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

Skin Cutaneous Melanoma (Metastatic)

15 January 2014 | analyses__2014_01_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/C1C53JBF

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 79 arm-level events and 10 molecular subtypes across 292 patients, 26 significant findings detected with P value < 0.05 and Q value < 0.25.

1q gain cnv correlated to 'CN_CNMF'.
2q gain cnv correlated to 'MIRSEQ_MATURE_CHIERARCHICAL'.
5p gain cnv correlated to 'CN_CNMF'.
6p gain cnv correlated to 'CN_CNMF' and 'MIRSEQ_MATURE_CHIERARCHICAL'.
7p gain cnv correlated to 'CN_CNMF'.
7q gain cnv correlated to 'CN_CNMF'.
8p gain cnv correlated to 'CN_CNMF'.
8q gain cnv correlated to 'CN_CNMF'.
13q gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.
15q gain cnv correlated to 'CN_CNMF'.
16q gain cnv correlated to 'MRNASEQ_CNMF'.
20p gain cnv correlated to 'CN_CNMF'.
20q gain cnv correlated to 'CN_CNMF'.
6q loss cnv correlated to 'CN_CNMF'.
9p loss cnv correlated to 'CN_CNMF'.
10p loss cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.
10q loss cnv correlated to 'CN_CNMF', 'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.
11q loss cnv correlated to 'CN_CNMF'.
14q loss cnv correlated to 'CN_CNMF'.
15q loss cnv correlated to 'CN_CNMF'.
xq loss cnv correlated to 'METHLYATION_CNMF'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 79 arm-level events and 10 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 26 significant findings detected.


