Correlation between copy number variations of arm-level result and molecular subtypes

Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)

15 July 2014 | analyses__2014_07_15

Maintainer Information

Citation Information

Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)

Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between copy number variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1DF6PXX

Overview

Introduction

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

Summary

Testing the association between copy number variation 80 arm-level events and 8 molecular subtypes across 206 patients, 12 significant findings detected with P value < 0.05 and Q value < 0.25.

2q gain cnv correlated to 'CN_CNMF'.
3q gain cnv correlated to 'METHLYATION_CNMF', 'MRNASEQ_CNMF', and 'MIRSEQ_MATURE_CHIERARCHICAL'.
11q gain cnv correlated to 'MRNASEQ_CHIERARCHICAL'.
19q gain cnv correlated to 'CN_CNMF'.
3p loss cnv correlated to 'MRNASEQ_CHIERARCHICAL'.
4p loss cnv correlated to 'CN_CNMF'.
4q loss cnv correlated to 'CN_CNMF'.
8q loss cnv correlated to 'MRNASEQ_CNMF'.
12p loss cnv correlated to 'CN_CNMF'.
18q loss cnv correlated to 'MRNASEQ_CNMF'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 80 arm-level events and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 12 significant findings detected.


		Clinical Features	CN CNMF	METHLYATION CNMF	MRNASEQ CNMF	MRNASEQ CHIERARCHICAL	MIRSEQ CNMF	MIRSEQ CHIERARCHICAL	MIRSEQ MATURE CNMF	MIRSEQ MATURE CHIERARCHICAL
	nCNV (%)	nWild-Type	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	Fisher's exact test
3q gain	126 (61%)	80	0.00186 (1.00)	0.00027 (0.17)	0.00023 (0.145)	0.00237 (1.00)	0.147 (1.00)	0.00853 (1.00)	0.0379 (1.00)	0.00016 (0.101)
2q gain	29 (14%)	177	0.00021 (0.133)	0.192 (1.00)	0.00708 (1.00)	0.00506 (1.00)	0.529 (1.00)	0.141 (1.00)	0.41 (1.00)	0.545 (1.00)
11q gain	7 (3%)	199	0.0306 (1.00)	0.583 (1.00)	0.0184 (1.00)	0.00033 (0.208)	0.181 (1.00)	0.215 (1.00)	0.2 (1.00)	0.0217 (1.00)
19q gain	47 (23%)	159	1e-05 (0.0064)	0.119 (1.00)	0.3 (1.00)	0.0446 (1.00)	0.159 (1.00)	0.228 (1.00)	0.151 (1.00)	0.574 (1.00)
3p loss	50 (24%)	156	0.432 (1.00)	0.0125 (1.00)	0.0572 (1.00)	0.00015 (0.0952)	0.0338 (1.00)	0.00783 (1.00)	0.118 (1.00)	0.00141 (0.871)
4p loss	86 (42%)	120	1e-05 (0.0064)	0.21 (1.00)	0.0137 (1.00)	0.00101 (0.629)	0.338 (1.00)	0.00915 (1.00)	0.518 (1.00)	0.00307 (1.00)
