Correlation between copy number variations of arm-level result and molecular subtypes
Kidney Chromophobe (Primary solid tumor)
22 February 2013 | analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C1F47MB2
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/C1F47MB2
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 57 arm-level results and 6 molecular subtypes across 66 patients, 51 significant findings detected with Q value < 0.25.

- 4p gain cnv correlated to 'MRNASEQ_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

- 4q gain cnv correlated to 'MRNASEQ_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

- 11p gain cnv correlated to 'MRNASEQ_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

- 11q gain cnv correlated to 'MRNASEQ_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

- 14q gain cnv correlated to 'MRNASEQ_CNMF'.

- 16p gain cnv correlated to 'MRNASEQ_CNMF'.

- 16q gain cnv correlated to 'MRNASEQ_CNMF'.

- Xq gain cnv correlated to 'MRNASEQ_CNMF'.

- 1p loss cnv correlated to 'METHLYATION_CNMF', 'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

- 1q loss cnv correlated to 'METHLYATION_CNMF', 'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

- 2p loss cnv correlated to 'METHLYATION_CNMF', 'MRNASEQ_CNMF', 'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

- 2q loss cnv correlated to 'METHLYATION_CNMF', 'MRNASEQ_CNMF', 'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

- 6p loss cnv correlated to 'METHLYATION_CNMF', 'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

- 6q loss cnv correlated to 'METHLYATION_CNMF', 'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

- 8p loss cnv correlated to 'CN_CNMF'.

- 8q loss cnv correlated to 'CN_CNMF'.

- 10p loss cnv correlated to 'MRNASEQ_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

- 10q loss cnv correlated to 'MRNASEQ_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

- 13q loss cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

- 16q loss cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

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

- 17q loss cnv correlated to 'METHLYATION_CNMF', 'MRNASEQ_CNMF', 'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

- Xq loss cnv correlated to 'METHLYATION_CNMF', 'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

Results
Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 57 arm-level results and 6 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 51 significant findings detected.