		Clinical Features	CN CNMF	METHLYATION CNMF	RPPA CNMF	RPPA CHIERARCHICAL	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	Fisher's exact test	Fisher's exact test
10q loss	181 (62%)	111	1.76e-09 (1.39e-06)	0.0683 (1.00)	0.895 (1.00)	0.128 (1.00)	3.04e-06 (0.00237)	1.62e-05 (0.0126)	0.827 (1.00)	0.13 (1.00)	0.67 (1.00)	0.594 (1.00)
6p gain	117 (40%)	175	2.63e-09 (2.07e-06)	0.00104 (0.781)	0.866 (1.00)	0.0557 (1.00)	0.316 (1.00)	0.0182 (1.00)	0.0178 (1.00)	0.000367 (0.28)	0.0313 (1.00)	0.000126 (0.0969)
13q gain	73 (25%)	219	0.000304 (0.232)	1.12e-06 (0.000875)	0.418 (1.00)	0.701 (1.00)	0.0266 (1.00)	0.0248 (1.00)	0.73 (1.00)	0.333 (1.00)	0.82 (1.00)	0.489 (1.00)
10p loss	164 (56%)	128	3.15e-08 (2.48e-05)	0.0418 (1.00)	0.841 (1.00)	0.367 (1.00)	4.43e-05 (0.0342)	0.000752 (0.569)	0.474 (1.00)	0.0286 (1.00)	0.475 (1.00)	0.316 (1.00)
1q gain	130 (45%)	162	5.62e-07 (0.00044)	0.172 (1.00)	0.226 (1.00)	0.95 (1.00)	0.0215 (1.00)	0.0927 (1.00)	0.12 (1.00)	0.167 (1.00)	0.0251 (1.00)	0.0394 (1.00)
2q gain	55 (19%)	237	0.0062 (1.00)	0.931 (1.00)	0.809 (1.00)	0.185 (1.00)	0.00256 (1.00)	0.00148 (1.00)	0.00163 (1.00)	0.000384 (0.292)	0.00289 (1.00)	5.17e-05 (0.0398)
5p gain	57 (20%)	235	2.16e-05 (0.0167)	0.297 (1.00)	0.919 (1.00)	0.55 (1.00)	0.379 (1.00)	0.781 (1.00)	0.0312 (1.00)	0.277 (1.00)	0.0552 (1.00)	0.244 (1.00)
7p gain	157 (54%)	135	4.73e-06 (0.00368)	0.694 (1.00)	0.482 (1.00)	0.975 (1.00)	0.0272 (1.00)	0.333 (1.00)	0.711 (1.00)	0.175 (1.00)	0.854 (1.00)	0.56 (1.00)
7q gain	155 (53%)	137	3.22e-07 (0.000253)	0.51 (1.00)	0.735 (1.00)	0.973 (1.00)	0.00591 (1.00)	0.1 (1.00)	0.527 (1.00)	0.0448 (1.00)	0.431 (1.00)	0.351 (1.00)
8p gain	93 (32%)	199	0.000194 (0.148)	0.213 (1.00)	0.796 (1.00)	0.695 (1.00)	0.0259 (1.00)	0.0992 (1.00)	0.155 (1.00)	0.643 (1.00)	0.047 (1.00)	0.459 (1.00)
8q gain	134 (46%)	158	1.35e-06 (0.00105)	0.00384 (1.00)	0.478 (1.00)	0.624 (1.00)	0.00318 (1.00)	0.0892 (1.00)	0.117 (1.00)	0.177 (1.00)	0.065 (1.00)	0.148 (1.00)
15q gain	65 (22%)	227	3.03e-06 (0.00237)	0.744 (1.00)	0.791 (1.00)	0.603 (1.00)	0.0885 (1.00)	0.229 (1.00)	0.273 (1.00)	0.0448 (1.00)	0.463 (1.00)	0.321 (1.00)
16q gain	34 (12%)	258	0.00376 (1.00)	0.027 (1.00)	0.282 (1.00)	0.651 (1.00)	5.42e-05 (0.0417)	0.00536 (1.00)	0.0539 (1.00)	0.000668 (0.507)	0.104 (1.00)	0.0657 (1.00)
20p gain	122 (42%)	170	0.00015 (0.115)	0.0227 (1.00)	0.742 (1.00)	0.924 (1.00)	0.000909 (0.685)	0.0106 (1.00)	0.0903 (1.00)	0.00148 (1.00)	0.0558 (1.00)	0.337 (1.00)
