Brain Lower Grade Glioma: Correlation between copy number variations of arm-level result and selected clinical features
(primary solid tumor cohort)
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
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 50 arm-level results and 7 clinical features across 207 patients, 16 significant findings detected with Q value < 0.25.

- 19q gain cnv correlated to 'Time to Death'.

- 20p gain cnv correlated to 'Time to Death'.

- 20q gain cnv correlated to 'Time to Death'.

- 1p loss cnv correlated to 'HISTOLOGICAL.TYPE'.

- 3p loss cnv correlated to 'AGE'.

- 6p loss cnv correlated to 'Time to Death'.

- 10p loss cnv correlated to 'Time to Death', 'AGE', and 'HISTOLOGICCLASSIFICATION'.

- 10q loss cnv correlated to 'Time to Death', 'AGE', 'HISTOLOGICAL.TYPE', and 'HISTOLOGICCLASSIFICATION'.

- 11q loss cnv correlated to 'Time to Death'.

- 19q loss cnv correlated to 'HISTOLOGICAL.TYPE'.

- 22q loss cnv correlated to 'Time to Death'.

Results
Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 50 arm-level results and 7 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 16 significant findings detected.

|  | Clinical Features | Time to Death | AGE | GENDER | KARNOFSKY PERFORMANCE SCORE | HISTOLOGICAL TYPE | HISTOLOGICCLASSIFICATION | RADIATIONS RADIATION REGIMENINDICATION
| nCNV (%) | nWild-Type | logrank test | t-test | Fisher's exact test | t-test | Fisher's exact test | Fisher's exact test | Fisher's exact test
10q loss | 31 (15%) | 176 | 1.88e-10 (6.29e-08) | 3.06e-08 (1.02e-05) | 0.0308 (1.00) | 0.927 (1.00) | 0.000389 (0.126) | 7.47e-06 (0.00247) | 1 (1.00)
10p loss | 30 (14%) | 177 | 8.93e-11 (3e-08) | 6.05e-08 (2.02e-05) | 0.0478 (1.00) | 0.879 (1.00) | 0.00083 (0.267) | 1.48e-05 (0.00487) | 1 (1.00)
19q gain | 8 (4%) | 199 | 0.000661 (0.214) | 0.0102 (1.00) | 1 (1.00) | 0.26 (1.00) | 0.595 (1.00) | 0.0733 (1.00) | 0.721 (1.00)
20p gain | 17 (8%) | 190 | 0.000116 (0.0379) | 0.00665 (1.00) | 0.0744 (1.00) | 0.976 (1.00) | 0.175 (1.00) | 0.207 (1.00) | 0.614 (1.00)
20q gain | 15 (7%) | 192 | 0.000335 (0.109) | 0.0141 (1.00) | 0.0627 (1.00) | 0.893 (1.00) | 0.16 (1.00) | 0.179 (1.00) | 1 (1.00)
1p loss | 65 (31%) | 142 | 0.124 (1.00) | 0.0169 (1.00) | 0.88 (1.00) | 0.692 (1.00) | 4.61e-19 (1.56e-16) | 0.132 (1.00) | 0.00165 (0.525)
3p loss | 4 (2%) | 203 | 0.917 (1.00) | 1.04e-05 (0.00342) | 0.636 (1.00) |  | 0.688 (1.00) | 0.127 (1.00) | 0.369 (1.00)
6p loss | 5 (2%) | 202 | 5.29e-05 (0.0173) | 0.806 (1.00) | 1 (1.00) | 0.861 (1.00) | 0.449 (1.00) | 0.379 (1.00) | 1 (1.00)
