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

Skin Cutaneous Melanoma (Metastatic)

16 April 2014 | analyses__2014_04_16

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/C13F4N9W

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 299 patients, 28 significant findings detected with P value < 0.05 and Q value < 0.25.

1q gain cnv correlated to 'CN_CNMF'.
2p gain cnv correlated to 'MIRSEQ_CHIERARCHICAL'.
2q gain cnv correlated to 'CN_CNMF', 'MIRSEQ_CHIERARCHICAL', and 'MIRSEQ_MATURE_CHIERARCHICAL'.
6p gain cnv correlated to 'CN_CNMF'.
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'.
16p gain cnv correlated to 'MRNASEQ_CNMF'.
16q gain cnv correlated to 'MRNASEQ_CNMF'.
20p gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.
20q gain cnv correlated to 'CN_CNMF'.
6q loss cnv correlated to 'CN_CNMF'.
10p loss cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.
10q loss cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.
11p loss cnv correlated to 'CN_CNMF'.
11q loss cnv correlated to 'CN_CNMF'.
13q loss cnv correlated to 'CN_CNMF'.
14q 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, 28 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
2q gain	56 (19%)	243	1.49e-05 (0.0115)	1 (1.00)	0.748 (1.00)	0.263 (1.00)	0.00131 (0.973)	0.0013 (0.967)	0.00129 (0.964)	1.25e-05 (0.00964)	0.00121 (0.91)	0.000127 (0.0966)
13q gain	75 (25%)	224	4.6e-09 (3.61e-06)	7.73e-06 (0.00597)	0.503 (1.00)	0.436 (1.00)	0.00133 (0.985)	0.00132 (0.979)	0.669 (1.00)	0.966 (1.00)	0.603 (1.00)	0.972 (1.00)
20p gain	124 (41%)	175	5.67e-07 (0.000442)	0.0104 (1.00)	0.838 (1.00)	0.816 (1.00)	6e-05 (0.0459)	0.00337 (1.00)	0.136 (1.00)	0.179 (1.00)	0.0908 (1.00)	0.392 (1.00)
10p loss	167 (56%)	132	1.13e-09 (8.89e-07)	0.0154 (1.00)	0.894 (1.00)	0.344 (1.00)	4.36e-05 (0.0334)	0.00427 (1.00)	0.543 (1.00)	0.841 (1.00)	0.685 (1.00)	0.289 (1.00)
10q loss	185 (62%)	114	1.77e-09 (1.39e-06)	0.019 (1.00)	0.903 (1.00)	0.207 (1.00)	1.24e-05 (0.00956)	0.000459 (0.347)	0.959 (1.00)	0.917 (1.00)	0.825 (1.00)	0.602 (1.00)
1q gain	136 (45%)	163	1.34e-17 (1.06e-14)	0.297 (1.00)	0.283 (1.00)	0.772 (1.00)	0.00978 (1.00)	0.0645 (1.00)	0.273 (1.00)	0.116 (1.00)	0.047 (1.00)	0.0551 (1.00)
