Correlation between copy number variations of arm-level result and molecular subtypes
Kidney Renal Papillary Cell Carcinoma (Primary solid tumor)
23 May 2013 | analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C1RB72NB
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 molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1RB72NB
Overview
Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and subtypes.

Summary

Testing the association between copy number variation 59 arm-level results and 8 molecular subtypes across 127 patients, 43 significant findings detected with Q value < 0.25.

- 1q gain cnv correlated to 'METHLYATION_CNMF'.

- 3p gain cnv correlated to 'CN_CNMF', 'MRNASEQ_CNMF', 'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

- 3q gain cnv correlated to 'CN_CNMF', 'MRNASEQ_CNMF', 'MRNASEQ_CHIERARCHICAL', 'MIRSEQ_CHIERARCHICAL', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

- 5p gain cnv correlated to 'CN_CNMF'.

- 5q gain cnv correlated to 'CN_CNMF'.

- 7p gain cnv correlated to 'CN_CNMF', 'METHLYATION_CNMF', 'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

- 7q gain cnv correlated to 'CN_CNMF', 'METHLYATION_CNMF', 'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

- 12p gain cnv correlated to 'CN_CNMF'.

- 12q gain cnv correlated to 'CN_CNMF'.

- 16p gain cnv correlated to 'CN_CNMF', 'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

- 16q gain cnv correlated to 'CN_CNMF', 'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

- 17p gain cnv correlated to 'CN_CNMF', 'METHLYATION_CNMF', 'MRNASEQ_CNMF', 'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

- 17q gain cnv correlated to 'CN_CNMF'.

- 4p loss cnv correlated to 'CN_CNMF'.

- 5q loss cnv correlated to 'CN_CNMF'.

- 6p loss cnv correlated to 'CN_CNMF'.

- 9p loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

- 9q loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

- 14q loss cnv correlated to 'CN_CNMF'.

- 22q loss cnv correlated to 'CN_CNMF'.

Results
Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 59 arm-level results and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 43 significant findings detected.