4q loss	61 (30%)	145	1e-05 (0.0064)	0.748 (1.00)	0.196 (1.00)	0.0142 (1.00)	0.531 (1.00)	0.331 (1.00)	0.945 (1.00)	0.0296 (1.00)
8q loss	18 (9%)	188	0.179 (1.00)	0.0998 (1.00)	5e-05 (0.0318)	0.00172 (1.00)	0.0446 (1.00)	0.0215 (1.00)	0.0278 (1.00)	0.02 (1.00)
12p loss	26 (13%)	180	0.00015 (0.0952)	0.137 (1.00)	0.224 (1.00)	0.333 (1.00)	0.191 (1.00)	0.917 (1.00)	0.174 (1.00)	0.0965 (1.00)
18q loss	53 (26%)	153	0.0277 (1.00)	0.00244 (1.00)	1e-05 (0.0064)	0.00414 (1.00)	0.112 (1.00)	0.00442 (1.00)	0.0414 (1.00)	0.00109 (0.678)
1p gain	64 (31%)	142	0.127 (1.00)	0.0123 (1.00)	0.0176 (1.00)	0.11 (1.00)	0.728 (1.00)	0.0493 (1.00)	0.829 (1.00)	0.00128 (0.794)
1q gain	97 (47%)	109	0.0147 (1.00)	0.0215 (1.00)	0.0307 (1.00)	0.285 (1.00)	0.812 (1.00)	0.351 (1.00)	0.703 (1.00)	0.0117 (1.00)
2p gain	45 (22%)	161	0.00194 (1.00)	0.018 (1.00)	0.0751 (1.00)	0.0601 (1.00)	0.471 (1.00)	0.11 (1.00)	0.774 (1.00)	0.16 (1.00)
3p gain	55 (27%)	151	0.896 (1.00)	0.335 (1.00)	0.476 (1.00)	0.594 (1.00)	0.331 (1.00)	0.761 (1.00)	0.37 (1.00)	0.32 (1.00)
4p gain	7 (3%)	199	1 (1.00)	0.813 (1.00)	0.29 (1.00)	0.656 (1.00)	1 (1.00)	0.314 (1.00)	0.709 (1.00)	0.73 (1.00)
4q gain	8 (4%)	198	0.296 (1.00)	0.24 (1.00)	0.597 (1.00)	0.395 (1.00)	0.315 (1.00)	0.0426 (1.00)	0.255 (1.00)	0.498 (1.00)
5p gain	72 (35%)	134	0.00077 (0.481)	0.344 (1.00)	0.192 (1.00)	0.559 (1.00)	0.177 (1.00)	0.0304 (1.00)	0.0711 (1.00)	0.649 (1.00)
5q gain	33 (16%)	173	0.01 (1.00)	0.874 (1.00)	0.375 (1.00)	0.872 (1.00)	0.375 (1.00)	0.833 (1.00)	0.303 (1.00)	0.724 (1.00)
6p gain	40 (19%)	166	0.363 (1.00)	0.0381 (1.00)	0.0246 (1.00)	0.0619 (1.00)	0.53 (1.00)	0.0977 (1.00)	0.838 (1.00)	0.0267 (1.00)
6q gain	25 (12%)	181	0.311 (1.00)	0.294 (1.00)	0.0593 (1.00)	0.0808 (1.00)	0.392 (1.00)	0.0781 (1.00)	0.666 (1.00)	0.814 (1.00)
7p gain	24 (12%)	182	0.0281 (1.00)	0.0648 (1.00)	0.0209 (1.00)	0.0969 (1.00)	0.0014 (0.867)	0.364 (1.00)	0.0021 (1.00)	0.438 (1.00)
7q gain	23 (11%)	183	0.0439 (1.00)	0.0908 (1.00)	0.0865 (1.00)	0.316 (1.00)	0.0112 (1.00)	0.165 (1.00)	0.0172 (1.00)	0.418 (1.00)
8p gain	32 (16%)	174	0.823 (1.00)	0.517 (1.00)	0.122 (1.00)	0.161 (1.00)	1 (1.00)	0.553 (1.00)	0.582 (1.00)	0.0343 (1.00)
8q gain	56 (27%)	150	0.363 (1.00)	0.29 (1.00)	0.113 (1.00)	0.0541 (1.00)	0.149 (1.00)	0.0398 (1.00)	0.422 (1.00)	0.04 (1.00)