2p gain	58 (19%)	241	0.000424 (0.322)	0.618 (1.00)	0.625 (1.00)	0.894 (1.00)	0.0191 (1.00)	0.000421 (0.32)	0.0138 (1.00)	0.000188 (0.143)	0.0156 (1.00)	0.000774 (0.582)
6p gain	117 (39%)	182	6.47e-08 (5.07e-05)	0.00138 (1.00)	0.839 (1.00)	0.194 (1.00)	0.666 (1.00)	0.2 (1.00)	0.0166 (1.00)	0.000446 (0.338)	0.0687 (1.00)	0.000479 (0.362)
7p gain	161 (54%)	138	7.19e-06 (0.00557)	0.913 (1.00)	0.455 (1.00)	0.654 (1.00)	0.0739 (1.00)	0.424 (1.00)	0.62 (1.00)	0.664 (1.00)	0.774 (1.00)	0.846 (1.00)
7q gain	159 (53%)	140	1.61e-06 (0.00125)	0.799 (1.00)	0.689 (1.00)	0.794 (1.00)	0.0172 (1.00)	0.0891 (1.00)	0.467 (1.00)	0.158 (1.00)	0.66 (1.00)	0.449 (1.00)
8p gain	99 (33%)	200	2.32e-05 (0.0179)	0.0657 (1.00)	0.615 (1.00)	0.796 (1.00)	0.00616 (1.00)	0.236 (1.00)	0.164 (1.00)	0.76 (1.00)	0.0691 (1.00)	0.15 (1.00)
8q gain	141 (47%)	158	1.5e-06 (0.00117)	0.00114 (0.858)	0.64 (1.00)	0.687 (1.00)	0.00158 (1.00)	0.205 (1.00)	0.143 (1.00)	0.732 (1.00)	0.104 (1.00)	0.0814 (1.00)
15q gain	69 (23%)	230	3.2e-06 (0.00248)	0.384 (1.00)	0.824 (1.00)	0.912 (1.00)	0.0684 (1.00)	0.0454 (1.00)	0.228 (1.00)	0.0605 (1.00)	0.221 (1.00)	0.0719 (1.00)
16p gain	41 (14%)	258	0.0914 (1.00)	0.00951 (1.00)	1 (1.00)	0.88 (1.00)	0.000102 (0.0779)	0.00541 (1.00)	0.0373 (1.00)	0.178 (1.00)	0.0282 (1.00)	0.0793 (1.00)
16q gain	35 (12%)	264	0.279 (1.00)	0.0269 (1.00)	0.264 (1.00)	0.711 (1.00)	0.000138 (0.105)	0.00126 (0.944)	0.0579 (1.00)	0.116 (1.00)	0.0765 (1.00)	0.0694 (1.00)
20q gain	147 (49%)	152	8.73e-07 (0.00068)	0.0545 (1.00)	0.933 (1.00)	0.967 (1.00)	0.00116 (0.873)	0.0265 (1.00)	0.756 (1.00)	0.273 (1.00)	0.129 (1.00)	0.462 (1.00)
6q loss	146 (49%)	153	3.14e-07 (0.000246)	0.06 (1.00)	0.991 (1.00)	0.219 (1.00)	0.00426 (1.00)	0.191 (1.00)	0.421 (1.00)	0.511 (1.00)	0.886 (1.00)	0.189 (1.00)
11p loss	102 (34%)	197	3.49e-06 (0.0027)	0.0388 (1.00)	0.575 (1.00)	0.591 (1.00)	0.13 (1.00)	0.608 (1.00)	0.424 (1.00)	0.32 (1.00)	0.209 (1.00)	0.21 (1.00)
11q loss	117 (39%)	182	7.85e-08 (6.14e-05)	0.16 (1.00)	0.955 (1.00)	0.623 (1.00)	0.0689 (1.00)	0.511 (1.00)	0.716 (1.00)	0.336 (1.00)	0.893 (1.00)	0.238 (1.00)
13q loss	65 (22%)	234	7.51e-06 (0.0058)	0.0129 (1.00)	0.0399 (1.00)	0.523 (1.00)	0.789 (1.00)	0.148 (1.00)	0.574 (1.00)	0.142 (1.00)	0.623 (1.00)	0.194 (1.00)
