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

Adrenocortical Carcinoma (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/C1RF5SMV

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 90 patients, 48 significant findings detected with P value < 0.05 and Q value < 0.25.

2p gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.
4p gain cnv correlated to 'CN_CNMF', 'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.
4q gain cnv correlated to 'CN_CNMF', 'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.
5p gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.
5q gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.
7p gain cnv correlated to 'MRNASEQ_CNMF'.
7q gain cnv correlated to 'CN_CNMF', 'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.
9p gain cnv correlated to 'CN_CNMF'.
9q gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.
10p gain cnv correlated to 'MRNASEQ_CNMF'.
10q gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.
12p gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.
12q gain cnv correlated to 'CN_CNMF'.
14q gain cnv correlated to 'MRNASEQ_CHIERARCHICAL', 'MIRSEQ_CNMF', 'MIRSEQ_CHIERARCHICAL', 'MIRSEQ_MATURE_CNMF', and 'MIRSEQ_MATURE_CHIERARCHICAL'.
16p gain cnv correlated to 'CN_CNMF', 'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.
16q gain cnv correlated to 'CN_CNMF', 'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.
19q gain cnv correlated to 'MRNASEQ_CNMF'.
20p gain cnv correlated to 'CN_CNMF', 'MRNASEQ_CNMF', and 'MIRSEQ_MATURE_CNMF'.
20q gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.
xq gain cnv correlated to 'CN_CNMF'.
2q loss cnv correlated to 'CN_CNMF'.
9p loss cnv correlated to 'MRNASEQ_CNMF'.
11q loss cnv correlated to 'CN_CNMF'.
17p loss cnv correlated to 'METHLYATION_CNMF'.
17q 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, 48 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	Chi-square 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
14q gain	21 (23%)	69	0.00718 (1.00)	0.0562 (1.00)	0.000508 (0.278)	0.000113 (0.0638)	9.9e-06 (0.00583)	1.31e-05 (0.00768)	9.64e-06 (0.00569)	3.57e-06 (0.00211)
4p gain	37 (41%)	53	7.8e-05 (0.0444)	0.0432 (1.00)	4.79e-05 (0.0276)	0.00035 (0.193)	0.272 (1.00)	0.394 (1.00)	0.635 (1.00)	0.572 (1.00)
4q gain	33 (37%)	57	0.000236 (0.132)	0.042 (1.00)	1.76e-05 (0.0103)	7.26e-05 (0.0415)	0.528 (1.00)	0.657 (1.00)	0.566 (1.00)	0.771 (1.00)
7q gain	48 (53%)	42	6.72e-05 (0.0385)	0.113 (1.00)	3.54e-06 (0.0021)	0.000192 (0.108)	0.865 (1.00)	0.474 (1.00)	1 (1.00)	0.31 (1.00)
16p gain	49 (54%)	41	9.86e-08 (5.9e-05)	0.0124 (1.00)	8.74e-06 (0.00517)	1.01e-05 (0.00595)	0.0468 (1.00)	0.25 (1.00)	0.0111 (1.00)	0.531 (1.00)
16q gain	47 (52%)	43	2.98e-07 (0.000178)	0.0093 (1.00)	0.000115 (0.065)	3.05e-05 (0.0177)	0.024 (1.00)	0.25 (1.00)	0.0111 (1.00)	0.531 (1.00)
20p gain	46 (51%)	44	1.95e-06 (0.00116)	0.226 (1.00)	0.00012 (0.0676)	0.00738 (1.00)	0.0049 (1.00)	0.00264 (1.00)	0.000147 (0.0825)	0.0128 (1.00)