9p gain	32 (16%)	174	0.351 (1.00)	0.219 (1.00)	0.828 (1.00)	0.158 (1.00)	0.613 (1.00)	0.802 (1.00)	0.836 (1.00)	0.554 (1.00)
9q gain	31 (15%)	175	0.238 (1.00)	0.00519 (1.00)	0.0726 (1.00)	0.0128 (1.00)	0.0312 (1.00)	0.0189 (1.00)	0.0968 (1.00)	0.164 (1.00)
10p gain	16 (8%)	190	0.292 (1.00)	0.822 (1.00)	0.433 (1.00)	0.768 (1.00)	0.72 (1.00)	0.478 (1.00)	0.611 (1.00)	0.924 (1.00)
10q gain	10 (5%)	196	0.709 (1.00)	0.744 (1.00)	1 (1.00)	0.514 (1.00)	0.326 (1.00)	0.674 (1.00)	0.61 (1.00)	0.964 (1.00)
11p gain	7 (3%)	199	0.889 (1.00)	0.79 (1.00)	0.548 (1.00)	0.0482 (1.00)	0.796 (1.00)	0.569 (1.00)	0.709 (1.00)	0.148 (1.00)
12p gain	35 (17%)	171	0.306 (1.00)	0.473 (1.00)	0.51 (1.00)	0.32 (1.00)	0.0951 (1.00)	0.407 (1.00)	0.0222 (1.00)	0.84 (1.00)
12q gain	32 (16%)	174	0.302 (1.00)	0.143 (1.00)	0.552 (1.00)	0.0663 (1.00)	0.156 (1.00)	0.533 (1.00)	0.102 (1.00)	0.719 (1.00)
13q gain	16 (8%)	190	0.557 (1.00)	0.338 (1.00)	0.0268 (1.00)	0.0429 (1.00)	0.00337 (1.00)	0.0509 (1.00)	0.0055 (1.00)	0.14 (1.00)
14q gain	30 (15%)	176	0.253 (1.00)	0.242 (1.00)	0.519 (1.00)	0.672 (1.00)	0.153 (1.00)	0.348 (1.00)	0.0832 (1.00)	0.377 (1.00)
15q gain	37 (18%)	169	0.749 (1.00)	0.385 (1.00)	0.946 (1.00)	0.864 (1.00)	0.247 (1.00)	0.968 (1.00)	0.634 (1.00)	0.756 (1.00)
16p gain	28 (14%)	178	0.0305 (1.00)	0.494 (1.00)	0.699 (1.00)	0.551 (1.00)	0.0681 (1.00)	0.476 (1.00)	0.0931 (1.00)	0.785 (1.00)
16q gain	25 (12%)	181	0.176 (1.00)	0.128 (1.00)	0.463 (1.00)	0.128 (1.00)	0.00707 (1.00)	0.0817 (1.00)	0.00339 (1.00)	0.281 (1.00)
17p gain	15 (7%)	191	0.0143 (1.00)	0.00051 (0.32)	0.834 (1.00)	0.64 (1.00)	0.588 (1.00)	0.491 (1.00)	0.495 (1.00)	1 (1.00)
17q gain	32 (16%)	174	0.0207 (1.00)	0.0232 (1.00)	0.0979 (1.00)	0.253 (1.00)	0.0834 (1.00)	0.279 (1.00)	0.118 (1.00)	0.613 (1.00)
18p gain	27 (13%)	179	0.312 (1.00)	0.153 (1.00)	0.626 (1.00)	0.282 (1.00)	0.932 (1.00)	0.274 (1.00)	0.965 (1.00)	0.139 (1.00)
18q gain	16 (8%)	190	0.29 (1.00)	0.328 (1.00)	0.633 (1.00)	0.342 (1.00)	0.647 (1.00)	0.337 (1.00)	0.804 (1.00)	0.391 (1.00)
19p gain	33 (16%)	173	0.00215 (1.00)	0.115 (1.00)	0.738 (1.00)	0.784 (1.00)	0.0231 (1.00)	0.0602 (1.00)	0.116 (1.00)	0.641 (1.00)
20p gain	71 (34%)	135	0.0174 (1.00)	0.0159 (1.00)	0.182 (1.00)	0.0131 (1.00)	0.244 (1.00)	0.0387 (1.00)	0.0771 (1.00)	0.461 (1.00)
20q gain	77 (37%)	129	0.0388 (1.00)	0.0544 (1.00)	0.237 (1.00)	0.178 (1.00)	0.616 (1.00)	0.0364 (1.00)	0.283 (1.00)	0.492 (1.00)