14q loss	93 (31%)	206	1.1e-07 (8.57e-05)	0.78 (1.00)	0.408 (1.00)	0.417 (1.00)	0.00214 (1.00)	0.503 (1.00)	0.599 (1.00)	0.963 (1.00)	0.546 (1.00)	0.834 (1.00)
xq loss	74 (25%)	225	0.0241 (1.00)	2.38e-05 (0.0182)	0.301 (1.00)	0.397 (1.00)	0.00224 (1.00)	0.0398 (1.00)	0.00906 (1.00)	0.466 (1.00)	0.101 (1.00)	0.839 (1.00)
1p gain	70 (23%)	229	0.096 (1.00)	0.772 (1.00)	0.894 (1.00)	0.67 (1.00)	0.168 (1.00)	0.282 (1.00)	0.711 (1.00)	0.596 (1.00)	0.872 (1.00)	0.781 (1.00)
3p gain	48 (16%)	251	0.654 (1.00)	0.227 (1.00)	0.0406 (1.00)	0.0497 (1.00)	0.297 (1.00)	0.385 (1.00)	0.974 (1.00)	0.698 (1.00)	0.917 (1.00)	0.373 (1.00)
3q gain	58 (19%)	241	0.272 (1.00)	0.567 (1.00)	0.0195 (1.00)	0.0486 (1.00)	0.0289 (1.00)	0.163 (1.00)	0.857 (1.00)	0.639 (1.00)	0.763 (1.00)	0.764 (1.00)
4p gain	44 (15%)	255	0.0105 (1.00)	0.152 (1.00)	0.305 (1.00)	0.214 (1.00)	0.692 (1.00)	0.889 (1.00)	0.21 (1.00)	0.08 (1.00)	0.0943 (1.00)	0.127 (1.00)
4q gain	37 (12%)	262	0.0201 (1.00)	0.0867 (1.00)	0.261 (1.00)	0.416 (1.00)	0.612 (1.00)	0.676 (1.00)	0.28 (1.00)	0.189 (1.00)	0.218 (1.00)	0.451 (1.00)
5p gain	58 (19%)	241	0.0133 (1.00)	0.222 (1.00)	0.886 (1.00)	0.772 (1.00)	0.17 (1.00)	0.594 (1.00)	0.054 (1.00)	0.286 (1.00)	0.135 (1.00)	0.217 (1.00)
5q gain	36 (12%)	263	0.0514 (1.00)	0.178 (1.00)	0.404 (1.00)	0.462 (1.00)	0.782 (1.00)	0.499 (1.00)	0.0298 (1.00)	0.256 (1.00)	0.111 (1.00)	0.046 (1.00)
6q gain	39 (13%)	260	0.0223 (1.00)	0.119 (1.00)	0.899 (1.00)	0.437 (1.00)	1 (1.00)	0.907 (1.00)	0.161 (1.00)	0.0895 (1.00)	0.47 (1.00)	0.161 (1.00)
9p gain	15 (5%)	284	0.345 (1.00)	0.28 (1.00)	0.375 (1.00)	0.768 (1.00)	0.451 (1.00)	0.7 (1.00)	1 (1.00)	0.308 (1.00)	0.737 (1.00)	0.35 (1.00)
9q gain	20 (7%)	279	0.181 (1.00)	0.686 (1.00)	0.135 (1.00)	0.509 (1.00)	0.57 (1.00)	0.924 (1.00)	0.875 (1.00)	0.566 (1.00)	0.699 (1.00)	0.626 (1.00)
10p gain	10 (3%)	289	0.889 (1.00)	1 (1.00)	0.866 (1.00)	0.846 (1.00)	0.662 (1.00)	0.701 (1.00)	0.836 (1.00)	0.78 (1.00)	1 (1.00)	0.5 (1.00)
11p gain	30 (10%)	269	0.0138 (1.00)	0.603 (1.00)	0.0865 (1.00)	0.0314 (1.00)	0.00465 (1.00)	0.313 (1.00)	0.0986 (1.00)	0.017 (1.00)	0.12 (1.00)	0.0929 (1.00)
11q gain	26 (9%)	273	0.000681 (0.514)	0.415 (1.00)	0.0758 (1.00)	0.00409 (1.00)	0.01 (1.00)	0.287 (1.00)	0.138 (1.00)	0.00981 (1.00)	0.121 (1.00)	0.0609 (1.00)