|  | Molecular subtypes | CN CNMF | METHLYATION CNMF | MRNASEQ CNMF | MRNASEQ CHIERARCHICAL | MIRSEQ CNMF | MIRSEQ CHIERARCHICAL
| nCNV (%) | nWild-Type | Fisher's exact test | Fisher's exact test | Fisher's exact test | Chi-square test | Fisher's exact test | Fisher's exact test
2p loss | 43 (65%) | 23 | 0.0828 (1.00) | 4.57e-06 (0.00148) | 8.31e-09 (2.82e-06) | 2.26e-07 (7.58e-05) | 0.0132 (1.00) | 0.000592 (0.174)
2q loss | 43 (65%) | 23 | 0.0828 (1.00) | 4.57e-06 (0.00148) | 8.31e-09 (2.82e-06) | 2.26e-07 (7.58e-05) | 0.0132 (1.00) | 0.000592 (0.174)
17p loss | 45 (68%) | 21 | 0.158 (1.00) | 1.31e-06 (0.00043) | 2.61e-09 (8.91e-07) | 3e-07 (1e-04) | 0.00372 (1.00) | 0.000255 (0.0761)
17q loss | 45 (68%) | 21 | 0.158 (1.00) | 1.31e-06 (0.00043) | 2.61e-09 (8.91e-07) | 3e-07 (1e-04) | 0.00372 (1.00) | 0.000255 (0.0761)
1p loss | 48 (73%) | 18 | 0.342 (1.00) | 5.89e-06 (0.00189) | 8.26e-06 (0.00264) | 1.79e-05 (0.0057) | 0.0798 (1.00) | 0.00103 (0.296)
1q loss | 47 (71%) | 19 | 0.32 (1.00) | 1.06e-05 (0.00337) | 3.11e-05 (0.00972) | 6.59e-05 (0.0205) | 0.0316 (1.00) | 0.00157 (0.443)
6p loss | 47 (71%) | 19 | 0.32 (1.00) | 0.000132 (0.0401) | 1.26e-06 (0.000417) | 2.67e-05 (0.00844) | 0.0316 (1.00) | 0.00157 (0.443)
6q loss | 47 (71%) | 19 | 0.32 (1.00) | 0.000132 (0.0401) | 1.26e-06 (0.000417) | 2.67e-05 (0.00844) | 0.0316 (1.00) | 0.00157 (0.443)
Xq loss | 33 (50%) | 33 | 0.713 (1.00) | 2.45e-05 (0.00777) | 7.96e-05 (0.0247) | 0.000217 (0.0648) | 0.0466 (1.00) | 0.00208 (0.575)
4p gain | 18 (27%) | 48 | 0.383 (1.00) | 0.813 (1.00) | 4.56e-05 (0.0142) | 0.000161 (0.0486) | 0.455 (1.00) | 0.1 (1.00)
4q gain | 17 (26%) | 49 | 0.362 (1.00) | 0.701 (1.00) | 0.000173 (0.0519) | 0.000784 (0.228) | 0.262 (1.00) | 0.0977 (1.00)
11p gain | 13 (20%) | 53 | 0.517 (1.00) | 0.271 (1.00) | 0.000287 (0.0851) | 0.000156 (0.0472) | 1 (1.00) | 0.186 (1.00)
11q gain | 14 (21%) | 52 | 0.606 (1.00) | 0.273 (1.00) | 8.33e-05 (0.0257) | 2.78e-05 (0.00874) | 1 (1.00) | 0.186 (1.00)
10p loss | 44 (67%) | 22 | 0.261 (1.00) | 0.00198 (0.553) | 2.51e-06 (0.00082) | 3.03e-06 (0.000983) | 0.19 (1.00) | 0.0506 (1.00)
10q loss | 44 (67%) | 22 | 0.261 (1.00) | 0.00198 (0.553) | 2.51e-06 (0.00082) | 3.03e-06 (0.000983) | 0.19 (1.00) | 0.0506 (1.00)
14q gain | 16 (24%) | 50 | 0.34 (1.00) | 0.554 (1.00) | 0.000706 (0.206) | 0.00332 (0.903) | 0.445 (1.00) | 0.436 (1.00)
16p gain | 15 (23%) | 51 | 0.556 (1.00) | 0.8 (1.00) | 9.21e-05 (0.0282) | 0.000936 (0.271) | 0.112 (1.00) | 0.106 (1.00)
16q gain | 15 (23%) | 51 | 0.556 (1.00) | 0.8 (1.00) | 9.21e-05 (0.0282) | 0.000936 (0.271) | 0.112 (1.00) | 0.106 (1.00)
Xq gain | 9 (14%) | 57 | 1 (1.00) | 0.503 (1.00) | 8.84e-05 (0.0271) | 0.00417 (1.00) | 0.27 (1.00) | 0.341 (1.00)
8p loss | 9 (14%) | 57 | 8.11e-08 (2.73e-05) | 0.0576 (1.00) | 0.0531 (1.00) | 0.0036 (0.974) | 0.126 (1.00) | 0.341 (1.00)
8q loss | 8 (12%) | 58 | 5.86e-07 (0.000195) | 0.0381 (1.00) | 0.134 (1.00) | 0.00434 (1.00) | 0.251 (1.00) | 0.586 (1.00)
13q loss | 37 (56%) | 29 | 0.116 (1.00) | 0.00923 (1.00) | 0.00123 (0.351) | 0.000506 (0.149) | 0.548 (1.00) | 0.036 (1.00)
16q loss | 4 (6%) | 62 | 0.685 (1.00) | 0.653 (1.00) | 0.00219 (0.601) | 8.58e-05 (0.0264) | 1 (1.00) | 0.452 (1.00)
3p gain | 5 (8%) | 61 | 0.721 (1.00) | 0.698 (1.00) | 1 (1.00) | 0.942 (1.00) | 0.356 (1.00) | 0.134 (1.00)
3q gain | 5 (8%) | 61 | 0.721 (1.00) | 0.698 (1.00) | 1 (1.00) | 0.942 (1.00) | 0.356 (1.00) | 0.134 (1.00)
5p gain | 5 (8%) | 61 | 0.549 (1.00) | 0.698 (1.00) | 1 (1.00) | 0.839 (1.00) | 1 (1.00) | 0.134 (1.00)