20q gain	145 (50%)	147	6.66e-05 (0.0512)	0.0415 (1.00)	0.819 (1.00)	0.858 (1.00)	0.00839 (1.00)	0.17 (1.00)	0.591 (1.00)	0.0105 (1.00)	0.108 (1.00)	0.453 (1.00)
6q loss	145 (50%)	147	0.000228 (0.174)	0.0954 (1.00)	0.927 (1.00)	0.45 (1.00)	0.00535 (1.00)	0.0391 (1.00)	0.398 (1.00)	0.678 (1.00)	0.709 (1.00)	0.319 (1.00)
9p loss	193 (66%)	99	5.01e-07 (0.000393)	0.0418 (1.00)	0.463 (1.00)	0.748 (1.00)	0.02 (1.00)	0.0483 (1.00)	0.577 (1.00)	0.0782 (1.00)	0.795 (1.00)	0.567 (1.00)
11q loss	116 (40%)	176	0.000248 (0.19)	0.237 (1.00)	0.966 (1.00)	0.558 (1.00)	0.108 (1.00)	0.551 (1.00)	0.979 (1.00)	0.217 (1.00)	0.813 (1.00)	0.36 (1.00)
14q loss	92 (32%)	200	8.44e-06 (0.00654)	0.753 (1.00)	0.377 (1.00)	0.737 (1.00)	0.00511 (1.00)	0.136 (1.00)	0.496 (1.00)	0.974 (1.00)	0.225 (1.00)	0.634 (1.00)
15q loss	42 (14%)	250	5.14e-06 (0.00399)	0.188 (1.00)	0.113 (1.00)	0.115 (1.00)	0.461 (1.00)	0.11 (1.00)	0.828 (1.00)	0.32 (1.00)	0.721 (1.00)	0.126 (1.00)
xq loss	73 (25%)	219	0.00184 (1.00)	4.77e-06 (0.00371)	0.198 (1.00)	0.0467 (1.00)	0.00658 (1.00)	0.0102 (1.00)	0.0157 (1.00)	0.57 (1.00)	0.176 (1.00)	0.887 (1.00)
1p gain	65 (22%)	227	0.32 (1.00)	1 (1.00)	0.827 (1.00)	0.348 (1.00)	0.157 (1.00)	0.213 (1.00)	0.879 (1.00)	0.867 (1.00)	0.796 (1.00)	0.716 (1.00)
2p gain	57 (20%)	235	0.0206 (1.00)	0.647 (1.00)	0.461 (1.00)	0.503 (1.00)	0.0331 (1.00)	0.00305 (1.00)	0.0174 (1.00)	0.00329 (1.00)	0.0123 (1.00)	0.000727 (0.551)
3p gain	47 (16%)	245	0.86 (1.00)	0.27 (1.00)	0.037 (1.00)	0.00588 (1.00)	0.363 (1.00)	0.542 (1.00)	0.88 (1.00)	0.031 (1.00)	0.444 (1.00)	0.237 (1.00)
3q gain	57 (20%)	235	0.327 (1.00)	0.639 (1.00)	0.0245 (1.00)	0.0122 (1.00)	0.0343 (1.00)	0.165 (1.00)	0.705 (1.00)	0.0255 (1.00)	0.4 (1.00)	0.676 (1.00)
4p gain	44 (15%)	248	0.00179 (1.00)	0.113 (1.00)	0.205 (1.00)	0.413 (1.00)	0.718 (1.00)	0.159 (1.00)	0.226 (1.00)	0.0293 (1.00)	0.157 (1.00)	0.188 (1.00)
4q gain	37 (13%)	255	0.000629 (0.477)	0.0397 (1.00)	0.242 (1.00)	0.81 (1.00)	0.639 (1.00)	0.109 (1.00)	0.299 (1.00)	0.118 (1.00)	0.363 (1.00)	0.358 (1.00)
5q gain	35 (12%)	257	0.00908 (1.00)	0.282 (1.00)	0.473 (1.00)	0.147 (1.00)	0.941 (1.00)	0.504 (1.00)	0.0139 (1.00)	0.299 (1.00)	0.0287 (1.00)	0.0381 (1.00)
6q gain	38 (13%)	254	0.0518 (1.00)	0.229 (1.00)	0.751 (1.00)	0.312 (1.00)	0.592 (1.00)	0.771 (1.00)	0.242 (1.00)	0.193 (1.00)	0.366 (1.00)	0.0744 (1.00)
9p gain	15 (5%)	277	0.343 (1.00)	0.218 (1.00)	0.347 (1.00)	0.551 (1.00)	0.45 (1.00)	0.839 (1.00)	1 (1.00)	0.721 (1.00)	0.801 (1.00)	0.478 (1.00)
