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

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

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/C1P26WQD

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 192 patients, 9 significant findings detected with P value < 0.05 and Q value < 0.25.

3q gain cnv correlated to 'MRNASEQ_CHIERARCHICAL' and 'MIRSEQ_MATURE_CHIERARCHICAL'.
5p gain cnv correlated to 'CN_CNMF'.
11q gain cnv correlated to 'MRNASEQ_CHIERARCHICAL'.
19q gain cnv correlated to 'CN_CNMF'.
4p loss cnv correlated to 'CN_CNMF'.
4q loss cnv correlated to 'CN_CNMF'.
5q loss cnv correlated to 'CN_CNMF'.
12p loss cnv correlated to 'CN_CNMF'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 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, 9 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	Chi-square test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
3q gain	113 (59%)	79	0.00263 (1.00)	0.00121 (0.748)	0.0022 (1.00)	0.000251 (0.159)	0.0946 (1.00)	0.00267 (1.00)	0.11 (1.00)	0.000355 (0.224)
5p gain	64 (33%)	128	0.00012 (0.0768)	0.136 (1.00)	0.231 (1.00)	0.0124 (1.00)	0.202 (1.00)	0.0959 (1.00)	0.169 (1.00)	0.202 (1.00)
11q gain	7 (4%)	185	0.0305 (1.00)	0.287 (1.00)	0.0113 (1.00)	0.000142 (0.0903)	0.235 (1.00)	0.0584 (1.00)	0.236 (1.00)	0.503 (1.00)
19q gain	45 (23%)	147	0.000261 (0.165)	0.0487 (1.00)	0.352 (1.00)	0.281 (1.00)	0.274 (1.00)	0.403 (1.00)	0.126 (1.00)	1 (1.00)
4p loss	77 (40%)	115	8.17e-07 (0.000522)	0.0564 (1.00)	0.0735 (1.00)	0.00103 (0.64)	0.0553 (1.00)	0.0411 (1.00)	0.173 (1.00)	0.0102 (1.00)
4q loss	54 (28%)	138	2.44e-07 (0.000156)	0.12 (1.00)	0.496 (1.00)	0.00892 (1.00)	0.529 (1.00)	0.404 (1.00)	0.619 (1.00)	0.891 (1.00)
5q loss	35 (18%)	157	0.000266 (0.169)	0.218 (1.00)	0.394 (1.00)	0.875 (1.00)	0.393 (1.00)	0.911 (1.00)	0.502 (1.00)	0.944 (1.00)
12p loss	25 (13%)	167	0.000138 (0.088)	0.17 (1.00)	0.107 (1.00)	0.224 (1.00)	0.164 (1.00)	0.0292 (1.00)	0.141 (1.00)	0.097 (1.00)
1p gain	57 (30%)	135	0.477 (1.00)	0.00799 (1.00)	0.032 (1.00)	0.125 (1.00)	0.914 (1.00)	0.0822 (1.00)	0.543 (1.00)	0.131 (1.00)
1q gain	90 (47%)	102	0.0401 (1.00)	0.126 (1.00)	0.188 (1.00)	0.181 (1.00)	0.792 (1.00)	0.34 (1.00)	0.975 (1.00)	0.236 (1.00)
2p gain	40 (21%)	152	0.0126 (1.00)	0.00611 (1.00)	0.0629 (1.00)	0.0364 (1.00)	0.183 (1.00)	0.00235 (1.00)	0.373 (1.00)	0.0335 (1.00)
2q gain	25 (13%)	167	0.00378 (1.00)	0.0556 (1.00)	0.000637 (0.4)	0.0007 (0.439)	0.158 (1.00)	0.0114 (1.00)	0.206 (1.00)	0.0641 (1.00)
3p gain	48 (25%)	144	0.753 (1.00)	0.0146 (1.00)	0.00842 (1.00)	0.416 (1.00)	0.0371 (1.00)	0.0365 (1.00)	0.108 (1.00)	0.134 (1.00)
4p gain	6 (3%)	186	1 (1.00)	0.648 (1.00)	0.762 (1.00)	1 (1.00)	0.88 (1.00)	0.517 (1.00)	0.88 (1.00)	0.674 (1.00)
