Correlation between copy number variations of arm-level result and selected clinical features
Brain Lower Grade Glioma (Primary solid tumor)
23 September 2013 | analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1X34VQR
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1X34VQR
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 71 arm-level events and 6 clinical features across 229 patients, 19 significant findings detected with Q value < 0.25.

- 3Q GAIN MUTATION ANALYSIS cnv correlated to 'Time to Death'.

- 7Q GAIN MUTATION ANALYSIS cnv correlated to 'AGE'.

- 19Q GAIN MUTATION ANALYSIS cnv correlated to 'Time to Death' and 'AGE'.

- 20P GAIN MUTATION ANALYSIS cnv correlated to 'Time to Death' and 'AGE'.

- 20Q GAIN MUTATION ANALYSIS cnv correlated to 'Time to Death' and 'AGE'.

- 1P LOSS MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

- 10P LOSS MUTATION ANALYSIS cnv correlated to 'Time to Death', 'AGE', and 'HISTOLOGICAL.TYPE'.

- 10Q LOSS MUTATION ANALYSIS cnv correlated to 'Time to Death', 'AGE', and 'HISTOLOGICAL.TYPE'.

- 11Q LOSS MUTATION ANALYSIS cnv correlated to 'Time to Death'.

- 17P LOSS MUTATION ANALYSIS cnv correlated to 'Time to Death' and 'AGE'.

- 19Q LOSS MUTATION ANALYSIS cnv correlated to 'HISTOLOGICAL.TYPE'.

Results
Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 71 arm-level events and 6 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 19 significant findings detected.