12p gain	50 (17%)	249	0.00474 (1.00)	0.323 (1.00)	0.367 (1.00)	0.335 (1.00)	0.0243 (1.00)	0.0642 (1.00)	0.925 (1.00)	0.6 (1.00)	0.744 (1.00)	0.851 (1.00)
12q gain	33 (11%)	266	0.065 (1.00)	0.693 (1.00)	0.602 (1.00)	0.0502 (1.00)	0.55 (1.00)	0.725 (1.00)	0.893 (1.00)	0.522 (1.00)	0.766 (1.00)	0.743 (1.00)
14q gain	32 (11%)	267	0.316 (1.00)	0.255 (1.00)	0.497 (1.00)	0.104 (1.00)	0.878 (1.00)	0.313 (1.00)	0.0534 (1.00)	0.628 (1.00)	0.794 (1.00)	0.932 (1.00)
17p gain	34 (11%)	265	0.00764 (1.00)	0.00456 (1.00)	0.595 (1.00)	0.618 (1.00)	0.385 (1.00)	0.206 (1.00)	0.401 (1.00)	0.123 (1.00)	0.737 (1.00)	0.183 (1.00)
17q gain	59 (20%)	240	0.0633 (1.00)	0.0752 (1.00)	0.0808 (1.00)	0.0713 (1.00)	0.62 (1.00)	0.088 (1.00)	0.153 (1.00)	0.373 (1.00)	0.0961 (1.00)	0.0125 (1.00)
18p gain	48 (16%)	251	0.0441 (1.00)	0.981 (1.00)	0.208 (1.00)	0.51 (1.00)	0.125 (1.00)	0.912 (1.00)	0.514 (1.00)	0.396 (1.00)	0.368 (1.00)	0.509 (1.00)
18q gain	39 (13%)	260	0.0236 (1.00)	1 (1.00)	0.397 (1.00)	0.793 (1.00)	0.348 (1.00)	0.921 (1.00)	0.74 (1.00)	0.793 (1.00)	0.371 (1.00)	0.669 (1.00)
19p gain	43 (14%)	256	0.257 (1.00)	0.0491 (1.00)	0.255 (1.00)	0.477 (1.00)	0.00555 (1.00)	0.0017 (1.00)	0.878 (1.00)	0.405 (1.00)	0.713 (1.00)	0.643 (1.00)
19q gain	44 (15%)	255	0.13 (1.00)	0.0238 (1.00)	0.298 (1.00)	0.894 (1.00)	0.000731 (0.55)	0.000618 (0.466)	0.622 (1.00)	0.321 (1.00)	0.502 (1.00)	0.696 (1.00)
21q gain	54 (18%)	245	0.424 (1.00)	0.0764 (1.00)	0.876 (1.00)	0.781 (1.00)	0.38 (1.00)	0.393 (1.00)	0.374 (1.00)	1 (1.00)	0.43 (1.00)	0.852 (1.00)
22q gain	107 (36%)	192	0.00517 (1.00)	0.396 (1.00)	0.903 (1.00)	0.726 (1.00)	0.0956 (1.00)	0.141 (1.00)	0.324 (1.00)	0.872 (1.00)	0.27 (1.00)	0.857 (1.00)
xq gain	32 (11%)	267	0.00804 (1.00)	0.0267 (1.00)	0.67 (1.00)	0.787 (1.00)	0.116 (1.00)	0.138 (1.00)	0.709 (1.00)	0.734 (1.00)	0.877 (1.00)	0.476 (1.00)
1p loss	36 (12%)	263	0.252 (1.00)	0.0059 (1.00)	0.376 (1.00)	0.0361 (1.00)	0.0531 (1.00)	0.455 (1.00)	0.153 (1.00)	0.451 (1.00)	0.269 (1.00)	0.278 (1.00)
1q loss	20 (7%)	279	0.107 (1.00)	0.191 (1.00)	0.969 (1.00)	0.448 (1.00)	0.241 (1.00)	1 (1.00)	0.113 (1.00)	0.244 (1.00)	0.164 (1.00)	0.273 (1.00)
