Correlation between copy number variations of arm-level result and selected clinical features
Sarcoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C18051D7
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/C18051D7
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 114 patients, 6 significant findings detected with Q value < 0.25.

  • 7p gain cnv correlated to 'AGE'.

  • 7q gain cnv correlated to 'AGE'.

  • 9q gain cnv correlated to 'AGE'.

  • 12p gain cnv correlated to 'Time to Death' and 'AGE'.

  • 10q loss cnv correlated to 'GENDER'.

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, 6 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
12p gain 13 (11%) 101 3.47e-05
(0.011) 		7.76e-05
(0.0246) 		1
(1.00) 		0.0755
(1.00)
7p gain 29 (25%) 85 0.302
(1.00) 		2.39e-05
(0.00762) 		0.198
(1.00) 		0.558
(1.00)
7q gain 25 (22%) 89 0.538
(1.00) 		1.53e-06
(0.000491) 		1
(1.00) 		0.305
(1.00)
9q gain 26 (23%) 88 0.53
(1.00) 		0.000127
(0.0403) 		0.824
(1.00) 		0.613
(1.00)
10q loss 62 (54%) 52 0.263
(1.00) 		0.351
(1.00) 		0.000144
(0.0455) 		0.791
(1.00)
1p gain 21 (18%) 93 0.0358
(1.00) 		0.549
(1.00) 		0.478
(1.00) 		0.469
(1.00)
1q gain 23 (20%) 91 0.509
(1.00) 		0.0475
(1.00) 		0.349
(1.00) 		1
(1.00)
2p gain 10 (9%) 104 0.14
(1.00) 		0.184
(1.00) 		0.753
(1.00) 		0.429
(1.00)
2q gain 7 (6%) 107 0.469
(1.00) 		0.313
(1.00) 		1
(1.00) 		0.265
(1.00)
3p gain 12 (11%) 102 0.965
(1.00) 		0.0945
(1.00) 		1
(1.00) 		0.191
(1.00)
3q gain 11 (10%) 103 0.916
(1.00) 		0.00875
(1.00) 		0.752
(1.00) 		0.349
(1.00)
4p gain 23 (20%) 91 0.554
(1.00) 		0.84
(1.00) 		0.159
(1.00) 		0.0918
(1.00)
4q gain 17 (15%) 97 0.797
(1.00) 		0.333
(1.00) 		0.795
(1.00) 		0.269
(1.00)
5p gain 36 (32%) 78 0.397
(1.00) 		0.0953
(1.00) 		0.419
(1.00) 		0.206
(1.00)
5q gain 30 (26%) 84 0.224
(1.00) 		0.526
(1.00) 		0.0558
(1.00) 		0.103
(1.00)
6p gain 22 (19%) 92 0.203
(1.00) 		0.00108
(0.339) 		0.353
(1.00) 		0.553
(1.00)
6q gain 21 (18%) 93 0.457
(1.00) 		0.00673
(1.00) 		0.813
(1.00) 		0.576
(1.00)
8p gain 25 (22%) 89 0.00252
(0.777) 		0.489
(1.00) 		0.364
(1.00) 		0.00818
(1.00)
8q gain 29 (25%) 85 0.00332
(1.00) 		0.609
(1.00) 		0.198
(1.00) 		0.0224
(1.00)
9p gain 19 (17%) 95 0.101
(1.00) 		0.005
(1.00) 		0.805
(1.00) 		1
(1.00)
10p gain 10 (9%) 104 0.0692
(1.00) 		0.253
(1.00) 		0.753
(1.00) 		0.703
(1.00)
10q gain 4 (4%) 110 0.00128
(0.401) 		0.584
(1.00) 		0.33
(1.00) 		1
(1.00)
11p gain 6 (5%) 108 0.00427
(1.00) 		0.00179
(0.556) 		0.217
(1.00) 		1
(1.00)
11q gain 5 (4%) 109 0.301
(1.00) 		0.58
(1.00) 		0.374
(1.00) 		1
(1.00)
12q gain 8 (7%) 106 0.381
(1.00) 		0.0107
(1.00) 		0.726
(1.00) 		0.028
(1.00)
13q gain 6 (5%) 108 0.75
(1.00) 		0.22
(1.00) 		0.217
(1.00) 		0.0762
(1.00)
14q gain 21 (18%) 93 0.0361
(1.00) 		0.637
(1.00) 		0.813
(1.00) 		0.727
(1.00)
15q gain 29 (25%) 85 0.0919
(1.00) 		0.146
(1.00) 		0.0853
(1.00) 		0.761
(1.00)
16p gain 17 (15%) 97 0.0069
(1.00) 		0.176
(1.00) 		0.795
(1.00) 		0.309
(1.00)
16q gain 6 (5%) 108 0.839
(1.00) 		0.469
(1.00) 		1
(1.00) 		1
(1.00)
17p gain 22 (19%) 92 0.0781
(1.00) 		0.0245
(1.00) 		1
(1.00) 		0.197
(1.00)
17q gain 16 (14%) 98 0.436
(1.00) 		0.0752
(1.00) 		0.0287
(1.00) 		0.0914
(1.00)
18p gain 17 (15%) 97 0.473
(1.00) 		0.0541
(1.00) 		0.434
(1.00) 		0.806
(1.00)
18q gain 16 (14%) 98 0.472
(1.00) 		0.00573
(1.00) 		0.282
(1.00) 		0.789
(1.00)
19p gain 33 (29%) 81 0.0252
(1.00) 		0.00982
(1.00) 		1
(1.00) 		0.345
(1.00)
19q gain 22 (19%) 92 0.668