11q loss | 4 (2%) | 203 | 0.000569 (0.184) | 0.0656 (1.00) | 0.316 (1.00) |  | 0.214 (1.00) | 0.127 (1.00) | 0.621 (1.00)
19q loss | 73 (35%) | 134 | 0.186 (1.00) | 0.0459 (1.00) | 0.769 (1.00) | 0.825 (1.00) | 2.67e-14 (8.99e-12) | 0.467 (1.00) | 0.0295 (1.00)
22q loss | 14 (7%) | 193 | 3.89e-06 (0.00129) | 0.452 (1.00) | 0.28 (1.00) | 0.187 (1.00) | 0.00293 (0.912) | 0.00373 (1.00) | 0.284 (1.00)
1p gain | 6 (3%) | 201 | 0.00425 (1.00) | 0.171 (1.00) | 0.0864 (1.00) | 0.14 (1.00) | 0.0282 (1.00) | 0.0325 (1.00) | 1 (1.00)
1q gain | 8 (4%) | 199 | 0.252 (1.00) | 0.00496 (1.00) | 0.293 (1.00) | 0.572 (1.00) | 0.432 (1.00) | 0.0733 (1.00) | 0.721 (1.00)
6p gain | 3 (1%) | 204 | 0.506 (1.00) | 0.761 (1.00) | 0.578 (1.00) |  | 0.0449 (1.00) | 1 (1.00) | 0.246 (1.00)
7p gain | 36 (17%) | 171 | 0.00841 (1.00) | 0.0264 (1.00) | 0.044 (1.00) | 0.958 (1.00) | 0.0204 (1.00) | 0.0262 (1.00) | 0.36 (1.00)
7q gain | 49 (24%) | 158 | 0.0113 (1.00) | 0.00174 (0.55) | 0.137 (1.00) | 0.702 (1.00) | 0.0623 (1.00) | 0.325 (1.00) | 0.514 (1.00)
8p gain | 14 (7%) | 193 | 0.731 (1.00) | 0.618 (1.00) | 0.403 (1.00) | 0.987 (1.00) | 0.159 (1.00) | 1 (1.00) | 0.165 (1.00)
8q gain | 17 (8%) | 190 | 0.941 (1.00) | 0.271 (1.00) | 0.613 (1.00) | 0.348 (1.00) | 0.0511 (1.00) | 1 (1.00) | 0.311 (1.00)
9p gain | 4 (2%) | 203 | 0.135 (1.00) | 0.00595 (1.00) | 0.316 (1.00) |  | 0.817 (1.00) | 0.627 (1.00) | 1 (1.00)
9q gain | 4 (2%) | 203 | 0.043 (1.00) | 0.0912 (1.00) | 0.316 (1.00) | 0.14 (1.00) | 0.214 (1.00) | 0.127 (1.00) | 0.621 (1.00)
10p gain | 21 (10%) | 186 | 0.502 (1.00) | 0.00632 (1.00) | 0.0669 (1.00) | 0.101 (1.00) | 0.101 (1.00) | 0.822 (1.00) | 0.0635 (1.00)
11p gain | 9 (4%) | 198 | 0.511 (1.00) | 0.277 (1.00) | 1 (1.00) | 0.722 (1.00) | 0.469 (1.00) | 0.514 (1.00) | 1 (1.00)
11q gain | 13 (6%) | 194 | 0.69 (1.00) | 0.185 (1.00) | 0.564 (1.00) | 0.605 (1.00) | 0.875 (1.00) | 0.576 (1.00) | 0.568 (1.00)
12p gain | 10 (5%) | 197 | 0.465 (1.00) | 0.00184 (0.581) | 0.0458 (1.00) |  | 0.758 (1.00) | 0.0826 (1.00) | 1 (1.00)
12q gain | 4 (2%) | 203 | 0.364 (1.00) | 0.000869 (0.278) | 0.136 (1.00) |  | 1 (1.00) | 0.0934 (1.00) | 1 (1.00)
18p gain | 4 (2%) | 203 | 0.493 (1.00) | 0.75 (1.00) | 0.316 (1.00) |  | 0.214 (1.00) | 0.627 (1.00) | 0.369 (1.00)
19p gain | 10 (5%) | 197 | 0.171 (1.00) | 0.00203 (0.639) | 1 (1.00) | 0.0572 (1.00) | 0.293 (1.00) | 0.114 (1.00) | 0.332 (1.00)
21q gain | 3 (1%) | 204 | 0.533 (1.00) | 0.994 (1.00) | 1 (1.00) |  | 0.26 (1.00) | 0.593 (1.00) | 1 (1.00)
1q loss | 9 (4%) | 198 | 0.489 (1.00) | 0.047 (1.00) | 1 (1.00) | 0.111 (1.00) | 0.00112 (0.356) | 0.735 (1.00) | 0.748 (1.00)
