Correlation between copy number variations of arm-level result and selected clinical features
Sarcoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1862FCP
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/C1862FCP
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 4 clinical features across 156 patients, 9 significant findings detected with Q value < 0.25.

  • 7p gain cnv correlated to 'AGE'.

  • 7q gain cnv correlated to 'AGE'.

  • 11p gain cnv correlated to 'Time to Death'.

  • 11q gain cnv correlated to 'Time to Death'.

  • 19p gain cnv correlated to 'AGE'.

  • 20q gain cnv correlated to 'AGE'.

  • 10p loss cnv correlated to 'GENDER'.

  • 10q loss cnv correlated to 'GENDER'.

  • 13q loss 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 4 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 9 significant findings detected.

Clinical
Features 		Time
to
Death 		AGE GENDER RACE
nCNV (%) nWild-Type logrank test Wilcoxon-test Fisher's exact test Fisher's exact test
7p gain 45 (29%) 111 0.594
(1.00) 		0.000122
(0.0387) 		0.378
(1.00) 		0.242
(1.00)
7q gain 36 (23%) 120 0.588
(1.00) 		8.25e-06
(0.00263) 		0.445
(1.00) 		0.695
(1.00)
11p gain 12 (8%) 144 4.88e-06
(0.00156) 		0.00657
(1.00) 		0.232
(1.00) 		0.409
(1.00)
11q gain 11 (7%) 145 0.000332
(0.104) 		0.526
(1.00) 		0.35
(1.00) 		0.742
(1.00)
19p gain 47 (30%) 109 0.174
(1.00) 		0.000559
(0.175) 		0.386
(1.00) 		0.369
(1.00)
20q gain 53 (34%) 103 0.116
(1.00) 		0.000734
(0.229) 		0.394
(1.00) 		0.24
(1.00)
10p loss 73 (47%) 83 0.79
(1.00) 		0.0118
(1.00) 		0.000181
(0.0569) 		0.177
(1.00)
10q loss 84 (54%) 72 0.385
(1.00) 		0.0649
(1.00) 		5.11e-05
(0.0162) 		0.577
(1.00)
13q loss 82 (53%) 74 0.22
(1.00) 		0.000106
(0.0337) 		0.0359
(1.00) 		1
(1.00)
1p gain 32 (21%) 124 0.283
(1.00) 		0.0232
(1.00) 		0.549
(1.00) 		0.525
(1.00)
1q gain 32 (21%) 124 0.299
(1.00) 		0.0397
(1.00) 		0.318
(1.00) 		0.869
(1.00)
2p gain 12 (8%) 144 0.0183
(1.00) 		0.0408
(1.00) 		1
(1.00) 		0.457
(1.00)
2q gain 10 (6%) 146 0.583
(1.00) 		0.0623
(1.00) 		0.515
(1.00) 		0.365
(1.00)
3p gain 19 (12%) 137 0.907
(1.00) 		0.0641
(1.00) 		0.625
(1.00) 		0.553
(1.00)
3q gain 17 (11%) 139 0.959
(1.00) 		0.023
(1.00) 		0.606
(1.00) 		0.788
(1.00)
4p gain 39 (25%) 117 0.898
(1.00) 		0.93
(1.00) 		0.0659
(1.00) 		0.326
(1.00)
4q gain 25 (16%) 131 0.299
(1.00) 		0.528
(1.00) 		1
(1.00) 		0.604
(1.00)
5p gain 56 (36%) 100 0.995
(1.00) 		0.00311
(0.945) 		0.501
(1.00) 		0.512