2p gain	13 (14%)	77	0.000224 (0.125)	0.00127 (0.686)	0.0119 (1.00)	0.000281 (0.156)	0.373 (1.00)	0.121 (1.00)	0.0803 (1.00)	0.0598 (1.00)
5p gain	57 (63%)	33	3.25e-06 (0.00193)	0.031 (1.00)	0.000603 (0.329)	5.59e-05 (0.0321)	0.237 (1.00)	0.376 (1.00)	0.0653 (1.00)	0.385 (1.00)
5q gain	53 (59%)	37	2.9e-05 (0.0168)	0.00943 (1.00)	0.000687 (0.374)	1.34e-05 (0.00787)	0.328 (1.00)	0.202 (1.00)	0.346 (1.00)	0.21 (1.00)
9q gain	29 (32%)	61	0.000186 (0.105)	0.00407 (1.00)	0.0266 (1.00)	0.000264 (0.147)	0.0331 (1.00)	0.279 (1.00)	0.0188 (1.00)	0.183 (1.00)
10q gain	26 (29%)	64	0.000352 (0.194)	0.0763 (1.00)	3.39e-05 (0.0196)	0.00111 (0.6)	0.0195 (1.00)	0.919 (1.00)	0.0704 (1.00)	0.88 (1.00)
12p gain	64 (71%)	26	1.66e-05 (0.00972)	0.199 (1.00)	0.000214 (0.12)	0.00476 (1.00)	0.235 (1.00)	0.471 (1.00)	0.0704 (1.00)	0.532 (1.00)
20q gain	49 (54%)	41	1.99e-05 (0.0116)	0.0627 (1.00)	7.02e-05 (0.0402)	0.00301 (1.00)	0.0186 (1.00)	0.0162 (1.00)	0.000824 (0.447)	0.0225 (1.00)
7p gain	48 (53%)	42	0.000544 (0.297)	0.113 (1.00)	0.000144 (0.0813)	0.00231 (1.00)	0.865 (1.00)	0.685 (1.00)	0.859 (1.00)	0.457 (1.00)
9p gain	20 (22%)	70	2.38e-05 (0.0138)	0.00402 (1.00)	0.0102 (1.00)	0.00161 (0.857)	0.375 (1.00)	0.427 (1.00)	0.233 (1.00)	0.336 (1.00)
10p gain	25 (28%)	65	0.000467 (0.257)	0.0632 (1.00)	4.69e-05 (0.027)	0.000483 (0.265)	0.0331 (1.00)	0.643 (1.00)	0.104 (1.00)	0.532 (1.00)
12q gain	64 (71%)	26	1.58e-06 (0.000939)	0.298 (1.00)	0.000713 (0.387)	0.0129 (1.00)	0.226 (1.00)	0.802 (1.00)	0.0389 (1.00)	0.918 (1.00)
19q gain	52 (58%)	38	0.00202 (1.00)	0.0524 (1.00)	0.000378 (0.208)	0.00236 (1.00)	0.141 (1.00)	0.431 (1.00)	0.0956 (1.00)	0.185 (1.00)
xq gain	40 (44%)	50	1.51e-05 (0.00881)	0.167 (1.00)	0.00164 (0.873)	0.0148 (1.00)	0.784 (1.00)	0.354 (1.00)	0.617 (1.00)	0.237 (1.00)
2q loss	15 (17%)	75	7.75e-05 (0.0442)	0.0024 (1.00)	0.115 (1.00)	0.0875 (1.00)	0.0283 (1.00)	0.17 (1.00)	0.115 (1.00)	0.275 (1.00)
9p loss	20 (22%)	70	0.000929 (0.502)	0.038 (1.00)	9.39e-05 (0.0533)	0.00231 (1.00)	0.00872 (1.00)	0.532 (1.00)	0.0594 (1.00)	0.512 (1.00)
11q loss	23 (26%)	67	4.81e-05 (0.0276)	0.00266 (1.00)	0.143 (1.00)	0.352 (1.00)	0.0975 (1.00)	0.392 (1.00)	0.208 (1.00)	0.447 (1.00)
17p loss	32 (36%)	58	0.00141 (0.753)	0.000305 (0.169)	0.0119 (1.00)	0.02 (1.00)	0.0735 (1.00)	0.0922 (1.00)	0.0514 (1.00)	0.0437 (1.00)
17q loss	24 (27%)	66	0.000199 (0.111)	0.00447 (1.00)	0.119 (1.00)	0.0372 (1.00)	0.0667 (1.00)	0.118 (1.00)	0.0777 (1.00)	0.0631 (1.00)
1p gain	4 (4%)	86	0.0853 (1.00)
1q gain	8 (9%)	82	0.157 (1.00)	0.508 (1.00)	0.0461 (1.00)	0.167 (1.00)	0.0645 (1.00)	0.855 (1.00)	0.299 (1.00)	0.851 (1.00)
2q gain	12 (13%)	78	0.00376 (1.00)	0.00156 (0.834)	0.0183 (1.00)	0.00415 (1.00)	0.0553 (1.00)	0.031 (1.00)	0.019 (1.00)	0.028 (1.00)
3p gain	13 (14%)	77	0.0606 (1.00)	0.112 (1.00)	0.331 (1.00)	0.274 (1.00)	0.407 (1.00)	0.139 (1.00)	0.311 (1.00)	0.227 (1.00)