(1.00) 		0.00221
(0.685) 		0.643
(1.00) 		0.411
(1.00)
20p gain 28 (25%) 86 0.112
(1.00) 		0.0574
(1.00) 		1
(1.00) 		0.863
(1.00)
20q gain 35 (31%) 79 0.195
(1.00) 		0.0451
(1.00) 		0.689
(1.00) 		0.6
(1.00)
21q gain 26 (23%) 88 0.0823
(1.00) 		0.0892
(1.00) 		0.658
(1.00) 		0.16
(1.00)
22q gain 26 (23%) 88 0.106
(1.00) 		0.123
(1.00) 		0.116
(1.00) 		0.165
(1.00)
xq gain 14 (12%) 100 0.767
(1.00) 		0.955
(1.00) 		1
(1.00) 		1
(1.00)
1p loss 16 (14%) 98 0.0365
(1.00) 		0.302
(1.00) 		0.0287
(1.00) 		0.115
(1.00)
1q loss 16 (14%) 98 0.466
(1.00) 		0.692
(1.00) 		0.282
(1.00) 		1
(1.00)
2p loss 32 (28%) 82 0.816
(1.00) 		0.0884
(1.00) 		0.148
(1.00) 		0.517
(1.00)
2q loss 27 (24%) 87 0.00267
(0.824) 		0.023
(1.00) 		0.66
(1.00) 		0.154
(1.00)
3p loss 20 (18%) 94 0.0172
(1.00) 		0.3
(1.00) 		0.46
(1.00) 		1
(1.00)
3q loss 24 (21%) 90 0.0753
(1.00) 		0.472
(1.00) 		0.366
(1.00) 		0.854
(1.00)
4p loss 18 (16%) 96 0.0347
(1.00) 		0.658
(1.00) 		1
(1.00) 		0.199
(1.00)
4q loss 22 (19%) 92 0.74
(1.00) 		0.442
(1.00) 		0.353
(1.00) 		0.351
(1.00)
5p loss 9 (8%) 105 0.175
(1.00) 		0.764
(1.00) 		1
(1.00) 		1
(1.00)
5q loss 15 (13%) 99 0.366
(1.00) 		0.361
(1.00) 		0.783
(1.00) 		1
(1.00)
6p loss 28 (25%) 86 0.156
(1.00) 		0.664
(1.00) 		0.828
(1.00) 		0.163
(1.00)
6q loss 17 (15%) 97 0.471
(1.00) 		0.09
(1.00) 		0.19
(1.00) 		0.426
(1.00)
7p loss 16 (14%) 98 0.41
(1.00) 		0.948
(1.00) 		0.18
(1.00) 		0.311
(1.00)
7q loss 14 (12%) 100 0.023
(1.00) 		0.789
(1.00) 		0.401
(1.00) 		1
(1.00)
8p loss 24 (21%) 90 0.97
(1.00) 		0.465
(1.00) 		0.49
(1.00) 		0.708
(1.00)
8q loss 14 (12%) 100 0.962
(1.00) 		0.158
(1.00) 		0.253
(1.00) 		0.271
(1.00)
9p loss 34 (30%) 80 0.887
(1.00) 		0.0301
(1.00) 		0.411
(1.00) 		0.773
(1.00)
9q loss 23 (20%) 91 0.128
(1.00) 		0.349
(1.00) 		0.64
(1.00) 		0.158
(1.00)
10p loss 52 (46%) 62 0.657
(1.00) 		0.0224
(1.00) 		0.0013
(0.406) 		0.458
(1.00)
11p loss 44 (39%) 70 0.513
(1.00) 		0.0309
(1.00) 		0.704
(1.00) 		0.698
(1.00)
11q loss 36 (32%) 78 0.413
(1.00) 		0.0715
(1.00) 		0.842
(1.00) 		1
(1.00)
12p loss 25 (22%) 89 0.828
(1.00) 		0.848
(1.00) 		1
(1.00) 		0.421
(1.00)
12q loss 26 (23%) 88 0.477
(1.00) 		0.884
(1.00) 		0.263
(1.00) 		0.421
(1.00)
13q loss 55 (48%) 59 0.373
(1.00) 		0.0279
(1.00) 		0.0625
(1.00) 		1
(1.00)
14q loss 30 (26%) 84 0.0832
(1.00) 		0.76
(1.00) 		0.526
(1.00) 		1
(1.00)
15q loss 17 (15%) 97 0.0517
(1.00) 		0.469
(1.00) 		0.795
(1.00) 		1
(1.00)
16p loss 33 (29%) 81 0.613
(1.00) 		0.299
(1.00) 		0.0136
(1.00) 		0.533
(1.00)
16q loss 59 (52%) 55 0.548
(1.00) 		0.0477
(1.00) 		0.0381
(1.00) 		1
(1.00)
17p loss 22 (19%) 92 0.742
(1.00) 		0.356
(1.00) 		1
(1.00) 		0.724
(1.00)
17q loss 22 (19%) 92 0.318
(1.00) 		0.336
(1.00) 		0.643
(1.00) 		0.726
(1.00)
18p loss 27 (24%) 87 0.214
(1.00) 		0.61
(1.00) 		0.0767
(1.00) 		0.537
(1.00)
18q loss 28 (25%) 86 0.0936
(1.00) 		0.182
(1.00) 		0.277
(1.00) 		0.639
(1.00)
19p loss 7 (6%) 107 0.697
(1.00) 		0.108
(1.00) 		0.452
(1.00) 		0.376
(1.00)
19q loss 17 (15%) 97 0.266
(1.00) 		0.0759
(1.00) 		1
(1.00) 		0.335
(1.00)
20p loss 18 (16%) 96 0.761
(1.00) 		0.0985
(1.00) 		0.612
(1.00) 		0.726
(1.00)
20q loss 8 (7%) 106 0.369
(1.00) 		0.0411
(1.00) 		1
(1.00) 		0.702
(1.00)
21q loss 19 (17%) 95 0.119
(1.00) 		0.0934
(1.00) 		0.457
(1.00) 		0.407
(1.00)
22q loss 33 (29%) 81 0.712
(1.00) 		0.16
(1.00) 		0.221
(1.00) 		0.755
(1.00)
xq loss 42 (37%) 72 0.765
(1.00) 		0.563
(1.00) 		0.0527
(1.00) 		0.708
(1.00)
'7p gain' versus 'AGE'