2p loss | 4 (2%) | 203 | 0.054 (1.00) | 0.675 (1.00) | 0.636 (1.00) |  | 0.688 (1.00) | 0.627 (1.00) | 0.621 (1.00)
2q loss | 3 (1%) | 204 | 0.539 (1.00) | 0.189 (1.00) | 0.261 (1.00) |  | 0.108 (1.00) | 1 (1.00) | 0.621 (1.00)
3q loss | 9 (4%) | 198 | 0.554 (1.00) | 0.857 (1.00) | 0.735 (1.00) | 0.217 (1.00) | 0.387 (1.00) | 0.514 (1.00) | 1 (1.00)
4p loss | 15 (7%) | 192 | 0.143 (1.00) | 0.252 (1.00) | 0.279 (1.00) | 0.563 (1.00) | 0.0664 (1.00) | 0.79 (1.00) | 0.436 (1.00)
4q loss | 24 (12%) | 183 | 0.116 (1.00) | 0.88 (1.00) | 0.663 (1.00) | 0.395 (1.00) | 0.314 (1.00) | 0.514 (1.00) | 0.394 (1.00)
5p loss | 11 (5%) | 196 | 0.309 (1.00) | 0.814 (1.00) | 0.358 (1.00) | 0.212 (1.00) | 0.00272 (0.852) | 0.757 (1.00) | 0.538 (1.00)
5q loss | 9 (4%) | 198 | 0.0292 (1.00) | 0.364 (1.00) | 1 (1.00) | 0.14 (1.00) | 0.224 (1.00) | 0.514 (1.00) | 0.17 (1.00)
6q loss | 19 (9%) | 188 | 0.00251 (0.787) | 0.134 (1.00) | 0.467 (1.00) | 0.194 (1.00) | 0.025 (1.00) | 0.14 (1.00) | 0.0029 (0.905)
9p loss | 36 (17%) | 171 | 0.00408 (1.00) | 0.126 (1.00) | 0.855 (1.00) | 0.595 (1.00) | 0.0808 (1.00) | 0.192 (1.00) | 0.00544 (1.00)
9q loss | 6 (3%) | 201 | 0.851 (1.00) | 0.116 (1.00) | 0.406 (1.00) | 0.615 (1.00) | 0.579 (1.00) | 1 (1.00) | 0.445 (1.00)
11p loss | 18 (9%) | 189 | 0.131 (1.00) | 0.111 (1.00) | 0.621 (1.00) | 0.797 (1.00) | 0.00472 (1.00) | 0.14 (1.00) | 0.217 (1.00)
12q loss | 8 (4%) | 199 | 0.464 (1.00) | 0.894 (1.00) | 0.727 (1.00) | 0.859 (1.00) | 0.214 (1.00) | 0.473 (1.00) | 0.721 (1.00)
13q loss | 27 (13%) | 180 | 0.163 (1.00) | 0.397 (1.00) | 1 (1.00) | 0.839 (1.00) | 1 (1.00) | 1 (1.00) | 0.215 (1.00)
14q loss | 22 (11%) | 185 | 0.000835 (0.268) | 0.0113 (1.00) | 0.0432 (1.00) | 0.5 (1.00) | 0.0839 (1.00) | 0.111 (1.00) | 0.377 (1.00)
15q loss | 12 (6%) | 195 | 0.252 (1.00) | 0.734 (1.00) | 0.561 (1.00) | 0.816 (1.00) | 0.0384 (1.00) | 0.388 (1.00) | 0.0822 (1.00)
16q loss | 6 (3%) | 201 | 0.962 (1.00) | 0.178 (1.00) | 1 (1.00) |  | 0.879 (1.00) | 0.69 (1.00) | 0.212 (1.00)
18p loss | 14 (7%) | 193 | 0.69 (1.00) | 0.409 (1.00) | 1 (1.00) | 0.5 (1.00) | 0.606 (1.00) | 1 (1.00) | 0.783 (1.00)
18q loss | 15 (7%) | 192 | 0.813 (1.00) | 0.367 (1.00) | 0.428 (1.00) | 0.731 (1.00) | 0.182 (1.00) | 0.597 (1.00) | 0.593 (1.00)
19p loss | 9 (4%) | 198 | 0.484 (1.00) | 0.247 (1.00) | 0.503 (1.00) | 0.44 (1.00) | 0.198 (1.00) | 0.185 (1.00) | 0.498 (1.00)
21q loss | 7 (3%) | 200 | 0.431 (1.00) | 0.746 (1.00) | 1 (1.00) | 0.26 (1.00) | 0.0666 (1.00) | 1 (1.00) | 1 (1.00)
Xq loss | 5 (2%) | 202 | 0.423 (1.00) | 0.794 (1.00) | 0.654 (1.00) |  | 0.578 (1.00) | 0.333 (1.00) | 0.369 (1.00)