|  | Clinical Features | Time to Death | AGE | GENDER | KARNOFSKY PERFORMANCE SCORE | HISTOLOGICAL TYPE | RADIATIONS RADIATION REGIMENINDICATION
| nCNV (%) | nWild-Type | logrank test | t-test | Fisher's exact test | t-test | Fisher's exact test | Fisher's exact test
10P LOSS MUTATION ANALYSIS | 39 (17%) | 190 | 1.15e-12 (4.84e-10) | 1.43e-08 (5.97e-06) | 0.0219 (1.00) | 0.305 (1.00) | 0.000156 (0.0639) | 0.473 (1.00)
10Q LOSS MUTATION ANALYSIS | 47 (21%) | 182 | 5.03e-06 (0.00209) | 2.25e-07 (9.36e-05) | 0.022 (1.00) | 0.644 (1.00) | 0.000297 (0.12) | 0.738 (1.00)
19Q GAIN MUTATION ANALYSIS | 11 (5%) | 218 | 5.1e-05 (0.021) | 0.00058 (0.234) | 0.758 (1.00) | 0.243 (1.00) | 0.455 (1.00) | 0.349 (1.00)
20P GAIN MUTATION ANALYSIS | 22 (10%) | 207 | 9.19e-07 (0.000382) | 8.28e-05 (0.034) | 0.178 (1.00) | 0.746 (1.00) | 0.354 (1.00) | 0.5 (1.00)
20Q GAIN MUTATION ANALYSIS | 22 (10%) | 207 | 2.34e-05 (0.00969) | 0.00025 (0.102) | 0.0717 (1.00) | 0.841 (1.00) | 0.515 (1.00) | 0.5 (1.00)
17P LOSS MUTATION ANALYSIS | 10 (4%) | 219 | 0.000276 (0.112) | 0.000572 (0.231) | 0.114 (1.00) | 0.142 (1.00) | 0.849 (1.00) | 0.323 (1.00)
3Q GAIN MUTATION ANALYSIS | 7 (3%) | 222 | 0.000245 (0.0998) | 0.0857 (1.00) | 0.703 (1.00) | 0.273 (1.00) | 0.0708 (1.00) | 0.438 (1.00)
7Q GAIN MUTATION ANALYSIS | 68 (30%) | 161 | 0.00349 (1.00) | 8.53e-05 (0.035) | 0.192 (1.00) | 0.605 (1.00) | 0.188 (1.00) | 0.768 (1.00)
1P LOSS MUTATION ANALYSIS | 76 (33%) | 153 | 0.0678 (1.00) | 0.0285 (1.00) | 1 (1.00) | 0.647 (1.00) | 9.42e-18 (3.97e-15) | 0.0616 (1.00)
11Q LOSS MUTATION ANALYSIS | 9 (4%) | 220 | 4.94e-05 (0.0204) | 0.159 (1.00) | 0.192 (1.00) | 0.439 (1.00) | 0.14 (1.00) | 0.488 (1.00)
19Q LOSS MUTATION ANALYSIS | 87 (38%) | 142 | 0.161 (1.00) | 0.186 (1.00) | 0.495 (1.00) | 0.882 (1.00) | 6.56e-14 (2.75e-11) | 0.405 (1.00)
1P GAIN MUTATION ANALYSIS | 8 (3%) | 221 | 0.00145 (0.58) | 0.0897 (1.00) | 0.144 (1.00) | 0.0763 (1.00) | 0.00267 (1.00) | 1 (1.00)
1Q GAIN MUTATION ANALYSIS | 12 (5%) | 217 | 0.828 (1.00) | 0.00363 (1.00) | 0.14 (1.00) | 0.44 (1.00) | 0.134 (1.00) | 1 (1.00)
2P GAIN MUTATION ANALYSIS | 5 (2%) | 224 | 0.865 (1.00) | 0.259 (1.00) | 0.658 (1.00) | 0.353 (1.00) | 0.522 (1.00) | 1 (1.00)
2Q GAIN MUTATION ANALYSIS | 5 (2%) | 224 | 0.865 (1.00) | 0.259 (1.00) | 0.658 (1.00) | 0.353 (1.00) | 0.522 (1.00) | 1 (1.00)
3P GAIN MUTATION ANALYSIS | 7 (3%) | 222 | 0.0109 (1.00) | 0.0901 (1.00) | 0.247 (1.00) | 0.704 (1.00) | 0.159 (1.00) | 1 (1.00)