5q gain | 5 (8%) | 61 | 0.549 (1.00) | 0.698 (1.00) | 1 (1.00) | 0.839 (1.00) | 1 (1.00) | 0.134 (1.00)
7p gain | 18 (27%) | 48 | 0.383 (1.00) | 0.384 (1.00) | 0.00906 (1.00) | 0.0191 (1.00) | 0.646 (1.00) | 1 (1.00)
7q gain | 18 (27%) | 48 | 0.383 (1.00) | 0.384 (1.00) | 0.00906 (1.00) | 0.0191 (1.00) | 0.646 (1.00) | 1 (1.00)
8p gain | 13 (20%) | 53 | 0.274 (1.00) | 0.0865 (1.00) | 0.0276 (1.00) | 0.0848 (1.00) | 0.39 (1.00) | 1 (1.00)
8q gain | 14 (21%) | 52 | 0.157 (1.00) | 0.105 (1.00) | 0.00994 (1.00) | 0.0317 (1.00) | 0.649 (1.00) | 1 (1.00)
9p gain | 8 (12%) | 58 | 1 (1.00) | 0.609 (1.00) | 0.911 (1.00) | 0.841 (1.00) | 0.714 (1.00) | 0.298 (1.00)
9q gain | 8 (12%) | 58 | 1 (1.00) | 0.609 (1.00) | 0.911 (1.00) | 0.841 (1.00) | 0.714 (1.00) | 0.298 (1.00)
12p gain | 14 (21%) | 52 | 0.688 (1.00) | 0.437 (1.00) | 0.0129 (1.00) | 0.0542 (1.00) | 0.414 (1.00) | 1 (1.00)
12q gain | 13 (20%) | 53 | 0.764 (1.00) | 0.709 (1.00) | 0.0135 (1.00) | 0.0191 (1.00) | 0.39 (1.00) | 0.675 (1.00)
15q gain | 14 (21%) | 52 | 0.224 (1.00) | 0.249 (1.00) | 0.00113 (0.324) | 0.00646 (1.00) | 0.803 (1.00) | 0.671 (1.00)
18p gain | 14 (21%) | 52 | 0.475 (1.00) | 0.294 (1.00) | 0.0062 (1.00) | 0.0191 (1.00) | 1 (1.00) | 0.386 (1.00)
18q gain | 13 (20%) | 53 | 0.671 (1.00) | 0.581 (1.00) | 0.00409 (1.00) | 0.0183 (1.00) | 0.793 (1.00) | 1 (1.00)
19p gain | 11 (17%) | 55 | 0.867 (1.00) | 0.83 (1.00) | 0.00206 (0.571) | 0.00219 (0.601) | 0.347 (1.00) | 0.337 (1.00)
19q gain | 9 (14%) | 57 | 0.713 (1.00) | 0.72 (1.00) | 0.00269 (0.734) | 0.00372 (1.00) | 0.126 (1.00) | 0.341 (1.00)
20p gain | 14 (21%) | 52 | 0.224 (1.00) | 0.672 (1.00) | 0.00468 (1.00) | 0.00377 (1.00) | 0.414 (1.00) | 0.671 (1.00)
20q gain | 15 (23%) | 51 | 0.282 (1.00) | 0.397 (1.00) | 0.00713 (1.00) | 0.00743 (1.00) | 0.611 (1.00) | 1 (1.00)
21q gain | 3 (5%) | 63 | 0.646 (1.00) |  | 0.327 (1.00) | 0.333 (1.00) | 0.767 (1.00) | 0.361 (1.00)
22q gain | 15 (23%) | 51 | 0.882 (1.00) | 0.116 (1.00) | 0.0748 (1.00) | 0.196 (1.00) | 0.932 (1.00) | 1 (1.00)
3p loss | 7 (11%) | 59 | 0.0826 (1.00) | 1 (1.00) | 0.252 (1.00) | 0.00554 (1.00) | 0.482 (1.00) | 0.581 (1.00)
3q loss | 6 (9%) | 60 | 0.0326 (1.00) | 0.532 (1.00) | 0.135 (1.00) | 0.00126 (0.358) | 0.348 (1.00) | 0.585 (1.00)
5p loss | 7 (11%) | 59 | 0.302 (1.00) | 0.175 (1.00) | 0.0329 (1.00) | 0.00478 (1.00) | 0.196 (1.00) | 0.581 (1.00)
5q loss | 7 (11%) | 59 | 0.302 (1.00) | 0.175 (1.00) | 0.0329 (1.00) | 0.00478 (1.00) | 0.196 (1.00) | 0.581 (1.00)
9p loss | 8 (12%) | 58 | 1 (1.00) | 1 (1.00) | 0.171 (1.00) | 0.579 (1.00) | 0.714 (1.00) | 0.298 (1.00)
9q loss | 8 (12%) | 58 | 1 (1.00) | 1 (1.00) | 0.171 (1.00) | 0.579 (1.00) | 0.714 (1.00) | 0.298 (1.00)
11p loss | 5 (8%) | 61 | 1 (1.00) | 0.593 (1.00) | 0.129 (1.00) | 0.408 (1.00) | 0.606 (1.00) | 1 (1.00)
11q loss | 5 (8%) | 61 | 1 (1.00) | 0.593 (1.00) | 0.129 (1.00) | 0.408 (1.00) | 0.606 (1.00) | 1 (1.00)
16p loss | 3 (5%) | 63 | 1 (1.00) | 0.417 (1.00) | 0.0126 (1.00) | 0.00148 (0.418) | 1 (1.00) | 1 (1.00)
18p loss | 5 (8%) | 61 | 0.257 (1.00) | 0.118 (1.00) | 0.0134 (1.00) | 0.0012 (0.343) | 0.606 (1.00) | 1 (1.00)
18q loss | 7 (11%) | 59 | 0.222 (1.00) | 0.175 (1.00) | 0.0481 (1.00) | 0.0178 (1.00) | 0.482 (1.00) | 1 (1.00)
21q loss | 28 (42%) | 38 | 1 (1.00) | 0.0183 (1.00) | 0.23 (1.00) | 0.0379 (1.00) | 0.742 (1.00) | 0.722 (1.00)
22q loss | 5 (8%) | 61 | 0.721 (1.00) | 0.118 (1.00) | 0.745 (1.00) | 0.38 (1.00) | 0.356 (1.00) | 1 (1.00)