2p loss	38 (13%)	261	0.198 (1.00)	0.35 (1.00)	0.0495 (1.00)	0.00692 (1.00)	0.548 (1.00)	0.0911 (1.00)	0.00428 (1.00)	0.034 (1.00)	0.00546 (1.00)	0.125 (1.00)
2q loss	39 (13%)	260	0.0359 (1.00)	0.0852 (1.00)	0.0129 (1.00)	0.00412 (1.00)	0.157 (1.00)	0.17 (1.00)	0.00347 (1.00)	0.0526 (1.00)	0.00659 (1.00)	0.171 (1.00)
3p loss	48 (16%)	251	0.274 (1.00)	0.421 (1.00)	0.486 (1.00)	0.681 (1.00)	0.065 (1.00)	0.0808 (1.00)	0.285 (1.00)	0.379 (1.00)	0.0542 (1.00)	0.0257 (1.00)
3q loss	37 (12%)	262	0.308 (1.00)	0.218 (1.00)	0.38 (1.00)	0.538 (1.00)	0.33 (1.00)	0.36 (1.00)	0.594 (1.00)	0.665 (1.00)	0.361 (1.00)	0.44 (1.00)
4p loss	64 (21%)	235	0.777 (1.00)	0.217 (1.00)	0.352 (1.00)	0.864 (1.00)	0.554 (1.00)	0.145 (1.00)	0.114 (1.00)	0.019 (1.00)	0.0379 (1.00)	0.0752 (1.00)
4q loss	66 (22%)	233	0.404 (1.00)	0.0588 (1.00)	0.481 (1.00)	0.723 (1.00)	0.229 (1.00)	0.0195 (1.00)	0.0134 (1.00)	0.00321 (1.00)	0.00664 (1.00)	0.0201 (1.00)
5p loss	66 (22%)	233	0.215 (1.00)	0.204 (1.00)	0.78 (1.00)	0.858 (1.00)	0.791 (1.00)	0.979 (1.00)	0.746 (1.00)	0.85 (1.00)	0.932 (1.00)	0.449 (1.00)
5q loss	84 (28%)	215	0.0169 (1.00)	0.0141 (1.00)	0.443 (1.00)	0.856 (1.00)	0.614 (1.00)	0.473 (1.00)	0.976 (1.00)	0.79 (1.00)	0.797 (1.00)	0.17 (1.00)
6p loss	56 (19%)	243	0.00217 (1.00)	0.783 (1.00)	0.89 (1.00)	0.361 (1.00)	0.00891 (1.00)	0.197 (1.00)	0.144 (1.00)	0.036 (1.00)	0.129 (1.00)	0.0504 (1.00)
7p loss	16 (5%)	283	0.799 (1.00)	0.139 (1.00)	0.0948 (1.00)	0.194 (1.00)	0.888 (1.00)	0.33 (1.00)	0.537 (1.00)	0.413 (1.00)	0.69 (1.00)	0.869 (1.00)
7q loss	15 (5%)	284	0.776 (1.00)	0.0602 (1.00)	0.338 (1.00)	0.607 (1.00)	0.311 (1.00)	0.605 (1.00)	0.407 (1.00)	0.921 (1.00)	0.574 (1.00)	0.933 (1.00)
8p loss	53 (18%)	246	0.698 (1.00)	0.94 (1.00)	0.0872 (1.00)	0.45 (1.00)	0.406 (1.00)	0.912 (1.00)	0.53 (1.00)	0.217 (1.00)	0.409 (1.00)	0.519 (1.00)
8q loss	21 (7%)	278	0.367 (1.00)	0.139 (1.00)	0.312 (1.00)	0.201 (1.00)	0.602 (1.00)	0.353 (1.00)	0.403 (1.00)	0.723 (1.00)	0.241 (1.00)	0.377 (1.00)
9p loss	197 (66%)	102	0.0298 (1.00)	0.0612 (1.00)	0.636 (1.00)	0.858 (1.00)	0.00154 (1.00)	0.1 (1.00)	0.688 (1.00)	0.289 (1.00)	0.625 (1.00)	0.638 (1.00)
9q loss	154 (52%)	145	0.853 (1.00)	0.0974 (1.00)	0.967 (1.00)	0.458 (1.00)	0.0437 (1.00)	0.277 (1.00)	0.298 (1.00)	0.564 (1.00)	0.828 (1.00)	0.563 (1.00)