4q gain	7 (4%)	185	0.784 (1.00)	0.446 (1.00)	0.796 (1.00)	0.501 (1.00)	0.893 (1.00)	0.799 (1.00)	0.895 (1.00)	0.71 (1.00)
5q gain	28 (15%)	164	0.0639 (1.00)	0.563 (1.00)	0.909 (1.00)	0.844 (1.00)	0.436 (1.00)	0.535 (1.00)	0.232 (1.00)	0.935 (1.00)
6p gain	35 (18%)	157	0.584 (1.00)	0.0341 (1.00)	0.215 (1.00)	0.126 (1.00)	0.318 (1.00)	0.258 (1.00)	0.624 (1.00)	0.918 (1.00)
6q gain	22 (11%)	170	0.725 (1.00)	0.315 (1.00)	0.288 (1.00)	0.329 (1.00)	0.553 (1.00)	0.295 (1.00)	0.811 (1.00)	0.613 (1.00)
7p gain	23 (12%)	169	0.0322 (1.00)	0.0617 (1.00)	0.116 (1.00)	0.426 (1.00)	0.0131 (1.00)	0.0813 (1.00)	0.0113 (1.00)	0.0467 (1.00)
7q gain	21 (11%)	171	0.044 (1.00)	0.593 (1.00)	0.755 (1.00)	0.592 (1.00)	0.0171 (1.00)	0.528 (1.00)	0.0415 (1.00)	0.304 (1.00)
8p gain	29 (15%)	163	0.904 (1.00)	0.0858 (1.00)	0.0138 (1.00)	0.472 (1.00)	0.902 (1.00)	0.644 (1.00)	0.731 (1.00)	0.918 (1.00)
8q gain	50 (26%)	142	0.381 (1.00)	0.1 (1.00)	0.299 (1.00)	0.331 (1.00)	0.0684 (1.00)	0.0527 (1.00)	0.546 (1.00)	0.154 (1.00)
9p gain	30 (16%)	162	0.588 (1.00)	0.105 (1.00)	0.575 (1.00)	0.00458 (1.00)	0.267 (1.00)	0.299 (1.00)	0.831 (1.00)	0.183 (1.00)
9q gain	30 (16%)	162	0.704 (1.00)	0.0148 (1.00)	0.0477 (1.00)	0.000522 (0.329)	0.0184 (1.00)	0.0147 (1.00)	0.529 (1.00)	0.0164 (1.00)
10p gain	14 (7%)	178	0.294 (1.00)	0.742 (1.00)	0.778 (1.00)	0.914 (1.00)	0.877 (1.00)	0.885 (1.00)	1 (1.00)	0.886 (1.00)
10q gain	9 (5%)	183	0.907 (1.00)	0.85 (1.00)	0.934 (1.00)	0.88 (1.00)	0.0781 (1.00)	1 (1.00)	0.128 (1.00)	0.58 (1.00)
11p gain	6 (3%)	186	0.669 (1.00)	0.666 (1.00)	0.0863 (1.00)	0.00653 (1.00)	0.88 (1.00)	0.0799 (1.00)	0.88 (1.00)	0.877 (1.00)
12p gain	30 (16%)	162	0.54 (1.00)	0.358 (1.00)	0.0137 (1.00)	0.582 (1.00)	0.0674 (1.00)	0.496 (1.00)	0.0104 (1.00)	0.55 (1.00)
12q gain	30 (16%)	162	0.3 (1.00)	0.448 (1.00)	0.00445 (1.00)	0.582 (1.00)	0.346 (1.00)	0.652 (1.00)	0.0951 (1.00)	0.845 (1.00)
13q gain	16 (8%)	176	0.444 (1.00)	0.486 (1.00)	0.348 (1.00)	0.3 (1.00)	0.061 (1.00)	0.252 (1.00)	0.0661 (1.00)	0.423 (1.00)
14q gain	27 (14%)	165	0.273 (1.00)	0.3 (1.00)	0.142 (1.00)	0.581 (1.00)	0.116 (1.00)	0.014 (1.00)	0.122 (1.00)	0.129 (1.00)
15q gain	34 (18%)	158	0.921 (1.00)	0.41 (1.00)	0.654 (1.00)	0.261 (1.00)	0.216 (1.00)	1 (1.00)	0.136 (1.00)	0.96 (1.00)
16p gain	26 (14%)	166	0.0681 (1.00)	0.205 (1.00)	0.437 (1.00)	0.324 (1.00)	0.0115 (1.00)	0.24 (1.00)	0.0981 (1.00)	0.324 (1.00)
16q gain	23 (12%)	169	0.27 (1.00)	0.00842 (1.00)	0.52 (1.00)	0.395 (1.00)	0.00102 (0.633)	0.0289 (1.00)	0.00181 (1.00)	0.141 (1.00)
17p gain	14 (7%)	178	0.0237 (1.00)	0.0955 (1.00)	0.551 (1.00)	0.416 (1.00)	0.721 (1.00)	0.62 (1.00)	0.776 (1.00)	0.822 (1.00)
17q gain	31 (16%)	161	0.00922 (1.00)	0.131 (1.00)	0.376 (1.00)	0.193 (1.00)	0.138 (1.00)	0.0693 (1.00)	0.128 (1.00)	0.166 (1.00)