'4p gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 4.56e-05 (Fisher's exact test), Q value = 0.014

Table S1. Gene #3: '4p gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
4P GAIN MUTATED | 3 | 14 | 1 | 0
4P GAIN WILD-TYPE | 16 | 8 | 14 | 10

Figure S1. Get High-res Image Gene #3: '4p gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'4p gain mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000161 (Chi-square test), Q value = 0.049

Table S2. Gene #3: '4p gain mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
4P GAIN MUTATED | 1 | 1 | 12 | 0 | 4
4P GAIN WILD-TYPE | 9 | 9 | 5 | 6 | 19

Figure S2. Get High-res Image Gene #3: '4p gain mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'4q gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 0.000173 (Fisher's exact test), Q value = 0.052

Table S3. Gene #4: '4q gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
4Q GAIN MUTATED | 3 | 13 | 1 | 0
4Q GAIN WILD-TYPE | 16 | 9 | 14 | 10

Figure S3. Get High-res Image Gene #4: '4q gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'4q gain mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000784 (Chi-square test), Q value = 0.23

Table S4. Gene #4: '4q gain mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
4Q GAIN MUTATED | 1 | 1 | 11 | 0 | 4
4Q GAIN WILD-TYPE | 9 | 9 | 6 | 6 | 19

Figure S4. Get High-res Image Gene #4: '4q gain mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'11p gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 0.000287 (Fisher's exact test), Q value = 0.085

Table S5. Gene #13: '11p gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
11P GAIN MUTATED | 1 | 11 | 1 | 0
11P GAIN WILD-TYPE | 18 | 11 | 14 | 10

Figure S5. Get High-res Image Gene #13: '11p gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'11p gain mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000156 (Chi-square test), Q value = 0.047