3q gain	15 (17%)	75	0.0539 (1.00)	0.0862 (1.00)	0.0528 (1.00)	0.623 (1.00)	0.653 (1.00)	0.545 (1.00)	0.558 (1.00)	0.56 (1.00)
6p gain	18 (20%)	72	0.0583 (1.00)	0.653 (1.00)	0.0686 (1.00)	0.937 (1.00)	0.149 (1.00)	0.102 (1.00)	0.197 (1.00)	0.257 (1.00)
6q gain	16 (18%)	74	0.00189 (1.00)	0.453 (1.00)	0.192 (1.00)	0.527 (1.00)	0.289 (1.00)	0.225 (1.00)	0.259 (1.00)	0.501 (1.00)
8p gain	32 (36%)	58	0.00226 (1.00)	0.137 (1.00)	0.165 (1.00)	0.246 (1.00)	0.117 (1.00)	0.307 (1.00)	0.0267 (1.00)	0.515 (1.00)
8q gain	38 (42%)	52	0.0191 (1.00)	0.286 (1.00)	0.401 (1.00)	0.502 (1.00)	0.471 (1.00)	0.552 (1.00)	0.0857 (1.00)	0.778 (1.00)
11p gain	5 (6%)	85	0.0478 (1.00)
11q gain	6 (7%)	84	0.126 (1.00)	0.126 (1.00)	0.0446 (1.00)	0.172 (1.00)	0.187 (1.00)	1 (1.00)	0.445 (1.00)	0.808 (1.00)
13q gain	6 (7%)	84	0.919 (1.00)	0.478 (1.00)	0.0392 (1.00)	0.363 (1.00)	0.141 (1.00)	0.855 (1.00)	0.299 (1.00)	0.851 (1.00)
15q gain	11 (12%)	79	0.221 (1.00)	0.0563 (1.00)	0.0106 (1.00)	0.0116 (1.00)	0.362 (1.00)	0.163 (1.00)	0.248 (1.00)	0.114 (1.00)
17p gain	5 (6%)	85	0.113 (1.00)	0.509 (1.00)	0.687 (1.00)	0.113 (1.00)	0.208 (1.00)	0.375 (1.00)	0.14 (1.00)	0.14 (1.00)
17q gain	7 (8%)	83	0.00981 (1.00)	0.509 (1.00)	0.687 (1.00)	0.113 (1.00)	0.208 (1.00)	0.375 (1.00)	0.14 (1.00)	0.14 (1.00)
18p gain	6 (7%)	84	0.422 (1.00)
18q gain	5 (6%)	85	0.598 (1.00)
19p gain	56 (62%)	34	0.0118 (1.00)	0.0496 (1.00)	0.00129 (0.691)	0.00128 (0.687)	0.438 (1.00)	0.729 (1.00)	0.366 (1.00)	0.393 (1.00)
21q gain	31 (34%)	59	0.0331 (1.00)	0.00842 (1.00)	0.0203 (1.00)	0.00137 (0.733)	0.0122 (1.00)	0.0557 (1.00)	0.0264 (1.00)	0.0327 (1.00)
22q gain	3 (3%)	87	0.496 (1.00)
1p loss	29 (32%)	61	0.215 (1.00)	0.168 (1.00)	0.414 (1.00)	0.0904 (1.00)	0.471 (1.00)	0.501 (1.00)	0.717 (1.00)	0.677 (1.00)
1q loss	20 (22%)	70	0.546 (1.00)	0.0989 (1.00)	0.944 (1.00)	0.798 (1.00)	0.364 (1.00)	0.271 (1.00)	0.58 (1.00)	0.363 (1.00)
2p loss	17 (19%)	73	0.000508 (0.278)	0.0255 (1.00)	0.588 (1.00)	0.468 (1.00)	0.0357 (1.00)	0.275 (1.00)	0.127 (1.00)	0.336 (1.00)
3p loss	20 (22%)	70	0.0363 (1.00)	0.109 (1.00)	0.115 (1.00)	0.214 (1.00)	0.484 (1.00)	0.36 (1.00)	0.204 (1.00)	0.229 (1.00)
3q loss	20 (22%)	70	0.0117 (1.00)	0.127 (1.00)	0.0241 (1.00)	0.0655 (1.00)	0.197 (1.00)	0.118 (1.00)	0.04 (1.00)	0.0724 (1.00)
4p loss	10 (11%)	80	0.0345 (1.00)	0.181 (1.00)	0.0232 (1.00)	0.0537 (1.00)	0.308 (1.00)	0.547 (1.00)	0.423 (1.00)	0.556 (1.00)
4q loss	11 (12%)	79	0.0916 (1.00)	0.0612 (1.00)	0.00728 (1.00)	0.0187 (1.00)	0.25 (1.00)	0.642 (1.00)	0.38 (1.00)	0.466 (1.00)
5p loss	8 (9%)	82	0.168 (1.00)	0.0597 (1.00)	0.229 (1.00)	0.00181 (0.959)	0.772 (1.00)	1 (1.00)	0.454 (1.00)	1 (1.00)
5q loss	7 (8%)	83	0.621 (1.00)	0.508 (1.00)	0.276 (1.00)	0.167 (1.00)	0.658 (1.00)	0.597 (1.00)	0.862 (1.00)	0.614 (1.00)
6p loss	19 (21%)	71	0.0438 (1.00)	0.833 (1.00)	0.594 (1.00)	0.39 (1.00)	0.607 (1.00)	0.737 (1.00)	0.816 (1.00)	0.586 (1.00)