12p loss	46 (15%)	253	0.0149 (1.00)	0.121 (1.00)	0.747 (1.00)	0.145 (1.00)	0.0385 (1.00)	0.822 (1.00)	0.824 (1.00)	0.872 (1.00)	0.586 (1.00)	0.762 (1.00)
12q loss	52 (17%)	247	0.0046 (1.00)	0.0982 (1.00)	0.988 (1.00)	0.37 (1.00)	0.0499 (1.00)	0.855 (1.00)	0.587 (1.00)	0.547 (1.00)	0.928 (1.00)	0.738 (1.00)
15q loss	42 (14%)	257	0.002 (1.00)	0.248 (1.00)	0.13 (1.00)	0.132 (1.00)	0.174 (1.00)	0.195 (1.00)	0.73 (1.00)	0.679 (1.00)	0.48 (1.00)	0.208 (1.00)
16p loss	58 (19%)	241	0.112 (1.00)	0.116 (1.00)	0.0473 (1.00)	0.511 (1.00)	0.0219 (1.00)	0.17 (1.00)	0.124 (1.00)	0.255 (1.00)	0.262 (1.00)	0.305 (1.00)
16q loss	87 (29%)	212	0.0535 (1.00)	0.287 (1.00)	0.0114 (1.00)	0.807 (1.00)	0.026 (1.00)	0.0537 (1.00)	0.08 (1.00)	0.0856 (1.00)	0.228 (1.00)	0.0607 (1.00)
17p loss	101 (34%)	198	0.708 (1.00)	0.124 (1.00)	0.749 (1.00)	0.199 (1.00)	0.246 (1.00)	0.241 (1.00)	0.975 (1.00)	0.377 (1.00)	0.666 (1.00)	0.551 (1.00)
17q loss	50 (17%)	249	0.61 (1.00)	0.421 (1.00)	0.175 (1.00)	0.0539 (1.00)	0.938 (1.00)	0.835 (1.00)	0.207 (1.00)	0.498 (1.00)	0.641 (1.00)	0.184 (1.00)
18p loss	86 (29%)	213	0.305 (1.00)	0.476 (1.00)	0.371 (1.00)	0.752 (1.00)	0.0136 (1.00)	0.339 (1.00)	1 (1.00)	0.468 (1.00)	0.66 (1.00)	0.331 (1.00)
18q loss	82 (27%)	217	0.0872 (1.00)	0.603 (1.00)	0.396 (1.00)	0.75 (1.00)	0.425 (1.00)	0.785 (1.00)	0.782 (1.00)	0.482 (1.00)	0.903 (1.00)	0.515 (1.00)
19p loss	62 (21%)	237	0.00433 (1.00)	0.204 (1.00)	0.759 (1.00)	0.186 (1.00)	0.0569 (1.00)	0.94 (1.00)	0.32 (1.00)	0.57 (1.00)	0.287 (1.00)	0.664 (1.00)
19q loss	60 (20%)	239	0.00681 (1.00)	0.0785 (1.00)	0.967 (1.00)	0.0789 (1.00)	0.124 (1.00)	0.548 (1.00)	0.533 (1.00)	0.522 (1.00)	0.622 (1.00)	0.554 (1.00)
20p loss	18 (6%)	281	0.455 (1.00)	0.807 (1.00)	0.236 (1.00)	0.403 (1.00)	0.58 (1.00)	0.219 (1.00)	0.131 (1.00)	0.572 (1.00)	0.246 (1.00)	0.33 (1.00)
20q loss	7 (2%)	292	0.498 (1.00)	0.346 (1.00)			0.136 (1.00)	0.00314 (1.00)	0.529 (1.00)	0.797 (1.00)	0.333 (1.00)	0.582 (1.00)
21q loss	58 (19%)	241	0.148 (1.00)	0.429 (1.00)	0.47 (1.00)	0.632 (1.00)	0.492 (1.00)	0.185 (1.00)	0.167 (1.00)	0.368 (1.00)	0.104 (1.00)	0.267 (1.00)
22q loss	32 (11%)	267	0.183 (1.00)	0.245 (1.00)	0.954 (1.00)	0.915 (1.00)	0.807 (1.00)	0.725 (1.00)	0.482 (1.00)	0.843 (1.00)	0.769 (1.00)	0.746 (1.00)