6P GAIN MUTATION ANALYSIS | 4 (2%) | 225 | 0.751 (1.00) | 0.341 (1.00) | 1 (1.00) | 0.0763 (1.00) | 0.487 (1.00) | 0.647 (1.00)
6Q GAIN MUTATION ANALYSIS | 3 (1%) | 226 | 0.712 (1.00) | 0.666 (1.00) | 0.587 (1.00) | 0.0763 (1.00) | 0.487 (1.00) | 0.563 (1.00)
7P GAIN MUTATION ANALYSIS | 54 (24%) | 175 | 0.00683 (1.00) | 0.00193 (0.772) | 0.0844 (1.00) | 0.876 (1.00) | 0.17 (1.00) | 0.874 (1.00)
8P GAIN MUTATION ANALYSIS | 22 (10%) | 207 | 0.609 (1.00) | 0.447 (1.00) | 0.261 (1.00) | 0.978 (1.00) | 0.138 (1.00) | 0.822 (1.00)
8Q GAIN MUTATION ANALYSIS | 27 (12%) | 202 | 0.884 (1.00) | 0.106 (1.00) | 0.225 (1.00) | 0.554 (1.00) | 0.0278 (1.00) | 0.837 (1.00)
9P GAIN MUTATION ANALYSIS | 8 (3%) | 221 | 0.021 (1.00) | 0.102 (1.00) | 0.144 (1.00) | 0.5 (1.00) | 0.547 (1.00) | 1 (1.00)
9Q GAIN MUTATION ANALYSIS | 9 (4%) | 220 | 0.00693 (1.00) | 0.0708 (1.00) | 0.0118 (1.00) | 0.788 (1.00) | 0.479 (1.00) | 1 (1.00)
10P GAIN MUTATION ANALYSIS | 25 (11%) | 204 | 0.645 (1.00) | 0.0345 (1.00) | 0.0904 (1.00) | 0.0594 (1.00) | 0.0641 (1.00) | 0.00393 (1.00)
10Q GAIN MUTATION ANALYSIS | 3 (1%) | 226 | 0.414 (1.00) | 0.113 (1.00) | 0.256 (1.00) |  | 0.0507 (1.00) | 0.0595 (1.00)
11P GAIN MUTATION ANALYSIS | 17 (7%) | 212 | 0.892 (1.00) | 0.0255 (1.00) | 0.613 (1.00) | 0.884 (1.00) | 0.409 (1.00) | 0.801 (1.00)
11Q GAIN MUTATION ANALYSIS | 25 (11%) | 204 | 0.489 (1.00) | 0.0185 (1.00) | 0.832 (1.00) | 0.973 (1.00) | 0.492 (1.00) | 1 (1.00)
12P GAIN MUTATION ANALYSIS | 16 (7%) | 213 | 0.53 (1.00) | 0.147 (1.00) | 0.307 (1.00) | 0.0763 (1.00) | 1 (1.00) | 1 (1.00)
12Q GAIN MUTATION ANALYSIS | 8 (3%) | 221 | 0.0586 (1.00) | 0.721 (1.00) | 1 (1.00) | 0.0763 (1.00) | 0.815 (1.00) | 0.485 (1.00)
15Q GAIN MUTATION ANALYSIS | 5 (2%) | 224 | 0.48 (1.00) | 0.14 (1.00) | 0.385 (1.00) | 0.666 (1.00) | 0.617 (1.00) | 1 (1.00)
16P GAIN MUTATION ANALYSIS | 7 (3%) | 222 | 0.433 (1.00) | 0.136 (1.00) | 0.247 (1.00) |  | 0.425 (1.00) | 0.707 (1.00)
16Q GAIN MUTATION ANALYSIS | 9 (4%) | 220 | 0.149 (1.00) | 0.157 (1.00) | 0.517 (1.00) | 0.771 (1.00) | 0.0946 (1.00) | 0.741 (1.00)
17P GAIN MUTATION ANALYSIS | 5 (2%) | 224 | 0.198 (1.00) | 0.495 (1.00) | 0.385 (1.00) | 0.704 (1.00) | 0.278 (1.00) | 0.0795 (1.00)
17Q GAIN MUTATION ANALYSIS | 5 (2%) | 224 | 0.198 (1.00) | 0.495 (1.00) | 0.385 (1.00) | 0.704 (1.00) | 0.278 (1.00) | 0.0795 (1.00)