6q loss	22 (24%)	68	0.0116 (1.00)	0.881 (1.00)	0.607 (1.00)	0.615 (1.00)	0.72 (1.00)	0.852 (1.00)	0.724 (1.00)	0.682 (1.00)
7p loss	5 (6%)	85	0.394 (1.00)	0.517 (1.00)	0.91 (1.00)	0.815 (1.00)	0.816 (1.00)	0.072 (1.00)	0.681 (1.00)	0.0865 (1.00)
7q loss	6 (7%)	84	0.287 (1.00)	0.254 (1.00)	0.62 (1.00)	0.442 (1.00)	1 (1.00)	0.0538 (1.00)	0.593 (1.00)	0.0647 (1.00)
8p loss	16 (18%)	74	0.00963 (1.00)	0.206 (1.00)	0.18 (1.00)	0.0702 (1.00)	0.192 (1.00)	0.0561 (1.00)	0.0175 (1.00)	0.0309 (1.00)
8q loss	12 (13%)	78	0.00206 (1.00)	0.0829 (1.00)	0.033 (1.00)	0.0283 (1.00)	0.0777 (1.00)	0.068 (1.00)	0.034 (1.00)	0.0344 (1.00)
9q loss	11 (12%)	79	0.135 (1.00)	0.932 (1.00)	0.0807 (1.00)	0.432 (1.00)	0.558 (1.00)	1 (1.00)	0.83 (1.00)	0.899 (1.00)
10p loss	12 (13%)	78	0.82 (1.00)	0.418 (1.00)	0.265 (1.00)	0.822 (1.00)	0.683 (1.00)	0.642 (1.00)	0.616 (1.00)	0.466 (1.00)
10q loss	10 (11%)	80	0.484 (1.00)	0.567 (1.00)	0.536 (1.00)	0.9 (1.00)	1 (1.00)	0.518 (1.00)	0.891 (1.00)	0.528 (1.00)
11p loss	24 (27%)	66	0.00129 (0.692)	0.0149 (1.00)	0.223 (1.00)	0.548 (1.00)	0.277 (1.00)	0.567 (1.00)	0.419 (1.00)	0.585 (1.00)
12p loss	5 (6%)	85	0.189 (1.00)	0.262 (1.00)	0.62 (1.00)	1 (1.00)	0.103 (1.00)	1 (1.00)	0.0107 (1.00)	1 (1.00)
12q loss	4 (4%)	86	0.108 (1.00)	0.0982 (1.00)	0.441 (1.00)	0.557 (1.00)	0.331 (1.00)	0.791 (1.00)	0.0427 (1.00)	1 (1.00)
13q loss	39 (43%)	51	0.0104 (1.00)	0.0838 (1.00)	0.6 (1.00)	0.768 (1.00)	0.761 (1.00)	0.9 (1.00)	0.915 (1.00)	0.766 (1.00)
14q loss	18 (20%)	72	0.0232 (1.00)	0.447 (1.00)	0.0184 (1.00)	0.00406 (1.00)	0.377 (1.00)	0.332 (1.00)	0.277 (1.00)	0.174 (1.00)
15q loss	21 (23%)	69	0.0299 (1.00)	0.36 (1.00)	0.11 (1.00)	0.172 (1.00)	0.571 (1.00)	0.843 (1.00)	0.331 (1.00)	0.912 (1.00)
16p loss	6 (7%)	84	0.126 (1.00)	0.0575 (1.00)	0.00215 (1.00)	0.0801 (1.00)	0.0128 (1.00)	0.258 (1.00)	0.0315 (1.00)	0.226 (1.00)
16q loss	5 (6%)	85	0.272 (1.00)	0.0356 (1.00)	0.0575 (1.00)	0.0214 (1.00)	0.169 (1.00)	1 (1.00)	0.36 (1.00)	1 (1.00)
18p loss	37 (41%)	53	0.0264 (1.00)	0.242 (1.00)	0.771 (1.00)	0.756 (1.00)	0.684 (1.00)	0.492 (1.00)	0.85 (1.00)	0.593 (1.00)
18q loss	35 (39%)	55	0.0444 (1.00)	0.399 (1.00)	0.811 (1.00)	0.927 (1.00)	0.471 (1.00)	0.472 (1.00)	0.732 (1.00)	0.63 (1.00)
19p loss	5 (6%)	85	0.0478 (1.00)	0.356 (1.00)	0.157 (1.00)	0.779 (1.00)	0.139 (1.00)	0.706 (1.00)	0.215 (1.00)	0.723 (1.00)
19q loss	4 (4%)	86	0.108 (1.00)	0.673 (1.00)	0.774 (1.00)	0.474 (1.00)	0.785 (1.00)	1 (1.00)	0.215 (1.00)	1 (1.00)
20p loss	9 (10%)	81	0.00774 (1.00)	0.282 (1.00)	0.213 (1.00)	0.028 (1.00)	0.0678 (1.00)	0.639 (1.00)	0.169 (1.00)	0.645 (1.00)
20q loss	3 (3%)	87	0.551 (1.00)
21q loss	15 (17%)	75	0.0147 (1.00)	0.366 (1.00)	0.256 (1.00)	0.234 (1.00)	0.224 (1.00)	0.245 (1.00)	0.233 (1.00)	0.107 (1.00)
22q loss	48 (53%)	42	0.0781 (1.00)	0.0753 (1.00)	0.604 (1.00)	0.584 (1.00)	0.859 (1.00)	0.725 (1.00)	0.794 (1.00)	0.68 (1.00)
xq loss	17 (19%)	73	0.00216 (1.00)	0.255 (1.00)	0.0335 (1.00)	0.0207 (1.00)	0.707 (1.00)	0.851 (1.00)	0.138 (1.00)	0.672 (1.00)