21q gain	28 (14%)	178	0.724 (1.00)	0.709 (1.00)	0.494 (1.00)	0.771 (1.00)	1 (1.00)	0.78 (1.00)	0.508 (1.00)	0.547 (1.00)
22q gain	25 (12%)	181	0.96 (1.00)	0.238 (1.00)	0.462 (1.00)	0.687 (1.00)	0.927 (1.00)	0.168 (1.00)	1 (1.00)	0.567 (1.00)
xq gain	28 (14%)	178	0.232 (1.00)	0.211 (1.00)	0.352 (1.00)	0.577 (1.00)	0.0498 (1.00)	0.0733 (1.00)	0.0997 (1.00)	0.133 (1.00)
1p loss	8 (4%)	198	0.00213 (1.00)	0.351 (1.00)	0.0474 (1.00)	0.371 (1.00)	0.9 (1.00)	0.468 (1.00)	0.665 (1.00)	0.726 (1.00)
1q loss	7 (3%)	199	0.00059 (0.369)	0.271 (1.00)	0.0262 (1.00)	0.381 (1.00)	0.266 (1.00)	1 (1.00)	0.159 (1.00)	0.737 (1.00)
2p loss	12 (6%)	194	0.863 (1.00)	0.576 (1.00)	0.516 (1.00)	0.831 (1.00)	1 (1.00)	0.339 (1.00)	0.869 (1.00)	0.675 (1.00)
2q loss	21 (10%)	185	0.634 (1.00)	0.265 (1.00)	0.0676 (1.00)	0.399 (1.00)	0.648 (1.00)	0.293 (1.00)	1 (1.00)	0.272 (1.00)
3q loss	8 (4%)	198	0.17 (1.00)	0.0314 (1.00)	0.0483 (1.00)	0.0283 (1.00)	0.898 (1.00)	0.786 (1.00)	0.666 (1.00)	0.401 (1.00)
5p loss	13 (6%)	193	0.157 (1.00)	0.41 (1.00)	1 (1.00)	0.729 (1.00)	0.939 (1.00)	0.622 (1.00)	0.937 (1.00)	0.0307 (1.00)
5q loss	37 (18%)	169	0.0159 (1.00)	0.712 (1.00)	0.797 (1.00)	0.856 (1.00)	0.524 (1.00)	0.248 (1.00)	0.456 (1.00)	0.00172 (1.00)
6p loss	30 (15%)	176	0.212 (1.00)	0.652 (1.00)	0.184 (1.00)	0.403 (1.00)	0.581 (1.00)	0.286 (1.00)	0.545 (1.00)	0.601 (1.00)
6q loss	51 (25%)	155	0.0362 (1.00)	0.336 (1.00)	0.267 (1.00)	0.457 (1.00)	0.65 (1.00)	0.222 (1.00)	0.526 (1.00)	0.799 (1.00)
7p loss	19 (9%)	187	0.605 (1.00)	0.444 (1.00)	0.0365 (1.00)	0.0386 (1.00)	0.54 (1.00)	0.193 (1.00)	0.323 (1.00)	0.0539 (1.00)
7q loss	29 (14%)	177	0.0639 (1.00)	0.106 (1.00)	0.0206 (1.00)	0.102 (1.00)	0.158 (1.00)	0.208 (1.00)	0.265 (1.00)	0.00839 (1.00)
8p loss	58 (28%)	148	0.00824 (1.00)	0.242 (1.00)	0.0588 (1.00)	0.933 (1.00)	0.168 (1.00)	0.201 (1.00)	0.236 (1.00)	0.141 (1.00)
9p loss	38 (18%)	168	0.0199 (1.00)	0.942 (1.00)	0.0846 (1.00)	0.495 (1.00)	0.949 (1.00)	0.938 (1.00)	0.975 (1.00)	0.903 (1.00)
9q loss	34 (17%)	172	0.00954 (1.00)	0.195 (1.00)	0.00296 (1.00)	0.0467 (1.00)	0.483 (1.00)	0.185 (1.00)	0.356 (1.00)	0.263 (1.00)
10p loss	45 (22%)	161	0.00095 (0.593)	0.515 (1.00)	0.537 (1.00)	0.372 (1.00)	0.315 (1.00)	0.776 (1.00)	0.246 (1.00)	0.833 (1.00)
10q loss	50 (24%)	156	0.0012 (0.745)	0.799 (1.00)	0.725 (1.00)	0.37 (1.00)	0.319 (1.00)	0.727 (1.00)	0.264 (1.00)	0.796 (1.00)