|  | Molecular subtypes | CN CNMF | METHLYATION CNMF | MRNASEQ CNMF | MRNASEQ CHIERARCHICAL | MIRSEQ CNMF | MIRSEQ CHIERARCHICAL | MIRSEQ MATURE CNMF | MIRSEQ MATURE CHIERARCHICAL
| nCNV (%) | nWild-Type | Chi-square 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 | Fisher's exact test
3q gain | 0 (0%) | 94 | 1.95e-12 (8.49e-10) | 0.00739 (1.00) | 3.65e-05 (0.015) | 6.94e-06 (0.00291) | 0.000679 (0.267) | 6.07e-08 (2.61e-05) | 0.197 (1.00) | 0.000241 (0.0969)
17p gain | 0 (0%) | 61 | 9.52e-08 (4.09e-05) | 1.3e-06 (0.000555) | 3.49e-05 (0.0144) | 2.21e-06 (0.000937) | 0.0228 (1.00) | 7.75e-05 (0.0316) | 0.0197 (1.00) | 0.012 (1.00)
3p gain | 0 (0%) | 98 | 7.99e-15 (3.49e-12) | 0.0132 (1.00) | 0.000268 (0.108) | 3.64e-07 (0.000156) | 0.00686 (1.00) | 4.64e-09 (2.01e-06) | 0.232 (1.00) | 0.00425 (1.00)
7p gain | 0 (0%) | 60 | 2.69e-07 (0.000115) | 2.62e-06 (0.00111) | 5.65e-05 (0.0231) | 2.01e-05 (0.00834) | 0.0834 (1.00) | 0.00341 (1.00) | 0.156 (1.00) | 0.00708 (1.00)
7q gain | 0 (0%) | 59 | 5.79e-08 (2.5e-05) | 9.37e-06 (0.00392) | 0.000181 (0.0735) | 3.74e-05 (0.0153) | 0.0474 (1.00) | 0.0042 (1.00) | 0.0832 (1.00) | 0.00741 (1.00)
16p gain | 0 (0%) | 67 | 4.19e-06 (0.00177) | 0.221 (1.00) | 0.00874 (1.00) | 0.000182 (0.0738) | 0.0074 (1.00) | 1.89e-05 (0.00787) | 0.0997 (1.00) | 0.00401 (1.00)
16q gain | 0 (0%) | 69 | 9.17e-06 (0.00384) | 0.0521 (1.00) | 0.00419 (1.00) | 1.46e-05 (0.00609) | 0.00489 (1.00) | 1.8e-06 (0.000764) | 0.134 (1.00) | 0.00254 (0.968)
9p loss | 0 (0%) | 112 | 0.000169 (0.069) | 0.000318 (0.127) | 0.00782 (1.00) | 0.0678 (1.00) | 0.114 (1.00) | 0.314 (1.00) | 1 (1.00) | 0.0241 (1.00)
9q loss | 0 (0%) | 110 | 0.000445 (0.177) | 3.17e-05 (0.0131) | 0.0256 (1.00) | 0.131 (1.00) | 0.0751 (1.00) | 0.0814 (1.00) | 1 (1.00) | 0.00493 (1.00)
1q gain | 0 (0%) | 118 | 0.00553 (1.00) | 0.000353 (0.141) | 0.00232 (0.89) | 0.00827 (1.00) | 0.446 (1.00) | 0.112 (1.00) | 0.812 (1.00) | 0.128 (1.00)
5p gain | 0 (0%) | 113 | 1.96e-08 (8.45e-06) | 0.0521 (1.00) | 0.156 (1.00) | 0.8 (1.00) | 0.835 (1.00) | 0.411 (1.00) | 0.437 (1.00) | 0.536 (1.00)
5q gain | 0 (0%) | 113 | 2.18e-10 (9.48e-08) | 0.0521 (1.00) | 0.579 (1.00) | 0.8 (1.00) | 0.851 (1.00) | 0.411 (1.00) | 0.437 (1.00) | 0.536 (1.00)
12p gain | 0 (0%) | 87 | 0.00055 (0.218) | 0.833 (1.00) | 0.161 (1.00) | 0.0648 (1.00) | 0.0938 (1.00) | 0.103 (1.00) | 0.465 (1.00) | 0.11 (1.00)
12q gain | 0 (0%) | 87 | 0.00055 (0.218) | 0.833 (1.00) | 0.161 (1.00) | 0.0648 (1.00) | 0.0938 (1.00) | 0.103 (1.00) | 0.465 (1.00) | 0.11 (1.00)
17q gain | 0 (0%) | 50 | 5.4e-06 (0.00227) | 0.00104 (0.404) | 0.0144 (1.00) | 0.000926 (0.362) | 0.0536 (1.00) | 0.0135 (1.00) | 0.0442 (1.00) | 0.05 (1.00)
4p loss | 0 (0%) | 116 | 0.000247 (0.0993) | 0.00449 (1.00) | 0.0129 (1.00) | 0.18 (1.00) | 0.181 (1.00) | 0.657 (1.00) | 0.346 (1.00) | 0.0408 (1.00)