18p gain	25 (13%)	167	0.485 (1.00)	0.35 (1.00)	0.131 (1.00)	0.503 (1.00)	0.726 (1.00)	0.283 (1.00)	0.779 (1.00)	0.605 (1.00)
18q gain	14 (7%)	178	0.548 (1.00)	0.0258 (1.00)	0.0154 (1.00)	1 (1.00)	0.349 (1.00)	0.781 (1.00)	0.723 (1.00)	0.76 (1.00)
19p gain	29 (15%)	163	0.0862 (1.00)	0.567 (1.00)	0.441 (1.00)	0.782 (1.00)	0.0735 (1.00)	0.946 (1.00)	0.041 (1.00)	1 (1.00)
20p gain	66 (34%)	126	0.00164 (1.00)	0.0533 (1.00)	0.191 (1.00)	0.13 (1.00)	0.645 (1.00)	0.122 (1.00)	0.203 (1.00)	0.233 (1.00)
20q gain	74 (39%)	118	0.00577 (1.00)	0.0738 (1.00)	0.533 (1.00)	0.197 (1.00)	0.387 (1.00)	0.0887 (1.00)	0.213 (1.00)	0.0621 (1.00)
21q gain	27 (14%)	165	0.791 (1.00)	0.321 (1.00)	0.159 (1.00)	0.435 (1.00)	1 (1.00)	0.23 (1.00)	0.872 (1.00)	0.0644 (1.00)
22q gain	23 (12%)	169	0.924 (1.00)	0.0996 (1.00)	0.0101 (1.00)	0.448 (1.00)	0.866 (1.00)	0.765 (1.00)	0.936 (1.00)	0.394 (1.00)
xq gain	26 (14%)	166	0.146 (1.00)	0.55 (1.00)	0.182 (1.00)	0.18 (1.00)	0.0552 (1.00)	0.0446 (1.00)	0.12 (1.00)	0.119 (1.00)
1p loss	7 (4%)	185	0.0124 (1.00)	0.348 (1.00)	0.0577 (1.00)	0.547 (1.00)	0.495 (1.00)	0.0315 (1.00)	0.629 (1.00)	0.447 (1.00)
1q loss	7 (4%)	185	0.000702 (0.44)	0.132 (1.00)	0.0403 (1.00)	0.169 (1.00)	0.296 (1.00)	0.125 (1.00)	0.265 (1.00)	0.232 (1.00)
2p loss	11 (6%)	181	0.925 (1.00)	0.886 (1.00)	0.971 (1.00)	0.236 (1.00)	0.925 (1.00)	0.734 (1.00)	0.861 (1.00)	0.686 (1.00)
2q loss	22 (11%)	170	0.835 (1.00)	0.11 (1.00)	0.142 (1.00)	0.286 (1.00)	0.436 (1.00)	0.607 (1.00)	0.768 (1.00)	0.533 (1.00)
3p loss	47 (24%)	145	0.0796 (1.00)	0.00387 (1.00)	0.0259 (1.00)	0.000544 (0.342)	0.00949 (1.00)	0.000857 (0.535)	0.00471 (1.00)	0.000886 (0.552)
3q loss	8 (4%)	184	0.00206 (1.00)	0.11 (1.00)	0.132 (1.00)	0.324 (1.00)	0.9 (1.00)	0.174 (1.00)	0.9 (1.00)	0.433 (1.00)
5p loss	13 (7%)	179	0.128 (1.00)	0.139 (1.00)	0.836 (1.00)	0.9 (1.00)	0.876 (1.00)	1 (1.00)	0.82 (1.00)	0.938 (1.00)
6p loss	29 (15%)	163	0.656 (1.00)	0.38 (1.00)	0.118 (1.00)	0.264 (1.00)	0.531 (1.00)	0.478 (1.00)	0.888 (1.00)	0.237 (1.00)
6q loss	47 (24%)	145	0.13 (1.00)	0.463 (1.00)	0.174 (1.00)	0.501 (1.00)	0.7 (1.00)	0.334 (1.00)	0.514 (1.00)	0.314 (1.00)
7p loss	18 (9%)	174	0.364 (1.00)	0.0821 (1.00)	0.00361 (1.00)	0.0538 (1.00)	0.356 (1.00)	0.0721 (1.00)	0.191 (1.00)	0.331 (1.00)
7q loss	29 (15%)	163	0.0305 (1.00)	0.615 (1.00)	0.108 (1.00)	0.281 (1.00)	0.187 (1.00)	0.0467 (1.00)	0.218 (1.00)	0.199 (1.00)
8p loss	51 (27%)	141	0.011 (1.00)	0.224 (1.00)	0.18 (1.00)	0.793 (1.00)	0.539 (1.00)	0.0589 (1.00)	0.353 (1.00)	0.0878 (1.00)
8q loss	17 (9%)	175	0.672 (1.00)	0.342 (1.00)	0.0248 (1.00)	0.0193 (1.00)	0.195 (1.00)	0.0447 (1.00)	0.0418 (1.00)	0.0936 (1.00)
9p loss	35 (18%)	157	0.000474 (0.299)	0.857 (1.00)	0.579 (1.00)	0.258 (1.00)	1 (1.00)	0.53 (1.00)	0.971 (1.00)	1 (1.00)