9q gain	20 (7%)	272	0.506 (1.00)	0.832 (1.00)	0.113 (1.00)	0.358 (1.00)	0.517 (1.00)	0.592 (1.00)	0.87 (1.00)	0.766 (1.00)	0.846 (1.00)	0.701 (1.00)
10p gain	9 (3%)	283	0.638 (1.00)	0.693 (1.00)	0.585 (1.00)	0.306 (1.00)	1 (1.00)	0.689 (1.00)	0.435 (1.00)	0.0618 (1.00)	0.604 (1.00)	0.383 (1.00)
11p gain	29 (10%)	263	0.0328 (1.00)	0.485 (1.00)	0.0822 (1.00)	0.0328 (1.00)	0.0113 (1.00)	0.1 (1.00)	0.153 (1.00)	0.0435 (1.00)	0.111 (1.00)	0.181 (1.00)
11q gain	25 (9%)	267	0.00631 (1.00)	0.336 (1.00)	0.076 (1.00)	0.0238 (1.00)	0.0151 (1.00)	0.289 (1.00)	0.127 (1.00)	0.0105 (1.00)	0.107 (1.00)	0.0756 (1.00)
12p gain	48 (16%)	244	0.00301 (1.00)	0.408 (1.00)	0.588 (1.00)	0.127 (1.00)	0.0201 (1.00)	0.031 (1.00)	0.839 (1.00)	0.679 (1.00)	0.813 (1.00)	0.974 (1.00)
12q gain	30 (10%)	262	0.162 (1.00)	0.887 (1.00)	0.596 (1.00)	0.0758 (1.00)	0.341 (1.00)	0.328 (1.00)	0.792 (1.00)	0.816 (1.00)	0.484 (1.00)	0.789 (1.00)
14q gain	31 (11%)	261	0.775 (1.00)	0.323 (1.00)	0.345 (1.00)	0.0181 (1.00)	0.961 (1.00)	0.942 (1.00)	0.2 (1.00)	0.161 (1.00)	0.676 (1.00)	0.947 (1.00)
16p gain	40 (14%)	252	0.0108 (1.00)	0.00802 (1.00)	1 (1.00)	0.861 (1.00)	0.000455 (0.345)	0.0179 (1.00)	0.0334 (1.00)	0.00182 (1.00)	0.0474 (1.00)	0.0755 (1.00)
17p gain	33 (11%)	259	0.00247 (1.00)	0.0114 (1.00)	0.6 (1.00)	0.237 (1.00)	0.236 (1.00)	0.318 (1.00)	0.415 (1.00)	0.283 (1.00)	0.411 (1.00)	0.177 (1.00)
17q gain	58 (20%)	234	0.153 (1.00)	0.114 (1.00)	0.0497 (1.00)	0.016 (1.00)	0.586 (1.00)	0.213 (1.00)	0.375 (1.00)	0.687 (1.00)	0.0653 (1.00)	0.00401 (1.00)
18p gain	47 (16%)	245	0.0286 (1.00)	0.631 (1.00)	0.482 (1.00)	0.337 (1.00)	0.142 (1.00)	0.615 (1.00)	0.763 (1.00)	0.667 (1.00)	0.322 (1.00)	0.621 (1.00)
18q gain	38 (13%)	254	0.0209 (1.00)	0.744 (1.00)	0.351 (1.00)	0.841 (1.00)	0.563 (1.00)	0.839 (1.00)	0.932 (1.00)	0.855 (1.00)	0.298 (1.00)	0.894 (1.00)
19p gain	42 (14%)	250	0.0445 (1.00)	0.113 (1.00)	0.233 (1.00)	0.593 (1.00)	0.00615 (1.00)	0.0045 (1.00)	0.959 (1.00)	0.501 (1.00)	0.913 (1.00)	0.722 (1.00)
19q gain	44 (15%)	248	0.0264 (1.00)	0.0262 (1.00)	0.282 (1.00)	1 (1.00)	0.000841 (0.635)	0.000917 (0.69)	0.486 (1.00)	0.394 (1.00)	0.526 (1.00)	0.755 (1.00)
21q gain	50 (17%)	242	0.49 (1.00)	0.154 (1.00)	0.869 (1.00)	0.747 (1.00)	0.447 (1.00)	0.736 (1.00)	0.319 (1.00)	0.312 (1.00)	0.482 (1.00)	0.861 (1.00)
22q gain	105 (36%)	187	0.0102 (1.00)	0.335 (1.00)	0.946 (1.00)	0.944 (1.00)	0.128 (1.00)	0.214 (1.00)	0.292 (1.00)	0.411 (1.00)	0.51 (1.00)	0.955 (1.00)