(1.00)
5q gain 46 (29%) 110 0.88
(1.00) 		0.0252
(1.00) 		0.0351
(1.00) 		0.351
(1.00)
6p gain 31 (20%) 125 0.0267
(1.00) 		0.00271
(0.826) 		0.419
(1.00) 		1
(1.00)
6q gain 30 (19%) 126 0.118
(1.00) 		0.0192
(1.00) 		0.838
(1.00) 		1
(1.00)
8p gain 33 (21%) 123 0.00407
(1.00) 		0.196
(1.00) 		0.236
(1.00) 		0.00251
(0.768)
8q gain 34 (22%) 122 0.00582
(1.00) 		0.747
(1.00) 		0.0782
(1.00) 		0.00394
(1.00)
9p gain 28 (18%) 128 0.127
(1.00) 		0.0555
(1.00) 		0.834
(1.00) 		0.635
(1.00)
9q gain 40 (26%) 116 0.888
(1.00) 		0.00156
(0.482) 		1
(1.00) 		0.632
(1.00)
10p gain 14 (9%) 142 0.049
(1.00) 		0.615
(1.00) 		1
(1.00) 		1
(1.00)
10q gain 7 (4%) 149 0.458
(1.00) 		0.32
(1.00) 		0.241
(1.00) 		1
(1.00)
12p gain 25 (16%) 131 0.0245
(1.00) 		0.0019
(0.585) 		0.664
(1.00) 		0.148
(1.00)
12q gain 18 (12%) 138 0.841
(1.00) 		0.0844
(1.00) 		0.618
(1.00) 		0.00934
(1.00)
13q gain 7 (4%) 149 0.666
(1.00) 		0.584
(1.00) 		0.0188
(1.00) 		0.0839
(1.00)
14q gain 31 (20%) 125 0.0311
(1.00) 		0.102
(1.00) 		0.686
(1.00) 		0.871
(1.00)
15q gain 42 (27%) 114 0.919
(1.00) 		0.033
(1.00) 		0.0687
(1.00) 		0.355
(1.00)
16p gain 23 (15%) 133 0.0906
(1.00) 		0.356
(1.00) 		1
(1.00) 		0.468
(1.00)
16q gain 9 (6%) 147 0.17
(1.00) 		0.407
(1.00) 		0.732
(1.00) 		1
(1.00)
17p gain 36 (23%) 120 0.187
(1.00) 		0.0236
(1.00) 		0.702
(1.00) 		0.109
(1.00)
17q gain 32 (21%) 124 0.649
(1.00) 		0.0922
(1.00) 		0.0709
(1.00) 		0.0278
(1.00)
18p gain 27 (17%) 129 0.14
(1.00) 		0.00844
(1.00) 		0.525
(1.00) 		0.263
(1.00)
18q gain 21 (13%) 135 0.255
(1.00) 		0.0189
(1.00) 		0.352
(1.00) 		0.552
(1.00)
19q gain 37 (24%) 119 0.54
(1.00) 		0.00114
(0.355) 		0.85
(1.00) 		0.602
(1.00)
20p gain 40 (26%) 116 0.0172
(1.00) 		0.0163
(1.00) 		0.584
(1.00) 		0.371
(1.00)
21q gain 34 (22%) 122 0.0384
(1.00) 		0.114
(1.00) 		0.698
(1.00) 		0.165
(1.00)
22q gain 36 (23%) 120 0.433
(1.00) 		0.0104
(1.00) 		0.183
(1.00) 		0.499
(1.00)
xq gain 19 (12%) 137 0.817
(1.00) 		0.942
(1.00) 		0.625
(1.00) 		1
(1.00)
1p loss 22 (14%) 134 0.0782
(1.00) 		0.282
(1.00) 		0.0022
(0.675) 		0.236
(1.00)
1q loss 22 (14%) 134 0.777
(1.00) 		0.76
(1.00) 		0.0381
(1.00) 		0.684
(1.00)
2p loss 49 (31%) 107 0.785
(1.00) 		0.0744
(1.00) 		0.0818
(1.00) 		0.292
(1.00)
2q loss 40 (26%) 116 0.00508
(1.00) 		0.00149
(0.461) 		1
(1.00) 		0.0961
(1.00)
3p loss 33 (21%) 123 0.0151
(1.00) 		0.111
(1.00) 		1
(1.00) 		0.869
(1.00)
3q loss 31 (20%) 125 0.00719
(1.00) 		0.0217
(1.00) 		0.843