9q loss	29 (15%)	163	0.00878 (1.00)	0.214 (1.00)	0.00639 (1.00)	0.0373 (1.00)	0.487 (1.00)	0.124 (1.00)	0.303 (1.00)	0.215 (1.00)
10p loss	41 (21%)	151	0.0446 (1.00)	0.163 (1.00)	0.191 (1.00)	0.232 (1.00)	0.919 (1.00)	0.501 (1.00)	0.713 (1.00)	0.693 (1.00)
10q loss	45 (23%)	147	0.0406 (1.00)	0.383 (1.00)	0.416 (1.00)	0.21 (1.00)	0.873 (1.00)	0.759 (1.00)	0.764 (1.00)	0.688 (1.00)
11p loss	58 (30%)	134	0.0312 (1.00)	0.00878 (1.00)	0.0475 (1.00)	0.125 (1.00)	0.0845 (1.00)	0.104 (1.00)	0.00971 (1.00)	0.11 (1.00)
11q loss	73 (38%)	119	0.00148 (0.911)	0.324 (1.00)	0.456 (1.00)	0.372 (1.00)	0.765 (1.00)	0.451 (1.00)	0.386 (1.00)	0.368 (1.00)
12q loss	8 (4%)	184	0.0307 (1.00)	0.342 (1.00)	1 (1.00)	1 (1.00)	0.672 (1.00)	0.281 (1.00)	0.604 (1.00)	0.392 (1.00)
13q loss	49 (26%)	143	0.0357 (1.00)	0.00743 (1.00)	0.0515 (1.00)	0.00275 (1.00)	0.00715 (1.00)	0.115 (1.00)	0.0051 (1.00)	0.0708 (1.00)
14q loss	22 (11%)	170	0.00759 (1.00)	0.523 (1.00)	0.109 (1.00)	0.00866 (1.00)	0.125 (1.00)	0.223 (1.00)	0.00885 (1.00)	0.077 (1.00)
15q loss	25 (13%)	167	0.328 (1.00)	0.151 (1.00)	0.456 (1.00)	0.354 (1.00)	0.949 (1.00)	0.312 (1.00)	0.716 (1.00)	0.732 (1.00)
16p loss	24 (12%)	168	0.362 (1.00)	0.355 (1.00)	0.196 (1.00)	0.166 (1.00)	0.122 (1.00)	0.0614 (1.00)	0.0548 (1.00)	0.26 (1.00)
16q loss	30 (16%)	162	0.704 (1.00)	0.0039 (1.00)	0.0262 (1.00)	0.0561 (1.00)	0.0376 (1.00)	0.00355 (1.00)	0.000722 (0.451)	0.0467 (1.00)
17p loss	56 (29%)	136	0.00235 (1.00)	0.256 (1.00)	0.0818 (1.00)	0.0624 (1.00)	0.0672 (1.00)	0.156 (1.00)	0.191 (1.00)	0.031 (1.00)
17q loss	19 (10%)	173	0.101 (1.00)	0.00911 (1.00)	0.0209 (1.00)	0.0355 (1.00)	0.0786 (1.00)	0.00843 (1.00)	0.0729 (1.00)	0.0811 (1.00)
18p loss	35 (18%)	157	0.263 (1.00)	0.191 (1.00)	0.0304 (1.00)	0.11 (1.00)	0.295 (1.00)	0.0391 (1.00)	0.013 (1.00)	0.0827 (1.00)
18q loss	48 (25%)	144	0.051 (1.00)	0.0101 (1.00)	0.00112 (0.697)	0.00924 (1.00)	0.153 (1.00)	0.00201 (1.00)	0.00533 (1.00)	0.0378 (1.00)
19p loss	36 (19%)	156	0.0374 (1.00)	0.0125 (1.00)	0.00285 (1.00)	0.35 (1.00)	0.465 (1.00)	0.00317 (1.00)	0.282 (1.00)	0.07 (1.00)
19q loss	16 (8%)	176	0.517 (1.00)	0.423 (1.00)	0.541 (1.00)	0.454 (1.00)	0.287 (1.00)	0.0874 (1.00)	0.0726 (1.00)	0.0568 (1.00)
20p loss	14 (7%)	178	0.373 (1.00)	0.34 (1.00)	0.56 (1.00)	0.416 (1.00)	0.469 (1.00)	0.152 (1.00)	0.224 (1.00)	0.6 (1.00)
20q loss	5 (3%)	187	1 (1.00)	0.398 (1.00)	0.647 (1.00)	1 (1.00)	0.635 (1.00)	0.525 (1.00)	0.742 (1.00)	1 (1.00)
21q loss	28 (15%)	164	0.00845 (1.00)	0.188 (1.00)	0.369 (1.00)	0.00144 (0.892)	0.776 (1.00)	0.333 (1.00)	0.784 (1.00)	0.603 (1.00)
22q loss	42 (22%)	150	0.167 (1.00)	0.0869 (1.00)	0.0829 (1.00)	0.0397 (1.00)	0.892 (1.00)	0.199 (1.00)	0.478 (1.00)	0.239 (1.00)
xq loss	39 (20%)	153	0.021 (1.00)	0.253 (1.00)	0.158 (1.00)	0.108 (1.00)	0.314 (1.00)	0.2 (1.00)	0.15 (1.00)	0.0139 (1.00)