11p loss	67 (33%)	139	0.0738 (1.00)	0.285 (1.00)	0.22 (1.00)	0.17 (1.00)	0.202 (1.00)	0.0803 (1.00)	0.123 (1.00)	0.0793 (1.00)
11q loss	79 (38%)	127	0.00217 (1.00)	0.0665 (1.00)	0.454 (1.00)	0.549 (1.00)	0.789 (1.00)	0.263 (1.00)	0.86 (1.00)	0.158 (1.00)
12q loss	9 (4%)	197	0.0579 (1.00)	0.423 (1.00)	0.834 (1.00)	0.584 (1.00)	0.578 (1.00)	0.631 (1.00)	0.913 (1.00)	0.764 (1.00)
13q loss	58 (28%)	148	0.0324 (1.00)	0.114 (1.00)	0.0113 (1.00)	0.0428 (1.00)	0.0302 (1.00)	0.00396 (1.00)	0.0846 (1.00)	0.0873 (1.00)
14q loss	21 (10%)	185	0.00986 (1.00)	0.327 (1.00)	0.0389 (1.00)	0.0125 (1.00)	0.234 (1.00)	0.359 (1.00)	0.0525 (1.00)	0.249 (1.00)
15q loss	27 (13%)	179	0.103 (1.00)	0.344 (1.00)	0.281 (1.00)	0.171 (1.00)	0.535 (1.00)	0.468 (1.00)	0.841 (1.00)	0.584 (1.00)
16p loss	26 (13%)	180	0.226 (1.00)	0.0897 (1.00)	0.176 (1.00)	0.33 (1.00)	0.172 (1.00)	0.0705 (1.00)	0.131 (1.00)	0.73 (1.00)
16q loss	30 (15%)	176	0.665 (1.00)	0.0541 (1.00)	0.0668 (1.00)	0.164 (1.00)	0.127 (1.00)	0.00856 (1.00)	0.0287 (1.00)	0.0602 (1.00)
17p loss	61 (30%)	145	0.00263 (1.00)	0.173 (1.00)	0.215 (1.00)	0.0521 (1.00)	0.104 (1.00)	0.0879 (1.00)	0.0665 (1.00)	0.216 (1.00)
17q loss	19 (9%)	187	0.0253 (1.00)	0.559 (1.00)	0.0243 (1.00)	0.049 (1.00)	0.0561 (1.00)	0.592 (1.00)	0.0586 (1.00)	0.455 (1.00)
18p loss	39 (19%)	167	0.209 (1.00)	0.0837 (1.00)	0.00157 (0.969)	0.145 (1.00)	0.315 (1.00)	0.0318 (1.00)	0.0777 (1.00)	0.0132 (1.00)
19p loss	37 (18%)	169	0.0997 (1.00)	0.0997 (1.00)	0.0423 (1.00)	0.237 (1.00)	0.248 (1.00)	0.342 (1.00)	0.485 (1.00)	0.0959 (1.00)
19q loss	19 (9%)	187	0.0532 (1.00)	0.116 (1.00)	0.908 (1.00)	0.471 (1.00)	0.233 (1.00)	0.347 (1.00)	0.322 (1.00)	0.807 (1.00)
20p loss	14 (7%)	192	0.552 (1.00)	0.582 (1.00)	0.873 (1.00)	0.553 (1.00)	0.645 (1.00)	0.466 (1.00)	0.738 (1.00)	0.204 (1.00)
20q loss	7 (3%)	199	0.0399 (1.00)	0.113 (1.00)	0.874 (1.00)	0.299 (1.00)	0.894 (1.00)	1 (1.00)	1 (1.00)	0.929 (1.00)
21q loss	32 (16%)	174	0.00302 (1.00)	0.155 (1.00)	0.0937 (1.00)	0.00054 (0.339)	0.695 (1.00)	0.572 (1.00)	0.307 (1.00)	0.143 (1.00)
22q loss	47 (23%)	159	0.0526 (1.00)	0.348 (1.00)	0.19 (1.00)	0.0376 (1.00)	0.621 (1.00)	0.397 (1.00)	0.572 (1.00)	0.444 (1.00)
xq loss	40 (19%)	166	0.175 (1.00)	0.103 (1.00)	0.26 (1.00)	0.134 (1.00)	0.0693 (1.00)	0.157 (1.00)	0.0262 (1.00)	0.0141 (1.00)