5q loss | 0 (0%) | 121 | 1.96e-05 (0.00815) | 0.23 (1.00) | 0.41 (1.00) | 0.211 (1.00) | 0.547 (1.00) | 0.665 (1.00) | 0.239 (1.00) | 0.615 (1.00)
6p loss | 0 (0%) | 118 | 0.00043 (0.171) | 0.443 (1.00) | 0.468 (1.00) | 1 (1.00) | 0.214 (1.00) | 0.546 (1.00) | 0.812 (1.00) | 1 (1.00)
14q loss | 0 (0%) | 104 | 1.54e-11 (6.7e-09) | 0.267 (1.00) | 0.135 (1.00) | 0.0977 (1.00) | 0.757 (1.00) | 0.934 (1.00) | 1 (1.00) | 0.458 (1.00)
22q loss | 0 (0%) | 103 | 0.000233 (0.0942) | 0.00271 (1.00) | 0.673 (1.00) | 0.0477 (1.00) | 0.0178 (1.00) | 0.0721 (1.00) | 0.0885 (1.00) | 0.0331 (1.00)
2p gain | 0 (0%) | 114 | 0.0607 (1.00) | 0.132 (1.00) | 0.585 (1.00) | 0.338 (1.00) | 0.788 (1.00) | 0.227 (1.00) | 0.0415 (1.00) | 0.155 (1.00)
2q gain | 0 (0%) | 112 | 0.0309 (1.00) | 0.354 (1.00) | 0.329 (1.00) | 0.205 (1.00) | 0.877 (1.00) | 0.441 (1.00) | 0.27 (1.00) | 0.291 (1.00)
4p gain | 0 (0%) | 123 | 0.382 (1.00) |  | 0.457 (1.00) | 1 (1.00) | 0.754 (1.00) | 0.874 (1.00) |  |
4q gain | 0 (0%) | 124 | 0.572 (1.00) |  | 0.645 (1.00) | 0.602 (1.00) | 0.759 (1.00) | 0.604 (1.00) |  |
6p gain | 0 (0%) | 123 | 0.503 (1.00) | 0.44 (1.00) | 0.114 (1.00) | 0.677 (1.00) | 0.282 (1.00) | 0.514 (1.00) | 0.279 (1.00) | 1 (1.00)
6q gain | 0 (0%) | 124 | 0.213 (1.00) |  | 0.41 (1.00) | 1 (1.00) | 0.429 (1.00) | 0.518 (1.00) |  |
8p gain | 0 (0%) | 118 | 0.318 (1.00) | 0.087 (1.00) | 0.732 (1.00) | 0.232 (1.00) | 0.502 (1.00) | 0.389 (1.00) | 0.424 (1.00) | 0.128 (1.00)
8q gain | 0 (0%) | 116 | 0.00446 (1.00) | 0.0131 (1.00) | 0.243 (1.00) | 0.0683 (1.00) | 0.0899 (1.00) | 0.396 (1.00) | 0.246 (1.00) | 0.0765 (1.00)
10p gain | 0 (0%) | 123 | 0.184 (1.00) |  | 0.645 (1.00) | 0.602 (1.00) | 0.138 (1.00) | 0.874 (1.00) |  |
10q gain | 0 (0%) | 124 | 0.393 (1.00) |  |  |  | 0.317 (1.00) | 0.442 (1.00) |  |
13q gain | 0 (0%) | 113 | 0.00662 (1.00) | 0.179 (1.00) | 0.324 (1.00) | 0.0445 (1.00) | 0.638 (1.00) | 0.307 (1.00) | 0.928 (1.00) | 0.414 (1.00)
18p gain | 0 (0%) | 121 | 0.16 (1.00) | 0.329 (1.00) | 0.863 (1.00) | 1 (1.00) | 0.885 (1.00) | 0.804 (1.00) | 0.188 (1.00) | 0.761 (1.00)
18q gain | 0 (0%) | 123 | 0.0227 (1.00) | 0.329 (1.00) | 0.77 (1.00) | 0.432 (1.00) | 0.827 (1.00) | 0.32 (1.00) | 0.188 (1.00) | 0.761 (1.00)
20p gain | 0 (0%) | 88 | 0.0185 (1.00) | 0.0743 (1.00) | 0.000722 (0.284) | 0.0152 (1.00) | 0.256 (1.00) | 0.267 (1.00) | 0.0791 (1.00) | 0.189 (1.00)
20q gain | 0 (0%) | 87 | 0.0107 (1.00) | 0.142 (1.00) | 0.000813 (0.319) | 0.0381 (1.00) | 0.166 (1.00) | 0.524 (1.00) | 0.0213 (1.00) | 0.259 (1.00)
21q gain | 0 (0%) | 122 | 0.637 (1.00) | 0.468 (1.00) |  |  | 0.0267 (1.00) | 0.193 (1.00) | 0.00525 (1.00) | 1 (1.00)
Xq gain | 0 (0%) | 122 | 0.121 (1.00) | 0.137 (1.00) | 0.457 (1.00) | 1 (1.00) | 0.278 (1.00) | 0.752 (1.00) | 0.827 (1.00) | 0.204 (1.00)
1p loss | 0 (0%) | 113 | 0.0256 (1.00) | 0.328 (1.00) | 0.611 (1.00) | 0.589 (1.00) | 0.417 (1.00) | 0.283 (1.00) | 0.162 (1.00) | 0.472 (1.00)