xq gain	30 (10%)	262	0.0358 (1.00)	0.0239 (1.00)	0.468 (1.00)	0.908 (1.00)	0.0524 (1.00)	0.131 (1.00)	0.499 (1.00)	0.375 (1.00)	0.816 (1.00)	0.603 (1.00)
1p loss	37 (13%)	255	0.0916 (1.00)	0.0267 (1.00)	0.562 (1.00)	0.0317 (1.00)	0.0517 (1.00)	0.238 (1.00)	0.142 (1.00)	0.0749 (1.00)	0.138 (1.00)	0.525 (1.00)
1q loss	20 (7%)	272	0.00644 (1.00)	0.18 (1.00)	0.969 (1.00)	0.351 (1.00)	0.111 (1.00)	0.467 (1.00)	0.114 (1.00)	0.262 (1.00)	0.245 (1.00)	0.39 (1.00)
2p loss	37 (13%)	255	0.0474 (1.00)	0.285 (1.00)	0.0391 (1.00)	0.00201 (1.00)	0.45 (1.00)	0.126 (1.00)	0.00324 (1.00)	0.00519 (1.00)	0.00799 (1.00)	0.0415 (1.00)
2q loss	37 (13%)	255	0.102 (1.00)	0.0657 (1.00)	0.0103 (1.00)	0.0011 (0.827)	0.178 (1.00)	0.088 (1.00)	0.000995 (0.748)	0.00445 (1.00)	0.00983 (1.00)	0.0302 (1.00)
3p loss	46 (16%)	246	0.889 (1.00)	0.572 (1.00)	0.436 (1.00)	0.658 (1.00)	0.119 (1.00)	0.106 (1.00)	0.259 (1.00)	0.33 (1.00)	0.0774 (1.00)	0.028 (1.00)
3q loss	35 (12%)	257	0.681 (1.00)	0.21 (1.00)	0.335 (1.00)	0.653 (1.00)	0.477 (1.00)	0.544 (1.00)	0.601 (1.00)	0.421 (1.00)	0.346 (1.00)	0.187 (1.00)
4p loss	62 (21%)	230	0.721 (1.00)	0.372 (1.00)	0.378 (1.00)	0.692 (1.00)	0.47 (1.00)	0.119 (1.00)	0.175 (1.00)	0.0346 (1.00)	0.0928 (1.00)	0.153 (1.00)
4q loss	64 (22%)	228	0.456 (1.00)	0.137 (1.00)	0.489 (1.00)	0.447 (1.00)	0.0946 (1.00)	0.00761 (1.00)	0.0175 (1.00)	0.00475 (1.00)	0.0193 (1.00)	0.0181 (1.00)
5p loss	66 (23%)	226	0.631 (1.00)	0.37 (1.00)	0.847 (1.00)	0.913 (1.00)	0.783 (1.00)	0.978 (1.00)	0.636 (1.00)	0.612 (1.00)	0.769 (1.00)	0.881 (1.00)
5q loss	83 (28%)	209	0.934 (1.00)	0.07 (1.00)	0.483 (1.00)	0.655 (1.00)	0.871 (1.00)	0.541 (1.00)	0.873 (1.00)	0.503 (1.00)	0.734 (1.00)	0.505 (1.00)
6p loss	56 (19%)	236	0.00759 (1.00)	0.559 (1.00)	0.913 (1.00)	0.531 (1.00)	0.0115 (1.00)	0.00355 (1.00)	0.121 (1.00)	0.188 (1.00)	0.0393 (1.00)	0.0323 (1.00)
7p loss	14 (5%)	278	1 (1.00)	0.0607 (1.00)	0.0907 (1.00)	0.104 (1.00)	0.527 (1.00)	0.691 (1.00)	0.369 (1.00)	0.382 (1.00)	0.461 (1.00)	0.665 (1.00)
7q loss	14 (5%)	278	0.302 (1.00)	0.00471 (1.00)	0.284 (1.00)	0.892 (1.00)	0.17 (1.00)	0.283 (1.00)	0.321 (1.00)	0.564 (1.00)	0.338 (1.00)	0.738 (1.00)
8p loss	53 (18%)	239	0.201 (1.00)	0.697 (1.00)	0.08 (1.00)	0.209 (1.00)	0.322 (1.00)	0.968 (1.00)	0.411 (1.00)	0.222 (1.00)	0.235 (1.00)	0.696 (1.00)
8q loss	21 (7%)	271	0.88 (1.00)	0.0953 (1.00)	0.297 (1.00)	0.13 (1.00)	0.53 (1.00)	0.732 (1.00)	0.456 (1.00)	0.705 (1.00)	0.26 (1.00)	0.0591 (1.00)
9q loss	150 (51%)	142	0.163 (1.00)	0.0672 (1.00)	0.905 (1.00)	0.0942 (1.00)	0.0894 (1.00)	0.575 (1.00)	0.504 (1.00)	0.571 (1.00)	0.652 (1.00)	0.494 (1.00)