'1q gain' versus 'CN_CNMF'

P value = 1.34e-17 (Fisher's exact test), Q value = 1.1e-14

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

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
1Q GAIN MUTATED	68	10	30	28
1Q GAIN WILD-TYPE	17	47	21	78

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

'2p gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000188 (Fisher's exact test), Q value = 0.14

Table S2. Gene #3: '2p gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	27	164	88
2P GAIN MUTATED	9	20	28
2P GAIN WILD-TYPE	18	144	60

Figure S2. Get High-res Image Gene #3: '2p gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

'2q gain' versus 'CN_CNMF'

P value = 1.49e-05 (Fisher's exact test), Q value = 0.011

Table S3. Gene #4: '2q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
2Q GAIN MUTATED	13	9	23	11
2Q GAIN WILD-TYPE	72	48	28	95

Figure S3. Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #1: 'CN_CNMF'

'2q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1.25e-05 (Fisher's exact test), Q value = 0.0096

Table S4. Gene #4: '2q gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	27	164	88
2Q GAIN MUTATED	9	17	29
2Q GAIN WILD-TYPE	18	147	59

Figure S4. Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

'2q gain' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.000127 (Fisher's exact test), Q value = 0.097

Table S5. Gene #4: '2q gain' versus Molecular Subtype #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	25	85	47	122
2Q GAIN MUTATED	8	28	3	16
2Q GAIN WILD-TYPE	17	57	44	106

Figure S5. Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

'6p gain' versus 'CN_CNMF'

P value = 6.47e-08 (Fisher's exact test), Q value = 5.1e-05

Table S6. Gene #11: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
6P GAIN MUTATED	49	29	6	33
6P GAIN WILD-TYPE	36	28	45	73

Figure S6. Get High-res Image Gene #11: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

'7p gain' versus 'CN_CNMF'

P value = 7.19e-06 (Fisher's exact test), Q value = 0.0056

Table S7. Gene #13: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
7P GAIN MUTATED	44	35	41	41
7P GAIN WILD-TYPE	41	22	10	65

Figure S7. Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

'7q gain' versus 'CN_CNMF'

P value = 1.61e-06 (Fisher's exact test), Q value = 0.0012

Table S8. Gene #14: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
7Q GAIN MUTATED	39	33	43	44
7Q GAIN WILD-TYPE	46	24	8	62

Figure S8. Get High-res Image Gene #14: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

'8p gain' versus 'CN_CNMF'

P value = 2.32e-05 (Fisher's exact test), Q value = 0.018

Table S9. Gene #15: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
8P GAIN MUTATED	27	29	24	19
8P GAIN WILD-TYPE	58	28	27	87

Figure S9. Get High-res Image Gene #15: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

'8q gain' versus 'CN_CNMF'

P value = 1.5e-06 (Fisher's exact test), Q value = 0.0012

Table S10. Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
8Q GAIN MUTATED	49	36	28	28
8Q GAIN WILD-TYPE	36	21	23	78

Figure S10. Get High-res Image Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

'13q gain' versus 'CN_CNMF'

P value = 4.6e-09 (Fisher's exact test), Q value = 3.6e-06

Table S11. Gene #24: '13q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
13Q GAIN MUTATED	26	31	7	11
13Q GAIN WILD-TYPE	59	26	44	95

Figure S11. Get High-res Image Gene #24: '13q gain' versus Molecular Subtype #1: 'CN_CNMF'

'13q gain' versus 'METHLYATION_CNMF'

P value = 7.73e-06 (Fisher's exact test), Q value = 0.006

Table S12. Gene #24: '13q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	78	104	109
13Q GAIN MUTATED	35	22	15
13Q GAIN WILD-TYPE	43	82	94

Figure S12. Get High-res Image Gene #24: '13q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'15q gain' versus 'CN_CNMF'

P value = 3.2e-06 (Fisher's exact test), Q value = 0.0025

Table S13. Gene #26: '15q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
15Q GAIN MUTATED	11	11	27	20
15Q GAIN WILD-TYPE	74	46	24	86

Figure S13. Get High-res Image Gene #26: '15q gain' versus Molecular Subtype #1: 'CN_CNMF'

'16p gain' versus 'MRNASEQ_CNMF'

P value = 0.000102 (Fisher's exact test), Q value = 0.078

Table S14. Gene #27: '16p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	101	81	109
16P GAIN MUTATED	25	10	5
16P GAIN WILD-TYPE	76	71	104

Figure S14. Get High-res Image Gene #27: '16p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'16q gain' versus 'MRNASEQ_CNMF'

P value = 0.000138 (Fisher's exact test), Q value = 0.11

Table S15. Gene #28: '16q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	101	81	109
16Q GAIN MUTATED	23	6	5
16Q GAIN WILD-TYPE	78	75	104

Figure S15. Get High-res Image Gene #28: '16q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'20p gain' versus 'CN_CNMF'