'2p gain' versus 'CN_CNMF'

P value = 0.000224 (Chi-square test), Q value = 0.12

Table S1. Gene #3: '2p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
2P GAIN MUTATED	12	0	1	0	0
2P GAIN WILD-TYPE	20	24	14	10	9

Figure S1. Get High-res Image Gene #3: '2p gain' versus Molecular Subtype #1: 'CN_CNMF'

'2p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000281 (Fisher's exact test), Q value = 0.16

Table S2. Gene #3: '2p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	23	32	22
2P GAIN MUTATED	8	1	0
2P GAIN WILD-TYPE	15	31	22

Figure S2. Get High-res Image Gene #3: '2p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'4p gain' versus 'CN_CNMF'

P value = 7.8e-05 (Chi-square test), Q value = 0.044

Table S3. Gene #7: '4p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
4P GAIN MUTATED	3	13	10	4	7
4P GAIN WILD-TYPE	29	11	5	6	2

Figure S3. Get High-res Image Gene #7: '4p gain' versus Molecular Subtype #1: 'CN_CNMF'

'4p gain' versus 'MRNASEQ_CNMF'

P value = 4.79e-05 (Fisher's exact test), Q value = 0.028

Table S4. Gene #7: '4p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	24	13	17	23
4P GAIN MUTATED	1	8	11	10
4P GAIN WILD-TYPE	23	5	6	13

Figure S4. Get High-res Image Gene #7: '4p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'4p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00035 (Fisher's exact test), Q value = 0.19

Table S5. Gene #7: '4p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	23	32	22
4P GAIN MUTATED	2	14	14
4P GAIN WILD-TYPE	21	18	8

Figure S5. Get High-res Image Gene #7: '4p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'4q gain' versus 'CN_CNMF'

P value = 0.000236 (Chi-square test), Q value = 0.13

Table S6. Gene #8: '4q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
4Q GAIN MUTATED	2	12	9	4	6
4Q GAIN WILD-TYPE	30	12	6	6	3

Figure S6. Get High-res Image Gene #8: '4q gain' versus Molecular Subtype #1: 'CN_CNMF'

'4q gain' versus 'MRNASEQ_CNMF'

P value = 1.76e-05 (Fisher's exact test), Q value = 0.01

Table S7. Gene #8: '4q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	24	13	17	23
4Q GAIN MUTATED	0	8	9	10
4Q GAIN WILD-TYPE	24	5	8	13

Figure S7. Get High-res Image Gene #8: '4q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'4q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 7.26e-05 (Fisher's exact test), Q value = 0.041

Table S8. Gene #8: '4q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	23	32	22
4Q GAIN MUTATED	1	12	14
4Q GAIN WILD-TYPE	22	20	8

Figure S8. Get High-res Image Gene #8: '4q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'5p gain' versus 'CN_CNMF'