P value = 2.39e-05 (Wilcoxon-test), Q value = 0.0076

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

nPatients Mean (Std.Dev)
ALL 114 61.3 (14.1)
7P GAIN MUTATED 29 70.2 (10.9)
7P GAIN WILD-TYPE 85 58.2 (13.8)

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

'7q gain' versus 'AGE'

P value = 1.53e-06 (Wilcoxon-test), Q value = 0.00049

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

nPatients Mean (Std.Dev)
ALL 114 61.3 (14.1)
7Q GAIN MUTATED 25 72.3 (9.6)
7Q GAIN WILD-TYPE 89 58.2 (13.6)

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

'9q gain' versus 'AGE'

P value = 0.000127 (Wilcoxon-test), Q value = 0.04

Table S3.  Gene #18: '9q gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 114 61.3 (14.1)
9Q GAIN MUTATED 26 69.9 (10.7)
9Q GAIN WILD-TYPE 88 58.7 (14.0)

Figure S3.  Get High-res Image Gene #18: '9q gain' versus Clinical Feature #2: 'AGE'

'12p gain' versus 'Time to Death'

P value = 3.47e-05 (logrank test), Q value = 0.011

Table S4.  Gene #23: '12p gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 114 36 0.1 - 143.4 (17.9)
12P GAIN MUTATED 13 8 0.1 - 37.5 (9.0)
12P GAIN WILD-TYPE 101 28 0.1 - 143.4 (18.2)

Figure S4.  Get High-res Image Gene #23: '12p gain' versus Clinical Feature #1: 'Time to Death'

'12p gain' versus 'AGE'

P value = 7.76e-05 (Wilcoxon-test), Q value = 0.025

Table S5.  Gene #23: '12p gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 114 61.3 (14.1)
12P GAIN MUTATED 13 75.0 (9.1)
12P GAIN WILD-TYPE 101 59.5 (13.6)

Figure S5.  Get High-res Image Gene #23: '12p gain' versus Clinical Feature #2: 'AGE'

'10q loss' versus 'GENDER'

P value = 0.000144 (Fisher's exact test), Q value = 0.045

Table S6.  Gene #60: '10q loss' versus Clinical Feature #3: 'GENDER'

nPatients FEMALE MALE
ALL 62 52
10Q LOSS MUTATED 44 18
10Q LOSS WILD-TYPE 18 34

Figure S6.  Get High-res Image Gene #60: '10q loss' versus Clinical Feature #3: 'GENDER'

Methods & Data
Input

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

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

  • Number of patients = 114

  • 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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