1q loss | 0 (0%) | 120 | 0.0171 (1.00) | 0.193 (1.00) | 0.103 (1.00) | 0.432 (1.00) | 0.111 (1.00) | 0.00803 (1.00) | 0.377 (1.00) | 0.123 (1.00)
3p loss | 0 (0%) | 119 | 0.00138 (0.536) | 0.00142 (0.549) | 0.058 (1.00) | 0.0149 (1.00) | 0.0923 (1.00) | 0.073 (1.00) | 0.426 (1.00) | 0.00239 (0.914)
3q loss | 0 (0%) | 124 | 0.248 (1.00) | 0.0335 (1.00) | 0.0288 (1.00) | 0.0762 (1.00) | 0.106 (1.00) | 0.518 (1.00) | 0.778 (1.00) | 0.0539 (1.00)
4q loss | 0 (0%) | 115 | 0.00104 (0.404) | 0.00153 (0.59) | 0.0999 (1.00) | 0.0683 (1.00) | 0.394 (1.00) | 0.802 (1.00) | 0.671 (1.00) | 0.163 (1.00)
5p loss | 0 (0%) | 122 | 0.00932 (1.00) | 0.246 (1.00) | 0.114 (1.00) | 0.0626 (1.00) | 0.805 (1.00) | 0.831 (1.00) | 0.438 (1.00) | 0.848 (1.00)
6q loss | 0 (0%) | 115 | 0.00107 (0.415) | 0.066 (1.00) | 0.374 (1.00) | 0.558 (1.00) | 0.151 (1.00) | 0.802 (1.00) | 0.618 (1.00) | 0.163 (1.00)
8p loss | 0 (0%) | 124 | 0.846 (1.00) |  |  |  | 1 (1.00) | 0.604 (1.00) |  |
10p loss | 0 (0%) | 120 | 0.0171 (1.00) | 0.056 (1.00) | 0.269 (1.00) | 0.18 (1.00) | 0.273 (1.00) | 0.51 (1.00) | 0.438 (1.00) | 0.222 (1.00)
10q loss | 0 (0%) | 119 | 0.00696 (1.00) | 0.0362 (1.00) | 0.269 (1.00) | 0.0871 (1.00) | 0.0171 (1.00) | 0.134 (1.00) | 0.171 (1.00) | 0.0667 (1.00)
11p loss | 0 (0%) | 118 | 0.167 (1.00) | 0.113 (1.00) | 0.269 (1.00) | 0.145 (1.00) | 0.446 (1.00) | 0.585 (1.00) | 0.899 (1.00) | 0.366 (1.00)
11q loss | 0 (0%) | 116 | 0.00512 (1.00) | 0.00354 (1.00) | 0.296 (1.00) | 0.0563 (1.00) | 0.355 (1.00) | 0.936 (1.00) | 0.671 (1.00) | 0.911 (1.00)
13q loss | 0 (0%) | 115 | 0.019 (1.00) | 0.00153 (0.59) | 0.091 (1.00) | 0.403 (1.00) | 0.016 (1.00) | 0.0706 (1.00) | 0.186 (1.00) | 0.00342 (1.00)
15q loss | 0 (0%) | 116 | 0.00407 (1.00) | 0.119 (1.00) | 0.579 (1.00) | 0.487 (1.00) | 0.727 (1.00) | 0.714 (1.00) | 0.772 (1.00) | 0.667 (1.00)
16q loss | 0 (0%) | 124 | 0.632 (1.00) | 0.139 (1.00) |  |  | 0.871 (1.00) | 0.22 (1.00) | 0.498 (1.00) | 0.283 (1.00)
17p loss | 0 (0%) | 122 | 0.756 (1.00) | 0.0436 (1.00) | 0.0288 (1.00) | 0.0762 (1.00) | 0.301 (1.00) | 0.267 (1.00) | 0.309 (1.00) | 0.116 (1.00)
18p loss | 0 (0%) | 108 | 0.0863 (1.00) | 0.0306 (1.00) | 0.0772 (1.00) | 0.0114 (1.00) | 0.543 (1.00) | 0.426 (1.00) | 0.373 (1.00) | 0.94 (1.00)
18q loss | 0 (0%) | 107 | 0.209 (1.00) | 0.0155 (1.00) | 0.0392 (1.00) | 0.00363 (1.00) | 0.755 (1.00) | 0.349 (1.00) | 0.63 (1.00) | 0.836 (1.00)
19p loss | 0 (0%) | 123 | 0.0513 (1.00) | 1 (1.00) |  |  | 1 (1.00) | 0.32 (1.00) | 0.555 (1.00) | 0.38 (1.00)
19q loss | 0 (0%) | 123 | 0.0513 (1.00) | 1 (1.00) |  |  | 1 (1.00) | 0.697 (1.00) | 0.555 (1.00) | 1 (1.00)
21q loss | 0 (0%) | 112 | 0.504 (1.00) | 0.231 (1.00) | 0.246 (1.00) | 0.728 (1.00) | 0.472 (1.00) | 0.376 (1.00) | 0.863 (1.00) | 0.173 (1.00)
Xq loss | 0 (0%) | 124 | 0.632 (1.00) |  |  |  | 0.665 (1.00) | 0.442 (1.00) |  |

'1q gain' versus 'METHLYATION_CNMF'

P value = 0.000353 (Fisher's exact test), Q value = 0.14

Table S1. Gene #1: '1q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 27 | 53 | 31
1Q GAIN CNV | 1 | 0 | 7
1Q GAIN WILD-TYPE | 26 | 53 | 24

Figure S1. Get High-res Image Gene #1: '1q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'3p gain' versus 'CN_CNMF'

P value = 7.99e-15 (Chi-square test), Q value = 3.5e-12

Table S2. Gene #4: '3p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
3P GAIN CNV | 1 | 3 | 1 | 5 | 19
3P GAIN WILD-TYPE | 23 | 41 | 12 | 21 | 1

Figure S2. Get High-res Image Gene #4: '3p gain' versus Molecular Subtype #1: 'CN_CNMF'

'3p gain' versus 'MRNASEQ_CNMF'

P value = 0.000268 (Fisher's exact test), Q value = 0.11

Table S3. Gene #4: '3p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 27 | 24 | 25
3P GAIN CNV | 12 | 0 | 7
3P GAIN WILD-TYPE | 15 | 24 | 18

Figure S3. Get High-res Image Gene #4: '3p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'3p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3.64e-07 (Fisher's exact test), Q value = 0.00016

Table S4. Gene #4: '3p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 18 | 37 | 21
3P GAIN CNV | 0 | 19 | 0
3P GAIN WILD-TYPE | 18 | 18 | 21

Figure S4. Get High-res Image Gene #4: '3p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'3p gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 4.64e-09 (Fisher's exact test), Q value = 2e-06

Table S5. Gene #4: '3p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 48 | 33 | 11 | 35
3P GAIN CNV | 4 | 2 | 10 | 13
3P GAIN WILD-TYPE | 44 | 31 | 1 | 22

Figure S5. Get High-res Image Gene #4: '3p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'3q gain' versus 'CN_CNMF'

P value = 1.95e-12 (Chi-square test), Q value = 8.5e-10

Table S6. Gene #5: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
3Q GAIN CNV | 2 | 4 | 2 | 6 | 19
3Q GAIN WILD-TYPE | 22 | 40 | 11 | 20 | 1

Figure S6. Get High-res Image Gene #5: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

'3q gain' versus 'MRNASEQ_CNMF'

P value = 3.65e-05 (Fisher's exact test), Q value = 0.015

Table S7. Gene #5: '3q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 27 | 24 | 25
3Q GAIN CNV | 14 | 0 | 8
3Q GAIN WILD-TYPE | 13 | 24 | 17

Figure S7. Get High-res Image Gene #5: '3q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'3q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 6.94e-06 (Fisher's exact test), Q value = 0.0029

Table S8. Gene #5: '3q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 18 | 37 | 21
3Q GAIN CNV | 1 | 20 | 1
3Q GAIN WILD-TYPE | 17 | 17 | 20

Figure S8. Get High-res Image Gene #5: '3q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'3q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 6.07e-08 (Fisher's exact test), Q value = 2.6e-05

Table S9. Gene #5: '3q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 48 | 33 | 11 | 35
3Q GAIN CNV | 4 | 5 | 10 | 14
3Q GAIN WILD-TYPE | 44 | 28 | 1 | 21

Figure S9. Get High-res Image Gene #5: '3q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'3q gain' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.000241 (Fisher's exact test), Q value = 0.097