Table S6. Gene #13: '11p gain mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
11P GAIN MUTATED | 1 | 1 | 10 | 0 | 1
11P GAIN WILD-TYPE | 9 | 9 | 7 | 6 | 22

Figure S6. Get High-res Image Gene #13: '11p gain mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'11q gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 8.33e-05 (Fisher's exact test), Q value = 0.026

Table S7. Gene #14: '11q gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
11Q GAIN MUTATED | 1 | 12 | 1 | 0
11Q GAIN WILD-TYPE | 18 | 10 | 14 | 10

Figure S7. Get High-res Image Gene #14: '11q gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'11q gain mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.78e-05 (Chi-square test), Q value = 0.0087

Table S8. Gene #14: '11q gain mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
11Q GAIN MUTATED | 1 | 1 | 11 | 0 | 1
11Q GAIN WILD-TYPE | 9 | 9 | 6 | 6 | 22

Figure S8. Get High-res Image Gene #14: '11q gain mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'14q gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 0.000706 (Fisher's exact test), Q value = 0.21

Table S9. Gene #17: '14q gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
14Q GAIN MUTATED | 3 | 12 | 1 | 0
14Q GAIN WILD-TYPE | 16 | 10 | 14 | 10

Figure S9. Get High-res Image Gene #17: '14q gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'16p gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 9.21e-05 (Fisher's exact test), Q value = 0.028

Table S10. Gene #19: '16p gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
16P GAIN MUTATED | 3 | 12 | 0 | 0
16P GAIN WILD-TYPE | 16 | 10 | 15 | 10

Figure S10. Get High-res Image Gene #19: '16p gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'16q gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 9.21e-05 (Fisher's exact test), Q value = 0.028

Table S11. Gene #20: '16q gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
16Q GAIN MUTATED | 3 | 12 | 0 | 0
16Q GAIN WILD-TYPE | 16 | 10 | 15 | 10

Figure S11. Get High-res Image Gene #20: '16q gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'Xq gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 8.84e-05 (Fisher's exact test), Q value = 0.027

Table S12. Gene #29: 'Xq gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
XQ GAIN MUTATED | 0 | 9 | 0 | 0
XQ GAIN WILD-TYPE | 19 | 13 | 15 | 10

Figure S12. Get High-res Image Gene #29: 'Xq gain mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'1p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 5.89e-06 (Fisher's exact test), Q value = 0.0019

Table S13. Gene #30: '1p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 17 | 34 | 14
1P LOSS MUTATED | 16 | 29 | 3
1P LOSS WILD-TYPE | 1 | 5 | 11

Figure S13. Get High-res Image Gene #30: '1p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'1p loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 8.26e-06 (Fisher's exact test), Q value = 0.0026

Table S14. Gene #30: '1p loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
1P LOSS MUTATED | 19 | 12 | 14 | 3
1P LOSS WILD-TYPE | 0 | 10 | 1 | 7

Figure S14. Get High-res Image Gene #30: '1p loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'1p loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1.79e-05 (Chi-square test), Q value = 0.0057

Table S15. Gene #30: '1p loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
1P LOSS MUTATED | 9 | 2 | 9 | 6 | 22
1P LOSS WILD-TYPE | 1 | 8 | 8 | 0 | 1

Figure S15. Get High-res Image Gene #30: '1p loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'1q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 1.06e-05 (Fisher's exact test), Q value = 0.0034

Table S16. Gene #31: '1q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 17 | 34 | 14
1Q LOSS MUTATED | 16 | 28 | 3
1Q LOSS WILD-TYPE | 1 | 6 | 11

Figure S16. Get High-res Image Gene #31: '1q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'1q loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 3.11e-05 (Fisher's exact test), Q value = 0.0097

Table S17. Gene #31: '1q loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
1Q LOSS MUTATED | 19 | 12 | 13 | 3
1Q LOSS WILD-TYPE | 0 | 10 | 2 | 7

Figure S17. Get High-res Image Gene #31: '1q loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'1q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 6.59e-05 (Chi-square test), Q value = 0.021