18P GAIN MUTATION ANALYSIS | 9 (4%) | 220 | 0.315 (1.00) | 0.9 (1.00) | 1 (1.00) | 0.0763 (1.00) | 0.291 (1.00) | 0.488 (1.00)
18Q GAIN MUTATION ANALYSIS | 6 (3%) | 223 | 0.0455 (1.00) | 0.502 (1.00) | 1 (1.00) |  | 0.44 (1.00) | 0.407 (1.00)
19P GAIN MUTATION ANALYSIS | 36 (16%) | 193 | 0.416 (1.00) | 0.00344 (1.00) | 1 (1.00) | 0.796 (1.00) | 0.127 (1.00) | 1 (1.00)
21Q GAIN MUTATION ANALYSIS | 10 (4%) | 219 | 0.966 (1.00) | 0.484 (1.00) | 0.755 (1.00) |  | 0.105 (1.00) | 1 (1.00)
22Q GAIN MUTATION ANALYSIS | 7 (3%) | 222 | 0.295 (1.00) | 0.212 (1.00) | 0.703 (1.00) | 0.704 (1.00) | 0.0611 (1.00) | 1 (1.00)
XQ GAIN MUTATION ANALYSIS | 18 (8%) | 211 | 0.559 (1.00) | 0.165 (1.00) | 0.0813 (1.00) | 0.836 (1.00) | 0.234 (1.00) | 0.451 (1.00)
1Q LOSS MUTATION ANALYSIS | 14 (6%) | 215 | 0.726 (1.00) | 0.152 (1.00) | 0.409 (1.00) | 0.289 (1.00) | 0.0463 (1.00) | 0.784 (1.00)
2P LOSS MUTATION ANALYSIS | 9 (4%) | 220 | 0.138 (1.00) | 0.701 (1.00) | 0.305 (1.00) | 0.0625 (1.00) | 0.479 (1.00) | 0.741 (1.00)
2Q LOSS MUTATION ANALYSIS | 7 (3%) | 222 | 0.501 (1.00) | 0.00747 (1.00) | 0.466 (1.00) | 0.166 (1.00) | 0.267 (1.00) | 1 (1.00)
3P LOSS MUTATION ANALYSIS | 9 (4%) | 220 | 0.122 (1.00) | 0.0584 (1.00) | 0.305 (1.00) | 0.958 (1.00) | 0.914 (1.00) | 0.741 (1.00)
3Q LOSS MUTATION ANALYSIS | 15 (7%) | 214 | 0.107 (1.00) | 0.836 (1.00) | 0.185 (1.00) | 0.271 (1.00) | 0.748 (1.00) | 1 (1.00)
4P LOSS MUTATION ANALYSIS | 37 (16%) | 192 | 0.735 (1.00) | 0.0494 (1.00) | 0.278 (1.00) | 0.554 (1.00) | 0.0913 (1.00) | 0.587 (1.00)
4Q LOSS MUTATION ANALYSIS | 46 (20%) | 183 | 0.306 (1.00) | 0.424 (1.00) | 0.507 (1.00) | 0.61 (1.00) | 0.0566 (1.00) | 0.866 (1.00)
5P LOSS MUTATION ANALYSIS | 19 (8%) | 210 | 0.497 (1.00) | 0.0974 (1.00) | 0.147 (1.00) | 0.362 (1.00) | 0.038 (1.00) | 0.047 (1.00)
5Q LOSS MUTATION ANALYSIS | 17 (7%) | 212 | 0.137 (1.00) | 0.819 (1.00) | 0.806 (1.00) | 0.0687 (1.00) | 0.565 (1.00) | 0.0372 (1.00)
6P LOSS MUTATION ANALYSIS | 14 (6%) | 215 | 0.0214 (1.00) | 0.586 (1.00) | 0.784 (1.00) | 0.319 (1.00) | 0.0252 (1.00) | 0.574 (1.00)
6Q LOSS MUTATION ANALYSIS | 29 (13%) | 200 | 0.00389 (1.00) | 0.124 (1.00) | 0.113 (1.00) | 0.166 (1.00) | 0.00422 (1.00) | 0.314 (1.00)
8P LOSS MUTATION ANALYSIS | 8 (3%) | 221 | 0.124 (1.00) | 0.112 (1.00) | 1 (1.00) | 0.824 (1.00) | 0.243 (1.00) | 0.715 (1.00)
8Q LOSS MUTATION ANALYSIS | 6 (3%) | 223 | 0.00478 (1.00) | 0.0997 (1.00) | 0.411 (1.00) | 0.824 (1.00) | 0.216 (1.00) | 1 (1.00)
9P LOSS MUTATION ANALYSIS | 55 (24%) | 174 | 0.0098 (1.00) | 0.053 (1.00) | 0.534 (1.00) | 0.74 (1.00) | 0.104 (1.00) | 0.113 (1.00)
9Q LOSS MUTATION ANALYSIS | 22 (10%) | 207 | 0.0403 (1.00) | 0.0402 (1.00) | 1 (1.00) | 0.158 (1.00) | 0.47 (1.00) | 0.822 (1.00)
11P LOSS MUTATION ANALYSIS | 28 (12%) | 201 | 0.451 (1.00) | 0.308 (1.00) | 0.162 (1.00) | 0.731 (1.00) | 0.0929 (1.00) | 0.417 (1.00)
12P LOSS MUTATION ANALYSIS | 13 (6%) | 216 | 0.539 (1.00) | 0.2 (1.00) | 0.571 (1.00) | 0.345 (1.00) | 0.333 (1.00) | 1 (1.00)
12Q LOSS MUTATION ANALYSIS | 21 (9%) | 208 | 0.348 (1.00) | 0.307 (1.00) | 1 (1.00) | 0.667 (1.00) | 0.304 (1.00) | 0.484 (1.00)
13Q LOSS MUTATION ANALYSIS | 59 (26%) | 170 | 0.769 (1.00) | 0.248 (1.00) | 0.544 (1.00) | 0.362 (1.00) | 0.2 (1.00) | 0.0888 (1.00)
14Q LOSS MUTATION ANALYSIS | 37 (16%) | 192 | 0.00103 (0.414) | 0.0208 (1.00) | 0.373 (1.00) | 0.198 (1.00) | 0.289 (1.00) | 0.714 (1.00)
15Q LOSS MUTATION ANALYSIS | 19 (8%) | 210 | 0.464 (1.00) | 0.931 (1.00) | 0.631 (1.00) | 0.811 (1.00) | 0.83 (1.00) | 0.81 (1.00)
16P LOSS MUTATION ANALYSIS | 7 (3%) | 222 | 0.408 (1.00) | 0.0647 (1.00) | 1 (1.00) | 0.439 (1.00) | 0.425 (1.00) | 0.438 (1.00)
16Q LOSS MUTATION ANALYSIS | 12 (5%) | 217 | 0.275 (1.00) | 0.0195 (1.00) | 0.379 (1.00) | 0.619 (1.00) | 0.361 (1.00) | 0.546 (1.00)
17Q LOSS MUTATION ANALYSIS | 7 (3%) | 222 | 0.0228 (1.00) | 0.0181 (1.00) | 0.703 (1.00) | 0.319 (1.00) | 0.721 (1.00) | 0.707 (1.00)
18P LOSS MUTATION ANALYSIS | 27 (12%) | 202 | 0.563 (1.00) | 0.709 (1.00) | 0.225 (1.00) | 0.548 (1.00) | 0.813 (1.00) | 0.675 (1.00)
18Q LOSS MUTATION ANALYSIS | 28 (12%) | 201 | 0.304 (1.00) | 0.663 (1.00) | 0.686 (1.00) | 0.852 (1.00) | 0.565 (1.00) | 0.685 (1.00)
19P LOSS MUTATION ANALYSIS | 13 (6%) | 216 | 0.88 (1.00) | 0.197 (1.00) | 0.777 (1.00) | 0.352 (1.00) | 0.937 (1.00) | 0.141 (1.00)
20P LOSS MUTATION ANALYSIS | 3 (1%) | 226 | 0.485 (1.00) | 0.545 (1.00) | 0.587 (1.00) |  | 1 (1.00) | 1 (1.00)
21Q LOSS MUTATION ANALYSIS | 19 (8%) | 210 | 0.318 (1.00) | 0.429 (1.00) | 0.238 (1.00) | 0.257 (1.00) | 0.0193 (1.00) | 0.625 (1.00)
22Q LOSS MUTATION ANALYSIS | 25 (11%) | 204 | 0.0462 (1.00) | 0.0478 (1.00) | 0.0179 (1.00) | 0.208 (1.00) | 0.0196 (1.00) | 0.83 (1.00)
XQ LOSS MUTATION ANALYSIS | 31 (14%) | 198 | 0.141 (1.00) | 0.411 (1.00) | 1 (1.00) | 0.998 (1.00) | 0.298 (1.00) | 1 (1.00)

'3Q GAIN MUTATION STATUS' versus 'Time to Death'

P value = 0.000245 (logrank test), Q value = 0.1

Table S1. Gene #6: '3Q GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 229 | 55 | 0.0 - 211.2 (14.5)
3Q GAIN MUTATED | 7 | 4 | 0.2 - 41.1 (8.8)
3Q GAIN WILD-TYPE | 222 | 51 | 0.0 - 211.2 (14.5)

Figure S1. Get High-res Image Gene #6: '3Q GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'7Q GAIN MUTATION STATUS' versus 'AGE'

P value = 8.53e-05 (t-test), Q value = 0.035

Table S2. Gene #10: '7Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 229 | 42.8 (13.4)
7Q GAIN MUTATED | 68 | 48.2 (13.4)
7Q GAIN WILD-TYPE | 161 | 40.5 (12.7)

Figure S2. Get High-res Image Gene #10: '7Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'19Q GAIN MUTATION STATUS' versus 'Time to Death'

P value = 5.1e-05 (logrank test), Q value = 0.021

Table S3. Gene #29: '19Q GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 229 | 55 | 0.0 - 211.2 (14.5)
19Q GAIN MUTATED | 11 | 5 | 0.5 - 26.3 (12.2)
19Q GAIN WILD-TYPE | 218 | 50 | 0.0 - 211.2 (14.7)

Figure S3. Get High-res Image Gene #29: '19Q GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'19Q GAIN MUTATION STATUS' versus 'AGE'

P value = 0.00058 (t-test), Q value = 0.23

Table S4. Gene #29: '19Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 229 | 42.8 (13.4)
19Q GAIN MUTATED | 11 | 54.4 (8.4)
19Q GAIN WILD-TYPE | 218 | 42.2 (13.3)

Figure S4. Get High-res Image Gene #29: '19Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'20P GAIN MUTATION STATUS' versus 'Time to Death'

P value = 9.19e-07 (logrank test), Q value = 0.00038

Table S5. Gene #30: '20P GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 229 | 55 | 0.0 - 211.2 (14.5)
20P GAIN MUTATED | 22 | 9 | 0.5 - 41.1 (12.2)
20P GAIN WILD-TYPE | 207 | 46 | 0.0 - 211.2 (14.9)

Figure S5. Get High-res Image Gene #30: '20P GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'20P GAIN MUTATION STATUS' versus 'AGE'

P value = 8.28e-05 (t-test), Q value = 0.034

Table S6. Gene #30: '20P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 229 | 42.8 (13.4)
20P GAIN MUTATED | 22 | 52.3 (9.9)
20P GAIN WILD-TYPE | 207 | 41.8 (13.3)

Figure S6. Get High-res Image Gene #30: '20P GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'20Q GAIN MUTATION STATUS' versus 'Time to Death'

P value = 2.34e-05 (logrank test), Q value = 0.0097

Table S7. Gene #31: '20Q GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 229 | 55 | 0.0 - 211.2 (14.5)
20Q GAIN MUTATED | 22 | 8 | 0.5 - 41.1 (12.2)
20Q GAIN WILD-TYPE | 207 | 47 | 0.0 - 211.2 (14.9)

Figure S7. Get High-res Image Gene #31: '20Q GAIN MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'20Q GAIN MUTATION STATUS' versus 'AGE'

P value = 0.00025 (t-test), Q value = 0.1

Table S8. Gene #31: '20Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 229 | 42.8 (13.4)
20Q GAIN MUTATED | 22 | 51.9 (10.5)
20Q GAIN WILD-TYPE | 207 | 41.8 (13.3)

Figure S8. Get High-res Image Gene #31: '20Q GAIN MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'1P LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 9.42e-18 (Fisher's exact test), Q value = 4e-15

Table S9. Gene #35: '1P LOSS MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 71 | 64 | 93
1P LOSS MUTATED | 5 | 10 | 61
1P LOSS WILD-TYPE | 66 | 54 | 32

Figure S9. Get High-res Image Gene #35: '1P LOSS MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'10P LOSS MUTATION STATUS' versus 'Time to Death'

P value = 1.15e-12 (logrank test), Q value = 4.8e-10

Table S10. Gene #51: '10P LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 229 | 55 | 0.0 - 211.2 (14.5)
10P LOSS MUTATED | 39 | 20 | 0.1 - 134.3 (10.4)
10P LOSS WILD-TYPE | 190 | 35 | 0.0 - 211.2 (15.2)

Figure S10. Get High-res Image Gene #51: '10P LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'10P LOSS MUTATION STATUS' versus 'AGE'

P value = 1.43e-08 (t-test), Q value = 6e-06

Table S11. Gene #51: '10P LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 229 | 42.8 (13.4)
10P LOSS MUTATED | 39 | 53.7 (11.1)
10P LOSS WILD-TYPE | 190 | 40.5 (12.7)