'19q gain mutation analysis' versus 'Time to Death'

P value = 0.000661 (logrank test), Q value = 0.21

Table S1. Gene #17: '19q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 206 | 51 | 0.0 - 211.2 (13.4)
19Q GAIN MUTATED | 8 | 4 | 0.5 - 26.3 (14.5)
19Q GAIN WILD-TYPE | 198 | 47 | 0.0 - 211.2 (13.4)

Figure S1. Get High-res Image Gene #17: '19q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

'20p gain mutation analysis' versus 'Time to Death'

P value = 0.000116 (logrank test), Q value = 0.038

Table S2. Gene #18: '20p gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 206 | 51 | 0.0 - 211.2 (13.4)
20P GAIN MUTATED | 17 | 7 | 0.5 - 41.1 (15.3)
20P GAIN WILD-TYPE | 189 | 44 | 0.0 - 211.2 (13.4)

Figure S2. Get High-res Image Gene #18: '20p gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

'20q gain mutation analysis' versus 'Time to Death'

P value = 0.000335 (logrank test), Q value = 0.11

Table S3. Gene #19: '20q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 206 | 51 | 0.0 - 211.2 (13.4)
20Q GAIN MUTATED | 15 | 6 | 0.5 - 41.1 (12.4)
20Q GAIN WILD-TYPE | 191 | 45 | 0.0 - 211.2 (13.4)

Figure S3. Get High-res Image Gene #19: '20q gain mutation analysis' versus Clinical Feature #1: 'Time to Death'

'1p loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 4.61e-19 (Fisher's exact test), Q value = 1.6e-16

Table S4. Gene #21: '1p loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 63 | 54 | 89
1P LOSS MUTATED | 2 | 6 | 57
1P LOSS WILD-TYPE | 61 | 48 | 32

Figure S4. Get High-res Image Gene #21: '1p loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'3p loss mutation analysis' versus 'AGE'

P value = 1.04e-05 (t-test), Q value = 0.0034

Table S5. Gene #25: '3p loss mutation analysis' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 207 | 43.1 (13.4)
3P LOSS MUTATED | 4 | 31.0 (2.2)
3P LOSS WILD-TYPE | 203 | 43.3 (13.4)

Figure S5. Get High-res Image Gene #25: '3p loss mutation analysis' versus Clinical Feature #2: 'AGE'

'6p loss mutation analysis' versus 'Time to Death'

P value = 5.29e-05 (logrank test), Q value = 0.017

Table S6. Gene #31: '6p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 206 | 51 | 0.0 - 211.2 (13.4)
6P LOSS MUTATED | 5 | 2 | 3.0 - 13.4 (6.4)
6P LOSS WILD-TYPE | 201 | 49 | 0.0 - 211.2 (14.4)

Figure S6. Get High-res Image Gene #31: '6p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'10p loss mutation analysis' versus 'Time to Death'

P value = 8.93e-11 (logrank test), Q value = 3e-08

Table S7. Gene #35: '10p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 206 | 51 | 0.0 - 211.2 (13.4)
10P LOSS MUTATED | 30 | 17 | 0.1 - 134.3 (8.6)
10P LOSS WILD-TYPE | 176 | 34 | 0.0 - 211.2 (14.6)

Figure S7. Get High-res Image Gene #35: '10p loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'10p loss mutation analysis' versus 'AGE'

P value = 6.05e-08 (t-test), Q value = 2e-05

Table S8. Gene #35: '10p loss mutation analysis' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 207 | 43.1 (13.4)
10P LOSS MUTATED | 30 | 54.9 (10.4)
10P LOSS WILD-TYPE | 177 | 41.1 (12.9)

Figure S8. Get High-res Image Gene #35: '10p loss mutation analysis' versus Clinical Feature #2: 'AGE'

'10p loss mutation analysis' versus 'HISTOLOGICCLASSIFICATION'

P value = 1.48e-05 (Fisher's exact test), Q value = 0.0049

Table S9. Gene #35: '10p loss mutation analysis' versus Clinical Feature #6: 'HISTOLOGICCLASSIFICATION'

nPatients | GRADE II | GRADE III
--- | --- | ---
ALL | 94 | 112
10P LOSS MUTATED | 3 | 27
10P LOSS WILD-TYPE | 91 | 85

Figure S9. Get High-res Image Gene #35: '10p loss mutation analysis' versus Clinical Feature #6: 'HISTOLOGICCLASSIFICATION'