Table S18. Gene #31: '1q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
1Q LOSS MUTATED | 9 | 2 | 9 | 5 | 22
1Q LOSS WILD-TYPE | 1 | 8 | 8 | 1 | 1

Figure S18. Get High-res Image Gene #31: '1q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'2p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 4.57e-06 (Fisher's exact test), Q value = 0.0015

Table S19. Gene #32: '2p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 17 | 34 | 14
2P LOSS MUTATED | 16 | 25 | 2
2P LOSS WILD-TYPE | 1 | 9 | 12

Figure S19. Get High-res Image Gene #32: '2p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'2p loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 8.31e-09 (Fisher's exact test), Q value = 2.8e-06

Table S20. Gene #32: '2p loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
2P LOSS MUTATED | 19 | 11 | 13 | 0
2P LOSS WILD-TYPE | 0 | 11 | 2 | 10

Figure S20. Get High-res Image Gene #32: '2p loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'2p loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.26e-07 (Chi-square test), Q value = 7.6e-05

Table S21. Gene #32: '2p loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
2P LOSS MUTATED | 10 | 0 | 8 | 3 | 22
2P LOSS WILD-TYPE | 0 | 10 | 9 | 3 | 1

Figure S21. Get High-res Image Gene #32: '2p loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'2p loss mutation analysis' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000592 (Fisher's exact test), Q value = 0.17

Table S22. Gene #32: '2p loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2
--- | --- | ---
ALL | 9 | 57
2P LOSS MUTATED | 1 | 42
2P LOSS WILD-TYPE | 8 | 15

Figure S22. Get High-res Image Gene #32: '2p loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'2q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 4.57e-06 (Fisher's exact test), Q value = 0.0015

Table S23. Gene #33: '2q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 17 | 34 | 14
2Q LOSS MUTATED | 16 | 25 | 2
2Q LOSS WILD-TYPE | 1 | 9 | 12

Figure S23. Get High-res Image Gene #33: '2q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'2q loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 8.31e-09 (Fisher's exact test), Q value = 2.8e-06

Table S24. Gene #33: '2q loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
2Q LOSS MUTATED | 19 | 11 | 13 | 0
2Q LOSS WILD-TYPE | 0 | 11 | 2 | 10

Figure S24. Get High-res Image Gene #33: '2q loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'2q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.26e-07 (Chi-square test), Q value = 7.6e-05

Table S25. Gene #33: '2q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
2Q LOSS MUTATED | 10 | 0 | 8 | 3 | 22
2Q LOSS WILD-TYPE | 0 | 10 | 9 | 3 | 1

Figure S25. Get High-res Image Gene #33: '2q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'2q loss mutation analysis' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000592 (Fisher's exact test), Q value = 0.17

Table S26. Gene #33: '2q loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2
--- | --- | ---
ALL | 9 | 57
2Q LOSS MUTATED | 1 | 42
2Q LOSS WILD-TYPE | 8 | 15

Figure S26. Get High-res Image Gene #33: '2q loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'6p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000132 (Fisher's exact test), Q value = 0.04

Table S27. Gene #38: '6p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 17 | 34 | 14
6P LOSS MUTATED | 16 | 27 | 4
6P LOSS WILD-TYPE | 1 | 7 | 10

Figure S27. Get High-res Image Gene #38: '6p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'6p loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 1.26e-06 (Fisher's exact test), Q value = 0.00042

Table S28. Gene #38: '6p loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
6P LOSS MUTATED | 19 | 12 | 14 | 2
6P LOSS WILD-TYPE | 0 | 10 | 1 | 8

Figure S28. Get High-res Image Gene #38: '6p loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'6p loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.67e-05 (Chi-square test), Q value = 0.0084

Table S29. Gene #38: '6p loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
6P LOSS MUTATED | 10 | 2 | 9 | 4 | 22
6P LOSS WILD-TYPE | 0 | 8 | 8 | 2 | 1

Figure S29. Get High-res Image Gene #38: '6p loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'6q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000132 (Fisher's exact test), Q value = 0.04