11p loss	102 (35%)	190	0.0291 (1.00)	0.0663 (1.00)	0.485 (1.00)	0.217 (1.00)	0.149 (1.00)	0.343 (1.00)	0.719 (1.00)	0.149 (1.00)	0.362 (1.00)	0.414 (1.00)
12p loss	45 (15%)	247	0.256 (1.00)	0.0636 (1.00)	0.725 (1.00)	0.422 (1.00)	0.0832 (1.00)	0.659 (1.00)	0.912 (1.00)	0.678 (1.00)	0.519 (1.00)	0.631 (1.00)
12q loss	51 (17%)	241	0.142 (1.00)	0.0414 (1.00)	0.84 (1.00)	0.526 (1.00)	0.0897 (1.00)	0.403 (1.00)	0.718 (1.00)	0.429 (1.00)	0.904 (1.00)	0.813 (1.00)
13q loss	63 (22%)	229	0.105 (1.00)	0.00512 (1.00)	0.0794 (1.00)	0.686 (1.00)	0.589 (1.00)	0.0324 (1.00)	0.719 (1.00)	0.38 (1.00)	0.957 (1.00)	0.288 (1.00)
16p loss	58 (20%)	234	0.416 (1.00)	0.156 (1.00)	0.035 (1.00)	0.311 (1.00)	0.0181 (1.00)	0.79 (1.00)	0.136 (1.00)	0.214 (1.00)	0.198 (1.00)	0.307 (1.00)
16q loss	86 (29%)	206	0.663 (1.00)	0.386 (1.00)	0.00697 (1.00)	0.415 (1.00)	0.00704 (1.00)	0.147 (1.00)	0.0749 (1.00)	0.0441 (1.00)	0.147 (1.00)	0.0583 (1.00)
17p loss	98 (34%)	194	0.673 (1.00)	0.335 (1.00)	0.752 (1.00)	0.302 (1.00)	0.231 (1.00)	0.305 (1.00)	0.87 (1.00)	0.422 (1.00)	0.423 (1.00)	0.609 (1.00)
17q loss	47 (16%)	245	0.143 (1.00)	0.864 (1.00)	0.227 (1.00)	0.432 (1.00)	0.932 (1.00)	0.744 (1.00)	0.378 (1.00)	0.733 (1.00)	0.753 (1.00)	0.697 (1.00)
18p loss	84 (29%)	208	0.23 (1.00)	0.651 (1.00)	0.462 (1.00)	0.843 (1.00)	0.0111 (1.00)	0.241 (1.00)	0.978 (1.00)	0.489 (1.00)	0.529 (1.00)	0.693 (1.00)
18q loss	79 (27%)	213	0.583 (1.00)	0.735 (1.00)	0.484 (1.00)	0.779 (1.00)	0.491 (1.00)	0.675 (1.00)	0.735 (1.00)	0.27 (1.00)	0.912 (1.00)	0.674 (1.00)
19p loss	61 (21%)	231	0.0362 (1.00)	0.212 (1.00)	0.782 (1.00)	0.0385 (1.00)	0.0611 (1.00)	0.536 (1.00)	0.368 (1.00)	0.687 (1.00)	0.144 (1.00)	0.42 (1.00)
19q loss	58 (20%)	234	0.0753 (1.00)	0.0783 (1.00)	0.938 (1.00)	0.0256 (1.00)	0.095 (1.00)	0.648 (1.00)	0.593 (1.00)	0.685 (1.00)	0.391 (1.00)	0.371 (1.00)
20p loss	18 (6%)	274	0.468 (1.00)	0.852 (1.00)	0.274 (1.00)	0.22 (1.00)	0.895 (1.00)	0.699 (1.00)	0.125 (1.00)	0.268 (1.00)	0.147 (1.00)	0.204 (1.00)
20q loss	7 (2%)	285	0.3 (1.00)	0.437 (1.00)			0.739 (1.00)	0.0808 (1.00)	0.528 (1.00)	0.898 (1.00)	0.277 (1.00)	0.181 (1.00)
21q loss	58 (20%)	234	0.536 (1.00)	0.389 (1.00)	0.42 (1.00)	0.599 (1.00)	0.503 (1.00)	0.253 (1.00)	0.134 (1.00)	0.082 (1.00)	0.0422 (1.00)	0.305 (1.00)
22q loss	31 (11%)	261	0.496 (1.00)	0.323 (1.00)	0.978 (1.00)	1 (1.00)	0.726 (1.00)	0.865 (1.00)	0.212 (1.00)	0.955 (1.00)	0.942 (1.00)	0.88 (1.00)