P value = 5.67e-07 (Fisher's exact test), Q value = 0.00044

Table S16. Gene #35: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
20P GAIN MUTATED	38	31	32	23
20P GAIN WILD-TYPE	47	26	19	83

Figure S16. Get High-res Image Gene #35: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

'20p gain' versus 'MRNASEQ_CNMF'

P value = 6e-05 (Fisher's exact test), Q value = 0.046

Table S17. Gene #35: '20p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	101	81	109
20P GAIN MUTATED	60	25	37
20P GAIN WILD-TYPE	41	56	72

Figure S17. Get High-res Image Gene #35: '20p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'20q gain' versus 'CN_CNMF'

P value = 8.73e-07 (Fisher's exact test), Q value = 0.00068

Table S18. Gene #36: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
20Q GAIN MUTATED	49	33	35	30
20Q GAIN WILD-TYPE	36	24	16	76

Figure S18. Get High-res Image Gene #36: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

'6q loss' versus 'CN_CNMF'

P value = 3.14e-07 (Fisher's exact test), Q value = 0.00025

Table S19. Gene #51: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
6Q LOSS MUTATED	42	36	37	31
6Q LOSS WILD-TYPE	43	21	14	75

Figure S19. Get High-res Image Gene #51: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'CN_CNMF'

P value = 1.13e-09 (Fisher's exact test), Q value = 8.9e-07

Table S20. Gene #58: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
10P LOSS MUTATED	49	38	44	36
10P LOSS WILD-TYPE	36	19	7	70

Figure S20. Get High-res Image Gene #58: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'MRNASEQ_CNMF'

P value = 4.36e-05 (Fisher's exact test), Q value = 0.033

Table S21. Gene #58: '10p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	101	81	109
10P LOSS MUTATED	74	34	56
10P LOSS WILD-TYPE	27	47	53

Figure S21. Get High-res Image Gene #58: '10p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'10q loss' versus 'CN_CNMF'

P value = 1.77e-09 (Fisher's exact test), Q value = 1.4e-06

Table S22. Gene #59: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
10Q LOSS MUTATED	51	42	47	45
10Q LOSS WILD-TYPE	34	15	4	61

Figure S22. Get High-res Image Gene #59: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

'10q loss' versus 'MRNASEQ_CNMF'

P value = 1.24e-05 (Fisher's exact test), Q value = 0.0096

Table S23. Gene #59: '10q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	101	81	109
10Q LOSS MUTATED	81	41	59
10Q LOSS WILD-TYPE	20	40	50

Figure S23. Get High-res Image Gene #59: '10q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'11p loss' versus 'CN_CNMF'

P value = 3.49e-06 (Fisher's exact test), Q value = 0.0027

Table S24. Gene #60: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
11P LOSS MUTATED	43	12	25	22
11P LOSS WILD-TYPE	42	45	26	84

Figure S24. Get High-res Image Gene #60: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

'11q loss' versus 'CN_CNMF'

P value = 7.85e-08 (Fisher's exact test), Q value = 6.1e-05

Table S25. Gene #61: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
11Q LOSS MUTATED	51	15	27	24
11Q LOSS WILD-TYPE	34	42	24	82

Figure S25. Get High-res Image Gene #61: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

'13q loss' versus 'CN_CNMF'

P value = 7.51e-06 (Fisher's exact test), Q value = 0.0058

Table S26. Gene #64: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
13Q LOSS MUTATED	17	5	25	18
13Q LOSS WILD-TYPE	68	52	26	88

Figure S26. Get High-res Image Gene #64: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

'14q loss' versus 'CN_CNMF'

P value = 1.1e-07 (Fisher's exact test), Q value = 8.6e-05

Table S27. Gene #65: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	85	57	51	106
14Q LOSS MUTATED	20	31	25	17
14Q LOSS WILD-TYPE	65	26	26	89

Figure S27. Get High-res Image Gene #65: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

'xq loss' versus 'METHLYATION_CNMF'

P value = 2.38e-05 (Fisher's exact test), Q value = 0.018

Table S28. Gene #79: 'xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	78	104	109
XQ LOSS MUTATED	21	39	12
XQ LOSS WILD-TYPE	57	65	97

Figure S28. 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 = 299
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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