(1.00) 		1
(1.00)
4p loss 24 (15%) 132 0.104
(1.00) 		0.339
(1.00) 		0.655
(1.00) 		0.38
(1.00)
4q loss 32 (21%) 124 0.921
(1.00) 		0.533
(1.00) 		0.161
(1.00) 		0.589
(1.00)
5p loss 14 (9%) 142 0.977
(1.00) 		0.862
(1.00) 		0.585
(1.00) 		0.455
(1.00)
5q loss 21 (13%) 135 0.446
(1.00) 		0.564
(1.00) 		0.643
(1.00) 		0.353
(1.00)
6p loss 38 (24%) 118 0.0353
(1.00) 		0.988
(1.00) 		0.579
(1.00) 		0.36
(1.00)
6q loss 31 (20%) 125 0.239
(1.00) 		0.396
(1.00) 		0.224
(1.00) 		0.774
(1.00)
7p loss 23 (15%) 133 0.306
(1.00) 		0.245
(1.00) 		0.255
(1.00) 		0.481
(1.00)
7q loss 21 (13%) 135 0.146
(1.00) 		0.256
(1.00) 		0.814
(1.00) 		0.862
(1.00)
8p loss 34 (22%) 122 0.7
(1.00) 		0.489
(1.00) 		0.559
(1.00) 		0.765
(1.00)
8q loss 27 (17%) 129 0.874
(1.00) 		0.137
(1.00) 		0.289
(1.00) 		0.5
(1.00)
9p loss 50 (32%) 106 0.887
(1.00) 		0.0183
(1.00) 		0.12
(1.00) 		0.448
(1.00)
9q loss 29 (19%) 127 0.175
(1.00) 		0.185
(1.00) 		0.539
(1.00) 		0.255
(1.00)
11p loss 60 (38%) 96 0.934
(1.00) 		0.00764
(1.00) 		0.323
(1.00) 		0.615
(1.00)
11q loss 51 (33%) 105 0.716
(1.00) 		0.0785
(1.00) 		0.494
(1.00) 		0.9
(1.00)
12p loss 37 (24%) 119 0.66
(1.00) 		0.233
(1.00) 		1
(1.00) 		0.534
(1.00)
12q loss 32 (21%) 124 0.632
(1.00) 		0.833
(1.00) 		0.161
(1.00) 		0.489
(1.00)
14q loss 37 (24%) 119 0.077
(1.00) 		0.782
(1.00) 		1
(1.00) 		0.685
(1.00)
15q loss 29 (19%) 127 0.00421
(1.00) 		0.155
(1.00) 		0.679
(1.00) 		0.762
(1.00)
16p loss 47 (30%) 109 0.97
(1.00) 		0.152
(1.00) 		0.159
(1.00) 		0.525
(1.00)
16q loss 78 (50%) 78 0.685
(1.00) 		0.0123
(1.00) 		0.0754
(1.00) 		0.485
(1.00)
17p loss 30 (19%) 126 0.177
(1.00) 		0.302
(1.00) 		0.688
(1.00) 		0.569
(1.00)
17q loss 26 (17%) 130 0.247
(1.00) 		0.212
(1.00) 		0.83
(1.00) 		0.739
(1.00)
18p loss 33 (21%) 123 0.303
(1.00) 		0.751
(1.00) 		0.113
(1.00) 		1
(1.00)
18q loss 37 (24%) 119 0.31
(1.00) 		0.0379
(1.00) 		0.26
(1.00) 		1
(1.00)
19p loss 13 (8%) 143 0.666
(1.00) 		0.729
(1.00) 		0.393
(1.00) 		0.32
(1.00)
19q loss 21 (13%) 135 0.802
(1.00) 		0.6
(1.00) 		1
(1.00) 		0.378
(1.00)
20p loss 27 (17%) 129 0.687
(1.00) 		0.0837
(1.00) 		0.289
(1.00) 		0.575
(1.00)
20q loss 12 (8%) 144 0.481
(1.00) 		0.246
(1.00) 		1
(1.00) 		1
(1.00)
21q loss 34 (22%) 122 0.0141
(1.00) 		0.00367
(1.00) 		1
(1.00) 		1
(1.00)
22q loss 45 (29%) 111 0.72
(1.00) 		0.503
(1.00) 		0.217
(1.00) 		0.896
(1.00)
xq loss 59 (38%) 97 0.151
(1.00) 		0.937
(1.00) 		0.135
(1.00) 		0.378
(1.00)
'7p gain' versus 'AGE'