'1q gain' versus 'CN_CNMF'

P value = 5.62e-07 (Fisher's exact test), Q value = 0.00044

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

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
1Q GAIN MUTATED	71	27	32
1Q GAIN WILD-TYPE	39	53	70

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

'2q gain' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 5.17e-05 (Fisher's exact test), Q value = 0.04

Table S2. Gene #4: '2q gain' versus Molecular Subtype #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	25	112	86	50
2Q GAIN MUTATED	8	16	28	2
2Q GAIN WILD-TYPE	17	96	58	48

Figure S2. Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

'5p gain' versus 'CN_CNMF'

P value = 2.16e-05 (Fisher's exact test), Q value = 0.017

Table S3. Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
5P GAIN MUTATED	28	23	6
5P GAIN WILD-TYPE	82	57	96

Figure S3. Get High-res Image Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

'6p gain' versus 'CN_CNMF'

P value = 2.63e-09 (Fisher's exact test), Q value = 2.1e-06

Table S4. Gene #11: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
6P GAIN MUTATED	69	17	31
6P GAIN WILD-TYPE	41	63	71

Figure S4. Get High-res Image Gene #11: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

'6p gain' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.000126 (Fisher's exact test), Q value = 0.097

Table S5. Gene #11: '6p gain' versus Molecular Subtype #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	25	112	86	50
6P GAIN MUTATED	11	57	19	26
6P GAIN WILD-TYPE	14	55	67	24

Figure S5. Get High-res Image Gene #11: '6p gain' versus Molecular Subtype #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

'7p gain' versus 'CN_CNMF'

P value = 4.73e-06 (Fisher's exact test), Q value = 0.0037

Table S6. Gene #13: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
7P GAIN MUTATED	60	59	38
7P GAIN WILD-TYPE	50	21	64

Figure S6. Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

'7q gain' versus 'CN_CNMF'

P value = 3.22e-07 (Fisher's exact test), Q value = 0.00025

Table S7. Gene #14: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
7Q GAIN MUTATED	54	62	39
7Q GAIN WILD-TYPE	56	18	63

Figure S7. Get High-res Image Gene #14: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

'8p gain' versus 'CN_CNMF'

P value = 0.000194 (Fisher's exact test), Q value = 0.15

Table S8. Gene #15: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
8P GAIN MUTATED	39	36	18
8P GAIN WILD-TYPE	71	44	84

Figure S8. Get High-res Image Gene #15: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

'8q gain' versus 'CN_CNMF'

P value = 1.35e-06 (Fisher's exact test), Q value = 0.0011

Table S9. Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
8Q GAIN MUTATED	62	46	26
8Q GAIN WILD-TYPE	48	34	76

Figure S9. Get High-res Image Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

'13q gain' versus 'CN_CNMF'

P value = 0.000304 (Fisher's exact test), Q value = 0.23

Table S10. Gene #24: '13q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
13Q GAIN MUTATED	40	20	13
13Q GAIN WILD-TYPE	70	60	89

Figure S10. Get High-res Image Gene #24: '13q gain' versus Molecular Subtype #1: 'CN_CNMF'

'13q gain' versus 'METHLYATION_CNMF'

P value = 1.12e-06 (Fisher's exact test), Q value = 0.00088

Table S11. Gene #24: '13q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	72	108	112
13Q GAIN MUTATED	34	25	14
13Q GAIN WILD-TYPE	38	83	98

Figure S11. Get High-res Image Gene #24: '13q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'15q gain' versus 'CN_CNMF'

P value = 3.03e-06 (Fisher's exact test), Q value = 0.0024

Table S12. Gene #26: '15q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
15Q GAIN MUTATED	13	34	18
15Q GAIN WILD-TYPE	97	46	84

Figure S12. Get High-res Image Gene #26: '15q gain' versus Molecular Subtype #1: 'CN_CNMF'

'16q gain' versus 'MRNASEQ_CNMF'

P value = 5.42e-05 (Fisher's exact test), Q value = 0.042

Table S13. Gene #28: '16q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	94	79	110
16Q GAIN MUTATED	23	6	5
16Q GAIN WILD-TYPE	71	73	105

Figure S13. Get High-res Image Gene #28: '16q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'20p gain' versus 'CN_CNMF'

P value = 0.00015 (Fisher's exact test), Q value = 0.12

Table S14. Gene #35: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
20P GAIN MUTATED	50	45	27
20P GAIN WILD-TYPE	60	35	75

Figure S14. Get High-res Image Gene #35: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

'20q gain' versus 'CN_CNMF'

P value = 6.66e-05 (Fisher's exact test), Q value = 0.051

Table S15. Gene #36: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
20Q GAIN MUTATED	63	49	33
20Q GAIN WILD-TYPE	47	31	69

Figure S15. Get High-res Image Gene #36: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

'6q loss' versus 'CN_CNMF'

P value = 0.000228 (Fisher's exact test), Q value = 0.17

Table S16. Gene #51: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
6Q LOSS MUTATED	59	51	35
6Q LOSS WILD-TYPE	51	29	67

Figure S16. Get High-res Image Gene #51: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'CN_CNMF'

P value = 5.01e-07 (Fisher's exact test), Q value = 0.00039

Table S17. Gene #56: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
9P LOSS MUTATED	74	69	50
9P LOSS WILD-TYPE	36	11	52

Figure S17. Get High-res Image Gene #56: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'CN_CNMF'

P value = 3.15e-08 (Fisher's exact test), Q value = 2.5e-05

Table S18. Gene #58: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
10P LOSS MUTATED	62	64	38
10P LOSS WILD-TYPE	48	16	64

Figure S18. Get High-res Image Gene #58: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'MRNASEQ_CNMF'

P value = 4.43e-05 (Fisher's exact test), Q value = 0.034

Table S19. Gene #58: '10p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	94	79	110
10P LOSS MUTATED	70	35	54
10P LOSS WILD-TYPE	24	44	56

Figure S19. Get High-res Image Gene #58: '10p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'10q loss' versus 'CN_CNMF'

P value = 1.76e-09 (Fisher's exact test), Q value = 1.4e-06

Table S20. Gene #59: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
10Q LOSS MUTATED	67	70	44
10Q LOSS WILD-TYPE	43	10	58

Figure S20. Get High-res Image Gene #59: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

'10q loss' versus 'MRNASEQ_CNMF'

P value = 3.04e-06 (Fisher's exact test), Q value = 0.0024

Table S21. Gene #59: '10q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	94	79	110
10Q LOSS MUTATED	77	41	57
10Q LOSS WILD-TYPE	17	38	53

Figure S21. Get High-res Image Gene #59: '10q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'10q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1.62e-05 (Fisher's exact test), Q value = 0.013

Table S22. Gene #59: '10q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	74	122	87
10Q LOSS MUTATED	62	65	48
10Q LOSS WILD-TYPE	12	57	39

Figure S22. Get High-res Image Gene #59: '10q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'11q loss' versus 'CN_CNMF'

P value = 0.000248 (Fisher's exact test), Q value = 0.19

Table S23. Gene #61: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
11Q LOSS MUTATED	58	32	26
11Q LOSS WILD-TYPE	52	48	76

Figure S23. Get High-res Image Gene #61: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

'14q loss' versus 'CN_CNMF'

P value = 8.44e-06 (Fisher's exact test), Q value = 0.0065

Table S24. Gene #65: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
14Q LOSS MUTATED	33	41	18
14Q LOSS WILD-TYPE	77	39	84

Figure S24. Get High-res Image Gene #65: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

'15q loss' versus 'CN_CNMF'

P value = 5.14e-06 (Fisher's exact test), Q value = 0.004

Table S25. Gene #66: '15q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	110	80	102
15Q LOSS MUTATED	30	3	9
15Q LOSS WILD-TYPE	80	77	93

Figure S25. Get High-res Image Gene #66: '15q loss' versus Molecular Subtype #1: 'CN_CNMF'

'xq loss' versus 'METHLYATION_CNMF'

P value = 4.77e-06 (Fisher's exact test), Q value = 0.0037

Table S26. Gene #79: 'xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	72	108	112
XQ LOSS MUTATED	19	42	12
XQ LOSS WILD-TYPE	53	66	100

Figure S26. Get High-res Image Gene #79: 'xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Molecular subtypes file = SKCM-TM.transferedmergedcluster.txt
Number of patients = 292
Number of significantly arm-level cnvs = 79
Number of molecular subtypes = 10
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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