'2q gain' versus 'CN_CNMF'

P value = 0.00021 (Fisher's exact test), Q value = 0.13

Table S1. Gene #4: '2q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	66	44	96
2Q GAIN MUTATED	10	14	5
2Q GAIN WILD-TYPE	56	30	91

Figure S1. Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #1: 'CN_CNMF'

'3q gain' versus 'METHLYATION_CNMF'

P value = 0.00027 (Fisher's exact test), Q value = 0.17

Table S2. Gene #6: '3q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5	CLUS_6
ALL	51	34	39	38	32	12
3Q GAIN MUTATED	24	22	28	15	27	10
3Q GAIN WILD-TYPE	27	12	11	23	5	2

Figure S2. Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'3q gain' versus 'MRNASEQ_CNMF'

P value = 0.00023 (Fisher's exact test), Q value = 0.15

Table S3. Gene #6: '3q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	86	50	65
3Q GAIN MUTATED	67	23	34
3Q GAIN WILD-TYPE	19	27	31

Figure S3. Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'3q gain' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.00016 (Fisher's exact test), Q value = 0.1

Table S4. Gene #6: '3q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5	CLUS_6	CLUS_7
ALL	25	38	16	32	34	28	33
3Q GAIN MUTATED	12	29	15	10	21	15	24
3Q GAIN WILD-TYPE	13	9	1	22	13	13	9

Figure S4. Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'11q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00033 (Fisher's exact test), Q value = 0.21

Table S5. Gene #22: '11q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	100	27	21	53
11Q GAIN MUTATED	0	0	4	3
11Q GAIN WILD-TYPE	100	27	17	50

Figure S5. Get High-res Image Gene #22: '11q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'19q gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0064

Table S6. Gene #35: '19q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	66	44	96
19Q GAIN MUTATED	10	23	14
19Q GAIN WILD-TYPE	56	21	82

Figure S6. Get High-res Image Gene #35: '19q gain' versus Molecular Subtype #1: 'CN_CNMF'

'3p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00015 (Fisher's exact test), Q value = 0.095

Table S7. Gene #45: '3p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	100	27	21	53
3P LOSS MUTATED	29	12	4	3
3P LOSS WILD-TYPE	71	15	17	50

Figure S7. Get High-res Image Gene #45: '3p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'4p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0064

Table S8. Gene #47: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	66	44	96
4P LOSS MUTATED	32	30	24
4P LOSS WILD-TYPE	34	14	72

Figure S8. Get High-res Image Gene #47: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

'4q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0064

Table S9. Gene #48: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	66	44	96
4Q LOSS MUTATED	20	31	10
4Q LOSS WILD-TYPE	46	13	86

Figure S9. Get High-res Image Gene #48: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

'8q loss' versus 'MRNASEQ_CNMF'

P value = 5e-05 (Fisher's exact test), Q value = 0.032

Table S10. Gene #56: '8q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	86	50	65
8Q LOSS MUTATED	0	7	11
8Q LOSS WILD-TYPE	86	43	54

Figure S10. Get High-res Image Gene #56: '8q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'12p loss' versus 'CN_CNMF'

P value = 0.00015 (Fisher's exact test), Q value = 0.095

Table S11. Gene #63: '12p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	66	44	96
12P LOSS MUTATED	7	14	5
12P LOSS WILD-TYPE	59	30	91

Figure S11. Get High-res Image Gene #63: '12p loss' versus Molecular Subtype #1: 'CN_CNMF'

'18q loss' versus 'MRNASEQ_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0064

Table S12. Gene #73: '18q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	86	50	65
18Q LOSS MUTATED	8	21	23
18Q LOSS WILD-TYPE	78	29	42

Figure S12. Get High-res Image Gene #73: '18q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Molecular subtypes file = CESC-TP.transferedmergedcluster.txt
Number of patients = 206
Number of significantly arm-level cnvs = 80
Number of molecular subtypes = 8
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

Q value calculation

For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References

[1] 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] 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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