Table S30. Gene #39: '6q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 17 | 34 | 14
6Q LOSS MUTATED | 16 | 27 | 4
6Q LOSS WILD-TYPE | 1 | 7 | 10

Figure S30. Get High-res Image Gene #39: '6q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'6q loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 1.26e-06 (Fisher's exact test), Q value = 0.00042

Table S31. Gene #39: '6q loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
6Q LOSS MUTATED | 19 | 12 | 14 | 2
6Q LOSS WILD-TYPE | 0 | 10 | 1 | 8

Figure S31. Get High-res Image Gene #39: '6q loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'6q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.67e-05 (Chi-square test), Q value = 0.0084

Table S32. Gene #39: '6q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
6Q LOSS MUTATED | 10 | 2 | 9 | 4 | 22
6Q LOSS WILD-TYPE | 0 | 8 | 8 | 2 | 1

Figure S32. Get High-res Image Gene #39: '6q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'8p loss mutation analysis' versus 'CN_CNMF'

P value = 8.11e-08 (Fisher's exact test), Q value = 2.7e-05

Table S33. Gene #40: '8p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 5 | 47 | 14
8P LOSS MUTATED | 0 | 0 | 9
8P LOSS WILD-TYPE | 5 | 47 | 5

Figure S33. Get High-res Image Gene #40: '8p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'8q loss mutation analysis' versus 'CN_CNMF'

P value = 5.86e-07 (Fisher's exact test), Q value = 0.00019

Table S34. Gene #41: '8q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 5 | 47 | 14
8Q LOSS MUTATED | 0 | 0 | 8
8Q LOSS WILD-TYPE | 5 | 47 | 6

Figure S34. Get High-res Image Gene #41: '8q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'10p loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 2.51e-06 (Fisher's exact test), Q value = 0.00082

Table S35. Gene #44: '10p loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
10P LOSS MUTATED | 19 | 9 | 13 | 3
10P LOSS WILD-TYPE | 0 | 13 | 2 | 7

Figure S35. Get High-res Image Gene #44: '10p loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'10p loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3.03e-06 (Chi-square test), Q value = 0.00098

Table S36. Gene #44: '10p loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
10P LOSS MUTATED | 10 | 2 | 6 | 4 | 22
10P LOSS WILD-TYPE | 0 | 8 | 11 | 2 | 1

Figure S36. Get High-res Image Gene #44: '10p loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'10q loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 2.51e-06 (Fisher's exact test), Q value = 0.00082

Table S37. Gene #45: '10q loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
10Q LOSS MUTATED | 19 | 9 | 13 | 3
10Q LOSS WILD-TYPE | 0 | 13 | 2 | 7

Figure S37. Get High-res Image Gene #45: '10q loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'10q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3.03e-06 (Chi-square test), Q value = 0.00098

Table S38. Gene #45: '10q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
10Q LOSS MUTATED | 10 | 2 | 6 | 4 | 22
10Q LOSS WILD-TYPE | 0 | 8 | 11 | 2 | 1

Figure S38. Get High-res Image Gene #45: '10q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'13q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000506 (Chi-square test), Q value = 0.15

Table S39. Gene #48: '13q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
13Q LOSS MUTATED | 10 | 1 | 8 | 2 | 16
13Q LOSS WILD-TYPE | 0 | 9 | 9 | 4 | 7

Figure S39. Get High-res Image Gene #48: '13q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'16q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 8.58e-05 (Chi-square test), Q value = 0.026

Table S40. Gene #50: '16q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
16Q LOSS MUTATED | 4 | 0 | 0 | 0 | 0
16Q LOSS WILD-TYPE | 6 | 10 | 17 | 6 | 23

Figure S40. Get High-res Image Gene #50: '16q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'17p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 1.31e-06 (Fisher's exact test), Q value = 0.00043

Table S41. Gene #51: '17p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 17 | 34 | 14
17P LOSS MUTATED | 16 | 27 | 2
17P LOSS WILD-TYPE | 1 | 7 | 12

Figure S41. Get High-res Image Gene #51: '17p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'17p loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 2.61e-09 (Fisher's exact test), Q value = 8.9e-07