Table S10. Gene #5: '3q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 47 | 16 | 48
3Q GAIN CNV | 20 | 0 | 7
3Q GAIN WILD-TYPE | 27 | 16 | 41

Figure S10. Get High-res Image Gene #5: '3q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'5p gain' versus 'CN_CNMF'

P value = 1.96e-08 (Chi-square test), Q value = 8.4e-06

Table S11. Gene #8: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
5P GAIN CNV | 1 | 0 | 0 | 12 | 1
5P GAIN WILD-TYPE | 23 | 44 | 13 | 14 | 19

Figure S11. Get High-res Image Gene #8: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

'5q gain' versus 'CN_CNMF'

P value = 2.18e-10 (Chi-square test), Q value = 9.5e-08

Table S12. Gene #9: '5q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
5Q GAIN CNV | 0 | 0 | 0 | 13 | 1
5Q GAIN WILD-TYPE | 24 | 44 | 13 | 13 | 19

Figure S12. Get High-res Image Gene #9: '5q gain' versus Molecular Subtype #1: 'CN_CNMF'

'7p gain' versus 'CN_CNMF'

P value = 2.69e-07 (Chi-square test), Q value = 0.00012

Table S13. Gene #12: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
7P GAIN CNV | 5 | 22 | 13 | 9 | 18
7P GAIN WILD-TYPE | 19 | 22 | 0 | 17 | 2

Figure S13. Get High-res Image Gene #12: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

'7p gain' versus 'METHLYATION_CNMF'

P value = 2.62e-06 (Fisher's exact test), Q value = 0.0011

Table S14. Gene #12: '7p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 27 | 53 | 31
7P GAIN CNV | 10 | 40 | 7
7P GAIN WILD-TYPE | 17 | 13 | 24

Figure S14. Get High-res Image Gene #12: '7p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'7p gain' versus 'MRNASEQ_CNMF'

P value = 5.65e-05 (Fisher's exact test), Q value = 0.023

Table S15. Gene #12: '7p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 27 | 24 | 25
7P GAIN CNV | 22 | 5 | 12
7P GAIN WILD-TYPE | 5 | 19 | 13

Figure S15. Get High-res Image Gene #12: '7p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'7p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.01e-05 (Fisher's exact test), Q value = 0.0083

Table S16. Gene #12: '7p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 18 | 37 | 21
7P GAIN CNV | 5 | 29 | 5
7P GAIN WILD-TYPE | 13 | 8 | 16

Figure S16. Get High-res Image Gene #12: '7p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'7q gain' versus 'CN_CNMF'

P value = 5.79e-08 (Chi-square test), Q value = 2.5e-05

Table S17. Gene #13: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
7Q GAIN CNV | 5 | 22 | 13 | 9 | 19
7Q GAIN WILD-TYPE | 19 | 22 | 0 | 17 | 1

Figure S17. Get High-res Image Gene #13: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

'7q gain' versus 'METHLYATION_CNMF'

P value = 9.37e-06 (Fisher's exact test), Q value = 0.0039

Table S18. Gene #13: '7q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 27 | 53 | 31
7Q GAIN CNV | 10 | 40 | 8
7Q GAIN WILD-TYPE | 17 | 13 | 23

Figure S18. Get High-res Image Gene #13: '7q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'7q gain' versus 'MRNASEQ_CNMF'

P value = 0.000181 (Fisher's exact test), Q value = 0.073

Table S19. Gene #13: '7q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 27 | 24 | 25
7Q GAIN CNV | 22 | 6 | 12
7Q GAIN WILD-TYPE | 5 | 18 | 13

Figure S19. Get High-res Image Gene #13: '7q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'7q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3.74e-05 (Fisher's exact test), Q value = 0.015

Table S20. Gene #13: '7q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 18 | 37 | 21
7Q GAIN CNV | 6 | 29 | 5
7Q GAIN WILD-TYPE | 12 | 8 | 16

Figure S20. Get High-res Image Gene #13: '7q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'12p gain' versus 'CN_CNMF'

P value = 0.00055 (Chi-square test), Q value = 0.22

Table S21. Gene #18: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
12P GAIN CNV | 7 | 6 | 10 | 9 | 8
12P GAIN WILD-TYPE | 17 | 38 | 3 | 17 | 12

Figure S21. Get High-res Image Gene #18: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

'12q gain' versus 'CN_CNMF'

P value = 0.00055 (Chi-square test), Q value = 0.22

Table S22. Gene #19: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
12Q GAIN CNV | 7 | 6 | 10 | 9 | 8
12Q GAIN WILD-TYPE | 17 | 38 | 3 | 17 | 12

Figure S22. Get High-res Image Gene #19: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

'16p gain' versus 'CN_CNMF'

P value = 4.19e-06 (Chi-square test), Q value = 0.0018

Table S23. Gene #21: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
16P GAIN CNV | 6 | 16 | 3 | 16 | 19
16P GAIN WILD-TYPE | 18 | 28 | 10 | 10 | 1

Figure S23. Get High-res Image Gene #21: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

'16p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000182 (Fisher's exact test), Q value = 0.074

Table S24. Gene #21: '16p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 18 | 37 | 21
16P GAIN CNV | 2 | 24 | 6
16P GAIN WILD-TYPE | 16 | 13 | 15

Figure S24. Get High-res Image Gene #21: '16p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'16p gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1.89e-05 (Fisher's exact test), Q value = 0.0079

Table S25. Gene #21: '16p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 48 | 33 | 11 | 35
16P GAIN CNV | 13 | 13 | 10 | 24
16P GAIN WILD-TYPE | 35 | 20 | 1 | 11

Figure S25. Get High-res Image Gene #21: '16p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'16q gain' versus 'CN_CNMF'

P value = 9.17e-06 (Chi-square test), Q value = 0.0038

Table S26. Gene #22: '16q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
16Q GAIN CNV | 6 | 16 | 3 | 14 | 19
16Q GAIN WILD-TYPE | 18 | 28 | 10 | 12 | 1

Figure S26. Get High-res Image Gene #22: '16q gain' versus Molecular Subtype #1: 'CN_CNMF'

'16q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1.46e-05 (Fisher's exact test), Q value = 0.0061

Table S27. Gene #22: '16q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 18 | 37 | 21
16Q GAIN CNV | 2 | 24 | 3
16Q GAIN WILD-TYPE | 16 | 13 | 18

Figure S27. Get High-res Image Gene #22: '16q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'16q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1.8e-06 (Fisher's exact test), Q value = 0.00076

Table S28. Gene #22: '16q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 48 | 33 | 11 | 35
16Q GAIN CNV | 13 | 10 | 10 | 25
16Q GAIN WILD-TYPE | 35 | 23 | 1 | 10

Figure S28. Get High-res Image Gene #22: '16q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'17p gain' versus 'CN_CNMF'

P value = 9.52e-08 (Chi-square test), Q value = 4.1e-05

Table S29. Gene #23: '17p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
17P GAIN CNV | 6 | 19 | 13 | 9 | 19
17P GAIN WILD-TYPE | 18 | 25 | 0 | 17 | 1

Figure S29. Get High-res Image Gene #23: '17p gain' versus Molecular Subtype #1: 'CN_CNMF'

'17p gain' versus 'METHLYATION_CNMF'

P value = 1.3e-06 (Fisher's exact test), Q value = 0.00056

Table S30. Gene #23: '17p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 27 | 53 | 31
17P GAIN CNV | 9 | 40 | 7
17P GAIN WILD-TYPE | 18 | 13 | 24

Figure S30. Get High-res Image Gene #23: '17p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'17p gain' versus 'MRNASEQ_CNMF'

P value = 3.49e-05 (Fisher's exact test), Q value = 0.014

Table S31. Gene #23: '17p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 27 | 24 | 25
17P GAIN CNV | 20 | 3 | 10
17P GAIN WILD-TYPE | 7 | 21 | 15

Figure S31. Get High-res Image Gene #23: '17p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'17p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.21e-06 (Fisher's exact test), Q value = 0.00094

Table S32. Gene #23: '17p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 18 | 37 | 21
17P GAIN CNV | 3 | 27 | 3
17P GAIN WILD-TYPE | 15 | 10 | 18

Figure S32. Get High-res Image Gene #23: '17p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'17p gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 7.75e-05 (Fisher's exact test), Q value = 0.032

Table S33. Gene #23: '17p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 48 | 33 | 11 | 35
17P GAIN CNV | 22 | 9 | 10 | 25
17P GAIN WILD-TYPE | 26 | 24 | 1 | 10

Figure S33. Get High-res Image Gene #23: '17p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'17q gain' versus 'CN_CNMF'

P value = 5.4e-06 (Chi-square test), Q value = 0.0023

Table S34. Gene #24: '17q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
17Q GAIN CNV | 7 | 25 | 13 | 13 | 19
17Q GAIN WILD-TYPE | 17 | 19 | 0 | 13 | 1

Figure S34. Get High-res Image Gene #24: '17q gain' versus Molecular Subtype #1: 'CN_CNMF'

'4p loss' versus 'CN_CNMF'

P value = 0.000247 (Chi-square test), Q value = 0.099

Table S35. Gene #35: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
4P LOSS CNV | 7 | 0 | 0 | 4 | 0
4P LOSS WILD-TYPE | 17 | 44 | 13 | 22 | 20

Figure S35. Get High-res Image Gene #35: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

'5q loss' versus 'CN_CNMF'

P value = 1.96e-05 (Chi-square test), Q value = 0.0081

Table S36. Gene #38: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
5Q LOSS CNV | 6 | 0 | 0 | 0 | 0
5Q LOSS WILD-TYPE | 18 | 44 | 13 | 26 | 20

Figure S36. Get High-res Image Gene #38: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

'6p loss' versus 'CN_CNMF'

P value = 0.00043 (Chi-square test), Q value = 0.17

Table S37. Gene #39: '6p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
6P LOSS CNV | 1 | 0 | 0 | 7 | 1
6P LOSS WILD-TYPE | 23 | 44 | 13 | 19 | 19

Figure S37. Get High-res Image Gene #39: '6p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'CN_CNMF'

P value = 0.000169 (Chi-square test), Q value = 0.069

Table S38. Gene #42: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
9P LOSS CNV | 8 | 0 | 0 | 6 | 1
9P LOSS WILD-TYPE | 16 | 44 | 13 | 20 | 19

Figure S38. Get High-res Image Gene #42: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'METHLYATION_CNMF'

P value = 0.000318 (Fisher's exact test), Q value = 0.13

Table S39. Gene #42: '9p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 27 | 53 | 31
9P LOSS CNV | 5 | 0 | 7
9P LOSS WILD-TYPE | 22 | 53 | 24

Figure S39. Get High-res Image Gene #42: '9p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'9q loss' versus 'CN_CNMF'

P value = 0.000445 (Chi-square test), Q value = 0.18

Table S40. Gene #43: '9q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
9Q LOSS CNV | 8 | 1 | 0 | 7 | 1
9Q LOSS WILD-TYPE | 16 | 43 | 13 | 19 | 19

Figure S40. Get High-res Image Gene #43: '9q loss' versus Molecular Subtype #1: 'CN_CNMF'

'9q loss' versus 'METHLYATION_CNMF'

P value = 3.17e-05 (Fisher's exact test), Q value = 0.013

Table S41. Gene #43: '9q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 27 | 53 | 31
9Q LOSS CNV | 6 | 0 | 9
9Q LOSS WILD-TYPE | 21 | 53 | 22

Figure S41. Get High-res Image Gene #43: '9q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'14q loss' versus 'CN_CNMF'

P value = 1.54e-11 (Chi-square test), Q value = 6.7e-09

Table S42. Gene #49: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
14Q LOSS CNV | 16 | 0 | 0 | 7 | 0
14Q LOSS WILD-TYPE | 8 | 44 | 13 | 19 | 20

Figure S42. Get High-res Image Gene #49: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

'22q loss' versus 'CN_CNMF'

P value = 0.000233 (Chi-square test), Q value = 0.094

Table S43. Gene #58: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 24 | 44 | 13 | 26 | 20
22Q LOSS CNV | 6 | 6 | 0 | 12 | 0
22Q LOSS WILD-TYPE | 18 | 38 | 13 | 14 | 20

Figure S43. Get High-res Image Gene #58: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data
Input

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

- Molecular subtypes file = KIRP-TP.transferedmergedcluster.txt

- Number of patients = 127

- Number of significantly arm-level cnvs = 59

- Number of molecular subtypes = 8

- Exclude genes that fewer than K tumors have mutations, K = 3

Chi-square test

For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[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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