'10q loss mutation analysis' versus 'Time to Death'

P value = 1.88e-10 (logrank test), Q value = 6.3e-08

Table S10. Gene #36: '10q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 206 | 51 | 0.0 - 211.2 (13.4)
10Q LOSS MUTATED | 31 | 17 | 0.1 - 134.3 (8.8)
10Q LOSS WILD-TYPE | 175 | 34 | 0.0 - 211.2 (14.7)

Figure S10. Get High-res Image Gene #36: '10q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'10q loss mutation analysis' versus 'AGE'

P value = 3.06e-08 (t-test), Q value = 1e-05

Table S11. Gene #36: '10q loss mutation analysis' versus Clinical Feature #2: 'AGE'

| nPatients | Mean (Std.Dev)
--- | --- | ---
ALL | 207 | 43.1 (13.4)
10Q LOSS MUTATED | 31 | 54.8 (10.3)
10Q LOSS WILD-TYPE | 176 | 41.0 (12.9)

Figure S11. Get High-res Image Gene #36: '10q loss mutation analysis' versus Clinical Feature #2: 'AGE'

'10q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 0.000389 (Fisher's exact test), Q value = 0.13

Table S12. Gene #36: '10q loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 63 | 54 | 89
10Q LOSS MUTATED | 19 | 6 | 6
10Q LOSS WILD-TYPE | 44 | 48 | 83

Figure S12. Get High-res Image Gene #36: '10q loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'10q loss mutation analysis' versus 'HISTOLOGICCLASSIFICATION'

P value = 7.47e-06 (Fisher's exact test), Q value = 0.0025

Table S13. Gene #36: '10q loss mutation analysis' versus Clinical Feature #6: 'HISTOLOGICCLASSIFICATION'

nPatients | GRADE II | GRADE III
--- | --- | ---
ALL | 94 | 112
10Q LOSS MUTATED | 3 | 28
10Q LOSS WILD-TYPE | 91 | 84

Figure S13. Get High-res Image Gene #36: '10q loss mutation analysis' versus Clinical Feature #6: 'HISTOLOGICCLASSIFICATION'

'11q loss mutation analysis' versus 'Time to Death'

P value = 0.000569 (logrank test), Q value = 0.18

Table S14. Gene #38: '11q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 206 | 51 | 0.0 - 211.2 (13.4)
11Q LOSS MUTATED | 4 | 3 | 6.0 - 41.1 (13.2)
11Q LOSS WILD-TYPE | 202 | 48 | 0.0 - 211.2 (13.4)

Figure S14. Get High-res Image Gene #38: '11q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

'19q loss mutation analysis' versus 'HISTOLOGICAL.TYPE'

P value = 2.67e-14 (Fisher's exact test), Q value = 9e-12

Table S15. Gene #47: '19q loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

nPatients | ASTROCYTOMA | OLIGOASTROCYTOMA | OLIGODENDROGLIOMA
--- | --- | --- | ---
ALL | 63 | 54 | 89
19Q LOSS MUTATED | 8 | 7 | 58
19Q LOSS WILD-TYPE | 55 | 47 | 31

Figure S15. Get High-res Image Gene #47: '19q loss mutation analysis' versus Clinical Feature #5: 'HISTOLOGICAL.TYPE'

'22q loss mutation analysis' versus 'Time to Death'

P value = 3.89e-06 (logrank test), Q value = 0.0013

Table S16. Gene #49: '22q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

| nPatients | nDeath | Duration Range (Median), Month
--- | --- | --- | ---
ALL | 206 | 51 | 0.0 - 211.2 (13.4)
22Q LOSS MUTATED | 14 | 7 | 0.1 - 46.6 (11.9)
22Q LOSS WILD-TYPE | 192 | 44 | 0.0 - 211.2 (13.9)

Figure S16. Get High-res Image Gene #49: '22q loss mutation analysis' versus Clinical Feature #1: 'Time to Death'

Methods & Data
Input

- Mutation data file = broad_values_by_arm.mutsig.cluster.txt

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

- Number of patients = 207

- Number of significantly arm-level cnvs = 50

- Number of selected clinical features = 7

- Exclude genes 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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

- 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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