Figure S11. Get High-res Image Gene #51: '10P LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'10P LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000156 (Fisher's exact test), Q value = 0.064

Table S12. Gene #51: '10P LOSS MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 71 | 64 | 93
10P LOSS MUTATED | 23 | 9 | 7
10P LOSS WILD-TYPE | 48 | 55 | 86

Figure S12. Get High-res Image Gene #51: '10P LOSS MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'10Q LOSS MUTATION STATUS' versus 'Time to Death'

P value = 5.03e-06 (logrank test), Q value = 0.0021

Table S13. Gene #52: '10Q LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 229 | 55 | 0.0 - 211.2 (14.5)
10Q LOSS MUTATED | 47 | 25 | 0.1 - 156.2 (12.2)
10Q LOSS WILD-TYPE | 182 | 30 | 0.0 - 211.2 (14.9)

Figure S13. Get High-res Image Gene #52: '10Q LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'10Q LOSS MUTATION STATUS' versus 'AGE'

P value = 2.25e-07 (t-test), Q value = 9.4e-05

Table S14. Gene #52: '10Q LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 229 | 42.8 (13.4)
10Q LOSS MUTATED | 47 | 52.0 (12.3)
10Q LOSS WILD-TYPE | 182 | 40.4 (12.6)

Figure S14. Get High-res Image Gene #52: '10Q LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'10Q LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 0.000297 (Fisher's exact test), Q value = 0.12

Table S15. Gene #52: '10Q LOSS MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 71 | 64 | 93
10Q LOSS MUTATED | 26 | 11 | 10
10Q LOSS WILD-TYPE | 45 | 53 | 83

Figure S15. Get High-res Image Gene #52: '10Q LOSS MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'11Q LOSS MUTATION STATUS' versus 'Time to Death'

P value = 4.94e-05 (logrank test), Q value = 0.02

Table S16. Gene #54: '11Q LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 229 | 55 | 0.0 - 211.2 (14.5)
11Q LOSS MUTATED | 9 | 5 | 0.2 - 41.1 (15.0)
11Q LOSS WILD-TYPE | 220 | 50 | 0.0 - 211.2 (14.5)

Figure S16. Get High-res Image Gene #54: '11Q LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'17P LOSS MUTATION STATUS' versus 'Time to Death'

P value = 0.000276 (logrank test), Q value = 0.11

Table S17. Gene #62: '17P LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 229 | 55 | 0.0 - 211.2 (14.5)
17P LOSS MUTATED | 10 | 4 | 0.1 - 23.7 (12.3)
17P LOSS WILD-TYPE | 219 | 51 | 0.0 - 211.2 (14.5)

Figure S17. Get High-res Image Gene #62: '17P LOSS MUTATION STATUS' versus Clinical Feature #1: 'Time to Death'

'17P LOSS MUTATION STATUS' versus 'AGE'

P value = 0.000572 (t-test), Q value = 0.23

Table S18. Gene #62: '17P LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 229 | 42.8 (13.4)
17P LOSS MUTATED | 10 | 54.7 (7.9)
17P LOSS WILD-TYPE | 219 | 42.2 (13.3)

Figure S18. Get High-res Image Gene #62: '17P LOSS MUTATION STATUS' versus Clinical Feature #2: 'AGE'

'19Q LOSS MUTATION STATUS' versus 'HISTOLOGICAL.TYPE'

P value = 6.56e-14 (Fisher's exact test), Q value = 2.8e-11

Table S19. Gene #67: '19Q LOSS MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 71 | 64 | 93
19Q LOSS MUTATED | 10 | 14 | 63
19Q LOSS WILD-TYPE | 61 | 50 | 30

Figure S19. Get High-res Image Gene #67: '19Q LOSS MUTATION STATUS' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

Methods & Data
Input

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

- Clinical data file = LGG-TP.clin.merged.picked.txt

- Number of patients = 229

- Number of significantly arm-level cnvs = 71

- Number of selected clinical features = 6

- 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

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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

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] 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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