'3q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000251 (Fisher's exact test), Q value = 0.16

Table S1. Gene #6: '3q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	19	112	49
3Q GAIN MUTATED	5	78	23
3Q GAIN WILD-TYPE	14	34	26

Figure S1. Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'3q gain' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.000355 (Fisher's exact test), Q value = 0.22

Table S2. Gene #6: '3q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	67	70	55
3Q GAIN MUTATED	52	36	25
3Q GAIN WILD-TYPE	15	34	30

Figure S2. Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'5p gain' versus 'CN_CNMF'

P value = 0.00012 (Fisher's exact test), Q value = 0.077

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

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	60	42	90
5P GAIN MUTATED	22	24	18
5P GAIN WILD-TYPE	38	18	72

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

'11q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000142 (Fisher's exact test), Q value = 0.09

Table S4. Gene #22: '11q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	19	112	49
11Q GAIN MUTATED	4	0	3
11Q GAIN WILD-TYPE	15	112	46

Figure S4. Get High-res Image Gene #22: '11q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'19q gain' versus 'CN_CNMF'

P value = 0.000261 (Fisher's exact test), Q value = 0.17

Table S5. Gene #35: '19q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	60	42	90
19Q GAIN MUTATED	12	20	13
19Q GAIN WILD-TYPE	48	22	77

Figure S5. Get High-res Image Gene #35: '19q gain' versus Molecular Subtype #1: 'CN_CNMF'

'4p loss' versus 'CN_CNMF'

P value = 8.17e-07 (Fisher's exact test), Q value = 0.00052

Table S6. Gene #47: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	60	42	90
4P LOSS MUTATED	28	29	20
4P LOSS WILD-TYPE	32	13	70

Figure S6. Get High-res Image Gene #47: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

'4q loss' versus 'CN_CNMF'

P value = 2.44e-07 (Fisher's exact test), Q value = 0.00016

Table S7. Gene #48: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	60	42	90
4Q LOSS MUTATED	15	26	13
4Q LOSS WILD-TYPE	45	16	77

Figure S7. Get High-res Image Gene #48: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

'5q loss' versus 'CN_CNMF'

P value = 0.000266 (Fisher's exact test), Q value = 0.17

Table S8. Gene #50: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	60	42	90
5Q LOSS MUTATED	9	17	9
5Q LOSS WILD-TYPE	51	25	81

Figure S8. Get High-res Image Gene #50: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

'12p loss' versus 'CN_CNMF'

P value = 0.000138 (Fisher's exact test), Q value = 0.088

Table S9. Gene #63: '12p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	60	42	90
12P LOSS MUTATED	6	14	5
12P LOSS WILD-TYPE	54	28	85

Figure S9. Get High-res Image Gene #63: '12p loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Molecular subtypes file = CESC-TP.transferedmergedcluster.txt
Number of patients = 192
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

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

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] 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)

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