P value = 0.000122 (Wilcoxon-test), Q value = 0.039

Table S1.  Gene #13: '7p gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 156 61.5 (13.4)
7P GAIN MUTATED 45 67.5 (12.1)
7P GAIN WILD-TYPE 111 59.1 (13.2)

Figure S1.  Get High-res Image Gene #13: '7p gain' versus Clinical Feature #2: 'AGE'

'7q gain' versus 'AGE'

P value = 8.25e-06 (Wilcoxon-test), Q value = 0.0026

Table S2.  Gene #14: '7q gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 156 61.5 (13.4)
7Q GAIN MUTATED 36 69.8 (10.3)
7Q GAIN WILD-TYPE 120 59.0 (13.3)

Figure S2.  Get High-res Image Gene #14: '7q gain' versus Clinical Feature #2: 'AGE'

'11p gain' versus 'Time to Death'

P value = 4.88e-06 (logrank test), Q value = 0.0016

Table S3.  Gene #21: '11p gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 155 51 0.1 - 175.0 (18.2)
11P GAIN MUTATED 12 8 1.1 - 21.3 (12.6)
11P GAIN WILD-TYPE 143 43 0.1 - 175.0 (20.3)

Figure S3.  Get High-res Image Gene #21: '11p gain' versus Clinical Feature #1: 'Time to Death'

'11q gain' versus 'Time to Death'

P value = 0.000332 (logrank test), Q value = 0.1

Table S4.  Gene #22: '11q gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 155 51 0.1 - 175.0 (18.2)
11Q GAIN MUTATED 11 7 1.1 - 24.3 (14.0)
11Q GAIN WILD-TYPE 144 44 0.1 - 175.0 (19.4)

Figure S4.  Get High-res Image Gene #22: '11q gain' versus Clinical Feature #1: 'Time to Death'

'19p gain' versus 'AGE'

P value = 0.000559 (Wilcoxon-test), Q value = 0.17

Table S5.  Gene #34: '19p gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 156 61.5 (13.4)
19P GAIN MUTATED 47 66.9 (11.3)
19P GAIN WILD-TYPE 109 59.2 (13.7)

Figure S5.  Get High-res Image Gene #34: '19p gain' versus Clinical Feature #2: 'AGE'

'20q gain' versus 'AGE'

P value = 0.000734 (Wilcoxon-test), Q value = 0.23

Table S6.  Gene #37: '20q gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 156 61.5 (13.4)
20Q GAIN MUTATED 53 66.7 (13.0)
20Q GAIN WILD-TYPE 103 58.8 (12.9)

Figure S6.  Get High-res Image Gene #37: '20q gain' versus Clinical Feature #2: 'AGE'

'10p loss' versus 'GENDER'

P value = 0.000181 (Fisher's exact test), Q value = 0.057

Table S7.  Gene #59: '10p loss' versus Clinical Feature #3: 'GENDER'

nPatients FEMALE MALE
ALL 88 68
10P LOSS MUTATED 53 20
10P LOSS WILD-TYPE 35 48

Figure S7.  Get High-res Image Gene #59: '10p loss' versus Clinical Feature #3: 'GENDER'

'10q loss' versus 'GENDER'

P value = 5.11e-05 (Fisher's exact test), Q value = 0.016

Table S8.  Gene #60: '10q loss' versus Clinical Feature #3: 'GENDER'

nPatients FEMALE MALE
ALL 88 68
10Q LOSS MUTATED 60 24
10Q LOSS WILD-TYPE 28 44

Figure S8.  Get High-res Image Gene #60: '10q loss' versus Clinical Feature #3: 'GENDER'

'13q loss' versus 'AGE'

P value = 0.000106 (Wilcoxon-test), Q value = 0.034

Table S9.  Gene #65: '13q loss' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 156 61.5 (13.4)
13Q LOSS MUTATED 82 65.3 (12.7)
13Q LOSS WILD-TYPE 74 57.3 (13.1)

Figure S9.  Get High-res Image Gene #65: '13q loss' versus Clinical Feature #2: 'AGE'

Methods & Data
Input

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

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

  • Number of patients = 156

  • Number of significantly arm-level cnvs = 80

  • Number of selected clinical features = 4

  • 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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