Table S42. Gene #51: '17p loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
17P LOSS MUTATED | 19 | 12 | 14 | 0
17P LOSS WILD-TYPE | 0 | 10 | 1 | 10

Figure S42. Get High-res Image Gene #51: '17p loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'17p loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3e-07 (Chi-square test), Q value = 1e-04

Table S43. Gene #51: '17p loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
17P LOSS MUTATED | 10 | 0 | 9 | 4 | 22
17P LOSS WILD-TYPE | 0 | 10 | 8 | 2 | 1

Figure S43. Get High-res Image Gene #51: '17p loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'17p loss mutation analysis' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000255 (Fisher's exact test), Q value = 0.076

Table S44. Gene #51: '17p loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2
--- | --- | ---
ALL | 9 | 57
17P LOSS MUTATED | 1 | 44
17P LOSS WILD-TYPE | 8 | 13

Figure S44. Get High-res Image Gene #51: '17p loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'17q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 1.31e-06 (Fisher's exact test), Q value = 0.00043

Table S45. Gene #52: '17q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 17 | 34 | 14
17Q LOSS MUTATED | 16 | 27 | 2
17Q LOSS WILD-TYPE | 1 | 7 | 12

Figure S45. Get High-res Image Gene #52: '17q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'17q loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 2.61e-09 (Fisher's exact test), Q value = 8.9e-07

Table S46. Gene #52: '17q loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
17Q LOSS MUTATED | 19 | 12 | 14 | 0
17Q LOSS WILD-TYPE | 0 | 10 | 1 | 10

Figure S46. Get High-res Image Gene #52: '17q loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'17q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3e-07 (Chi-square test), Q value = 1e-04

Table S47. Gene #52: '17q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
17Q LOSS MUTATED | 10 | 0 | 9 | 4 | 22
17Q LOSS WILD-TYPE | 0 | 10 | 8 | 2 | 1

Figure S47. Get High-res Image Gene #52: '17q loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

'17q loss mutation analysis' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000255 (Fisher's exact test), Q value = 0.076

Table S48. Gene #52: '17q loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2
--- | --- | ---
ALL | 9 | 57
17Q LOSS MUTATED | 1 | 44
17Q LOSS WILD-TYPE | 8 | 13

Figure S48. Get High-res Image Gene #52: '17q loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'Xq loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 2.45e-05 (Fisher's exact test), Q value = 0.0078

Table S49. Gene #57: 'Xq loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3
--- | --- | --- | ---
ALL | 17 | 34 | 14
XQ LOSS MUTATED | 12 | 21 | 0
XQ LOSS WILD-TYPE | 5 | 13 | 14

Figure S49. Get High-res Image Gene #57: 'Xq loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'Xq loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 7.96e-05 (Fisher's exact test), Q value = 0.025

Table S50. Gene #57: 'Xq loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4
--- | --- | --- | --- | ---
ALL | 19 | 22 | 15 | 10
XQ LOSS MUTATED | 15 | 8 | 10 | 0
XQ LOSS WILD-TYPE | 4 | 14 | 5 | 10

Figure S50. Get High-res Image Gene #57: 'Xq loss mutation analysis' versus Clinical Feature #3: 'MRNASEQ_CNMF'

'Xq loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000217 (Chi-square test), Q value = 0.065

Table S51. Gene #57: 'Xq loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

nPatients | CLUS_1 | CLUS_2 | CLUS_3 | CLUS_4 | CLUS_5
--- | --- | --- | --- | --- | ---
ALL | 10 | 10 | 17 | 6 | 23
XQ LOSS MUTATED | 7 | 0 | 5 | 3 | 18
XQ LOSS WILD-TYPE | 3 | 10 | 12 | 3 | 5

Figure S51. Get High-res Image Gene #57: 'Xq loss mutation analysis' versus Clinical Feature #4: 'MRNASEQ_CHIERARCHICAL'

Methods & Data
Input

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

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

- Number of patients = 66

- Number of significantly arm-level cnvs = 57

- Number of molecular subtypes = 6

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

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

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

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] 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)
[2] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle