3)

Figure S5.  Get High-res Image Gene #32: '19q gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'10p loss' versus 'YEARS_TO_BIRTH'

P value = 0.000894 (Wilcoxon-test), Q value = 0.088

Table S6.  Gene #55: '10p loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 133 32.0 (9.3)
10P LOSS MUTATED 67 29.5 (8.7)
10P LOSS WILD-TYPE 66 34.4 (9.4)

Figure S6.  Get High-res Image Gene #55: '10p loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'10q loss' versus 'YEARS_TO_BIRTH'

P value = 0.00307 (Wilcoxon-test), Q value = 0.18

Table S7.  Gene #56: '10q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 133 32.0 (9.3)
10Q LOSS MUTATED 63 29.6 (8.8)
10Q LOSS WILD-TYPE 70 34.1 (9.4)

Figure S7.  Get High-res Image Gene #56: '10q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'14q loss' versus 'YEARS_TO_BIRTH'

P value = 0.000683 (Wilcoxon-test), Q value = 0.088

Table S8.  Gene #60: '14q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 133 32.0 (9.3)
14Q LOSS MUTATED 17 25.4 (5.7)
14Q LOSS WILD-TYPE 116 32.9 (9.4)

Figure S8.  Get High-res Image Gene #60: '14q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'19q loss' versus 'YEARS_TO_BIRTH'

P value = 0.0019 (Wilcoxon-test), Q value = 0.12

Table S9.  Gene #69: '19q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 133 32.0 (9.3)
19Q LOSS MUTATED 42 29.0 (10.1)
19Q LOSS WILD-TYPE 91 33.4 (8.7)

Figure S9.  Get High-res Image Gene #69: '19q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'19q loss' versus 'NEOPLASM_DISEASESTAGE'

P value = 0.00022 (Fisher's exact test), Q value = 0.082

Table S10.  Gene #69: '19q loss' versus Clinical Feature #3: 'NEOPLASM_DISEASESTAGE'

nPatients STAGE I STAGE IA STAGE IB STAGE II STAGE IIA STAGE IIB STAGE IIC STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IS
ALL 19 25 11 5 6 1 1 2 1 6 5 46
19Q LOSS MUTATED 3 2 3 5 4 0 0 1 0 4 3 16
19Q LOSS WILD-TYPE 16 23 8 0 2 1 1 1 1 2 2 30

Figure S10.  Get High-res Image Gene #69: '19q loss' versus Clinical Feature #3: 'NEOPLASM_DISEASESTAGE'

Methods & Data
Input

  • Copy number data file = broad_values_by_arm.txt from GISTIC pipeline

  • Processed Copy number data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/TGCT-TP/15101914/transformed.cor.cli.txt

  • Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/TGCT-TP/15092576/TGCT-TP.merged_data.txt

  • Number of patients = 133

  • Number of significantly arm-level cnvs = 74

  • Number of selected clinical features = 8

  • 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

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] 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)
[3] 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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