P value = 3.25e-06 (Chi-square test), Q value = 0.0019

Table S9. Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
5P GAIN MUTATED	10	22	13	4	8
5P GAIN WILD-TYPE	22	2	2	6	1

Figure S9. Get High-res Image Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

'5p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 5.59e-05 (Fisher's exact test), Q value = 0.032

Table S10. Gene #9: '5p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	23	32	22
5P GAIN MUTATED	6	26	17
5P GAIN WILD-TYPE	17	6	5

Figure S10. Get High-res Image Gene #9: '5p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'5q gain' versus 'CN_CNMF'

P value = 2.9e-05 (Chi-square test), Q value = 0.017

Table S11. Gene #10: '5q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
5Q GAIN MUTATED	9	19	13	4	8
5Q GAIN WILD-TYPE	23	5	2	6	1

Figure S11. Get High-res Image Gene #10: '5q gain' versus Molecular Subtype #1: 'CN_CNMF'

'5q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1.34e-05 (Fisher's exact test), Q value = 0.0079

Table S12. Gene #10: '5q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	23	32	22
5Q GAIN MUTATED	5	23	19
5Q GAIN WILD-TYPE	18	9	3

Figure S12. Get High-res Image Gene #10: '5q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'7p gain' versus 'MRNASEQ_CNMF'

P value = 0.000144 (Fisher's exact test), Q value = 0.081

Table S13. Gene #13: '7p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	24	13	17	23
7P GAIN MUTATED	6	12	13	11
7P GAIN WILD-TYPE	18	1	4	12

Figure S13. Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'7q gain' versus 'CN_CNMF'

P value = 6.72e-05 (Chi-square test), Q value = 0.038

Table S14. Gene #14: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
7Q GAIN MUTATED	8	18	13	3	6
7Q GAIN WILD-TYPE	24	6	2	7	3

Figure S14. Get High-res Image Gene #14: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

'7q gain' versus 'MRNASEQ_CNMF'

P value = 3.54e-06 (Fisher's exact test), Q value = 0.0021

Table S15. Gene #14: '7q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	24	13	17	23
7Q GAIN MUTATED	5	13	13	11
7Q GAIN WILD-TYPE	19	0	4	12

Figure S15. Get High-res Image Gene #14: '7q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'7q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000192 (Fisher's exact test), Q value = 0.11

Table S16. Gene #14: '7q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	23	32	22
7Q GAIN MUTATED	6	17	19
7Q GAIN WILD-TYPE	17	15	3

Figure S16. Get High-res Image Gene #14: '7q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'9p gain' versus 'CN_CNMF'

P value = 2.38e-05 (Chi-square test), Q value = 0.014

Table S17. Gene #17: '9p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
9P GAIN MUTATED	2	3	10	1	4
9P GAIN WILD-TYPE	30	21	5	9	5

Figure S17. Get High-res Image Gene #17: '9p gain' versus Molecular Subtype #1: 'CN_CNMF'

'9q gain' versus 'CN_CNMF'

P value = 0.000186 (Chi-square test), Q value = 0.1

Table S18. Gene #18: '9q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
9Q GAIN MUTATED	7	3	12	3	4
9Q GAIN WILD-TYPE	25	21	3	7	5

Figure S18. Get High-res Image Gene #18: '9q gain' versus Molecular Subtype #1: 'CN_CNMF'

'9q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000264 (Fisher's exact test), Q value = 0.15

Table S19. Gene #18: '9q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	23	32	22
9Q GAIN MUTATED	8	2	12
9Q GAIN WILD-TYPE	15	30	10

Figure S19. Get High-res Image Gene #18: '9q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'10p gain' versus 'MRNASEQ_CNMF'

P value = 4.69e-05 (Fisher's exact test), Q value = 0.027

Table S20. Gene #19: '10p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	24	13	17	23
10P GAIN MUTATED	6	11	4	2
10P GAIN WILD-TYPE	18	2	13	21

Figure S20. Get High-res Image Gene #19: '10p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'10q gain' versus 'CN_CNMF'

P value = 0.000352 (Chi-square test), Q value = 0.19

Table S21. Gene #20: '10q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
10Q GAIN MUTATED	10	3	11	1	1
10Q GAIN WILD-TYPE	22	21	4	9	8

Figure S21. Get High-res Image Gene #20: '10q gain' versus Molecular Subtype #1: 'CN_CNMF'

'10q gain' versus 'MRNASEQ_CNMF'

P value = 3.39e-05 (Fisher's exact test), Q value = 0.02

Table S22. Gene #20: '10q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	24	13	17	23
10Q GAIN MUTATED	7	11	3	2
10Q GAIN WILD-TYPE	17	2	14	21

Figure S22. Get High-res Image Gene #20: '10q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'12p gain' versus 'CN_CNMF'

P value = 1.66e-05 (Chi-square test), Q value = 0.0097

Table S23. Gene #23: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
12P GAIN MUTATED	14	24	14	5	7
12P GAIN WILD-TYPE	18	0	1	5	2

Figure S23. Get High-res Image Gene #23: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

'12p gain' versus 'MRNASEQ_CNMF'

P value = 0.000214 (Fisher's exact test), Q value = 0.12

Table S24. Gene #23: '12p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	24	13	17	23
12P GAIN MUTATED	9	13	14	18
12P GAIN WILD-TYPE	15	0	3	5

Figure S24. Get High-res Image Gene #23: '12p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'12q gain' versus 'CN_CNMF'

P value = 1.58e-06 (Chi-square test), Q value = 0.00094

Table S25. Gene #24: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
12Q GAIN MUTATED	14	24	15	4	7
12Q GAIN WILD-TYPE	18	0	0	6	2

Figure S25. Get High-res Image Gene #24: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

'14q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000113 (Fisher's exact test), Q value = 0.064

Table S26. Gene #26: '14q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	23	32	22
14Q GAIN MUTATED	3	2	12
14Q GAIN WILD-TYPE	20	30	10

Figure S26. Get High-res Image Gene #26: '14q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'14q gain' versus 'MIRSEQ_CNMF'

P value = 9.9e-06 (Fisher's exact test), Q value = 0.0058

Table S27. Gene #26: '14q gain' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	36	16	26
14Q GAIN MUTATED	17	0	1
14Q GAIN WILD-TYPE	19	16	25

Figure S27. Get High-res Image Gene #26: '14q gain' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'14q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1.31e-05 (Fisher's exact test), Q value = 0.0077

Table S28. Gene #26: '14q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	26	10	42
14Q GAIN MUTATED	0	0	18
14Q GAIN WILD-TYPE	26	10	24

Figure S28. Get High-res Image Gene #26: '14q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'14q gain' versus 'MIRSEQ_MATURE_CNMF'

P value = 9.64e-06 (Fisher's exact test), Q value = 0.0057

Table S29. Gene #26: '14q gain' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	37	18	23
14Q GAIN MUTATED	17	1	0
14Q GAIN WILD-TYPE	20	17	23

Figure S29. Get High-res Image Gene #26: '14q gain' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'14q gain' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 3.57e-06 (Fisher's exact test), Q value = 0.0021

Table S30. Gene #26: '14q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	40	11	27
14Q GAIN MUTATED	18	0	0
14Q GAIN WILD-TYPE	22	11	27

Figure S30. Get High-res Image Gene #26: '14q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'16p gain' versus 'CN_CNMF'

P value = 9.86e-08 (Chi-square test), Q value = 5.9e-05

Table S31. Gene #28: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
16P GAIN MUTATED	6	24	10	4	5
16P GAIN WILD-TYPE	26	0	5	6	4

Figure S31. Get High-res Image Gene #28: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

'16p gain' versus 'MRNASEQ_CNMF'

P value = 8.74e-06 (Fisher's exact test), Q value = 0.0052

Table S32. Gene #28: '16p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	24	13	17	23
16P GAIN MUTATED	3	10	13	16
16P GAIN WILD-TYPE	21	3	4	7

Figure S32. Get High-res Image Gene #28: '16p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'16p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1.01e-05 (Fisher's exact test), Q value = 0.0059

Table S33. Gene #28: '16p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	23	32	22
16P GAIN MUTATED	4	19	19
16P GAIN WILD-TYPE	19	13	3

Figure S33. Get High-res Image Gene #28: '16p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'16q gain' versus 'CN_CNMF'

P value = 2.98e-07 (Chi-square test), Q value = 0.00018

Table S34. Gene #29: '16q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
16Q GAIN MUTATED	6	23	10	3	5
16Q GAIN WILD-TYPE	26	1	5	7	4

Figure S34. Get High-res Image Gene #29: '16q gain' versus Molecular Subtype #1: 'CN_CNMF'

'16q gain' versus 'MRNASEQ_CNMF'

P value = 0.000115 (Fisher's exact test), Q value = 0.065

Table S35. Gene #29: '16q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	24	13	17	23
16Q GAIN MUTATED	4	9	13	16
16Q GAIN WILD-TYPE	20	4	4	7

Figure S35. Get High-res Image Gene #29: '16q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'16q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3.05e-05 (Fisher's exact test), Q value = 0.018

Table S36. Gene #29: '16q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	23	32	22
16Q GAIN MUTATED	4	20	18
16Q GAIN WILD-TYPE	19	12	4

Figure S36. Get High-res Image Gene #29: '16q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'19q gain' versus 'MRNASEQ_CNMF'

P value = 0.000378 (Fisher's exact test), Q value = 0.21

Table S37. Gene #35: '19q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	24	13	17	23
19Q GAIN MUTATED	10	13	12	9
19Q GAIN WILD-TYPE	14	0	5	14

Figure S37. Get High-res Image Gene #35: '19q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'20p gain' versus 'CN_CNMF'

P value = 1.95e-06 (Chi-square test), Q value = 0.0012

Table S38. Gene #36: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
20P GAIN MUTATED	7	22	9	2	6
20P GAIN WILD-TYPE	25	2	6	8	3

Figure S38. Get High-res Image Gene #36: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

'20p gain' versus 'MRNASEQ_CNMF'

P value = 0.00012 (Fisher's exact test), Q value = 0.068

Table S39. Gene #36: '20p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	24	13	17	23
20P GAIN MUTATED	4	9	8	18
20P GAIN WILD-TYPE	20	4	9	5

Figure S39. Get High-res Image Gene #36: '20p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'20p gain' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.000147 (Fisher's exact test), Q value = 0.083

Table S40. Gene #36: '20p gain' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	37	18	23
20P GAIN MUTATED	13	7	20
20P GAIN WILD-TYPE	24	11	3

Figure S40. Get High-res Image Gene #36: '20p gain' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'20q gain' versus 'CN_CNMF'

P value = 1.99e-05 (Chi-square test), Q value = 0.012

Table S41. Gene #37: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
20Q GAIN MUTATED	9	21	11	2	6
20Q GAIN WILD-TYPE	23	3	4	8	3

Figure S41. Get High-res Image Gene #37: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

'20q gain' versus 'MRNASEQ_CNMF'

P value = 7.02e-05 (Fisher's exact test), Q value = 0.04

Table S42. Gene #37: '20q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	24	13	17	23
20Q GAIN MUTATED	5	11	8	18
20Q GAIN WILD-TYPE	19	2	9	5

Figure S42. Get High-res Image Gene #37: '20q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'xq gain' versus 'CN_CNMF'

P value = 1.51e-05 (Chi-square test), Q value = 0.0088

Table S43. Gene #40: 'xq gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
XQ GAIN MUTATED	6	20	9	2	3
XQ GAIN WILD-TYPE	26	4	6	8	6

Figure S43. Get High-res Image Gene #40: 'xq gain' versus Molecular Subtype #1: 'CN_CNMF'

'2q loss' versus 'CN_CNMF'

P value = 7.75e-05 (Chi-square test), Q value = 0.044

Table S44. Gene #44: '2q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
2Q LOSS MUTATED	1	2	2	6	4
2Q LOSS WILD-TYPE	31	22	13	4	5

Figure S44. Get High-res Image Gene #44: '2q loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'MRNASEQ_CNMF'

P value = 9.39e-05 (Fisher's exact test), Q value = 0.053

Table S45. Gene #57: '9p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	24	13	17	23
9P LOSS MUTATED	14	1	3	1
9P LOSS WILD-TYPE	10	12	14	22

Figure S45. Get High-res Image Gene #57: '9p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'11q loss' versus 'CN_CNMF'

P value = 4.81e-05 (Chi-square test), Q value = 0.028

Table S46. Gene #62: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
11Q LOSS MUTATED	4	3	3	8	5
11Q LOSS WILD-TYPE	28	21	12	2	4

Figure S46. Get High-res Image Gene #62: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

'17p loss' versus 'METHLYATION_CNMF'

P value = 0.000305 (Chi-square test), Q value = 0.17

Table S47. Gene #70: '17p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	18	11	20	18	11
17P LOSS MUTATED	11	0	12	4	1
17P LOSS WILD-TYPE	7	11	8	14	10

Figure S47. Get High-res Image Gene #70: '17p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'17q loss' versus 'CN_CNMF'

P value = 0.000199 (Chi-square test), Q value = 0.11

Table S48. Gene #71: '17q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	32	24	15	10	9
17Q LOSS MUTATED	7	3	6	8	0
17Q LOSS WILD-TYPE	25	21	9	2	9

Figure S48. Get High-res Image Gene #71: '17q loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Molecular subtypes file = ACC-TP.transferedmergedcluster.txt
Number of patients = 90
Number of significantly arm-level cnvs = 80
Number of molecular subtypes = 8
Exclude genes that fewer than K tumors have mutations, K = 3

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

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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)

[2] 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)

[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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