Correlation between copy number variation genes (focal events) and molecular subtypes

Rectum Adenocarcinoma (Primary solid tumor)

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 variation genes (focal events) and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1G73C5R

Overview

Introduction

This pipeline computes the correlation between significant copy number variation (cnv focal) genes and molecular subtypes.

Summary

Testing the association between copy number variation 40 focal events and 12 molecular subtypes across 162 patients, 12 significant findings detected with P value < 0.05 and Q value < 0.25.

4p cnv correlated to 'CN_CNMF'.
4q cnv correlated to 'CN_CNMF'.
7p cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.
7q cnv correlated to 'CN_CNMF'.
8p cnv correlated to 'CN_CNMF'.
8q cnv correlated to 'CN_CNMF'.
13q cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.
18p cnv correlated to 'CN_CNMF'.
18q cnv correlated to 'CN_CNMF'.
19p 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 40 focal events and 12 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 12 significant findings detected.


		Clinical Features	MRNA CNMF	MRNA CHIERARCHICAL	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	Chi-square test	Fisher's exact test	Fisher's exact test	Chi-square test	Fisher's exact test	Fisher's exact test	Chi-square test	Fisher's exact test	Fisher's exact test	Chi-square test
7p	102 (63%)	60	0.00506 (1.00)	0.0115 (1.00)	2.58e-05 (0.0123)	0.00526 (1.00)	0.638 (1.00)	0.518 (1.00)	0.00263 (1.00)	7.32e-05 (0.0346)	0.0612 (1.00)	0.0211 (1.00)	0.117 (1.00)	0.238 (1.00)
13q	118 (73%)	44	0.608 (1.00)	0.792 (1.00)	1.81e-05 (0.00863)	0.14 (1.00)	0.838 (1.00)	0.0948 (1.00)	0.456 (1.00)	0.000172 (0.0809)	0.0274 (1.00)	0.0216 (1.00)	0.155 (1.00)	0.317 (1.00)
4p	67 (41%)	95	0.606 (1.00)	0.141 (1.00)	9e-05 (0.0425)	0.0275 (1.00)	0.451 (1.00)	0.0764 (1.00)	0.983 (1.00)	0.711 (1.00)	0.817 (1.00)	0.0477 (1.00)	0.433 (1.00)	0.519 (1.00)
4q	70 (43%)	92	0.538 (1.00)	0.116 (1.00)	1.49e-05 (0.00712)	0.0132 (1.00)	0.512 (1.00)	0.349 (1.00)	0.854 (1.00)	0.9 (1.00)	0.878 (1.00)	0.0632 (1.00)	0.767 (1.00)	0.721 (1.00)
7q	86 (53%)	76	0.08 (1.00)	0.076 (1.00)	0.000171 (0.0802)	0.273 (1.00)	0.777 (1.00)	0.967 (1.00)	0.0783 (1.00)	0.0229 (1.00)	0.421 (1.00)	0.416 (1.00)	0.571 (1.00)	0.763 (1.00)
8p	114 (70%)	48	0.0383 (1.00)	0.142 (1.00)	6.17e-08 (2.96e-05)	0.328 (1.00)	0.851 (1.00)	0.712 (1.00)	0.00456 (1.00)	0.0657 (1.00)	0.819 (1.00)	0.406 (1.00)	0.314 (1.00)	0.0746 (1.00)
8q	99 (61%)	63	0.116 (1.00)	0.229 (1.00)	1.03e-06 (0.000496)	0.0417 (1.00)	0.574 (1.00)	0.698 (1.00)	0.0444 (1.00)	0.0748 (1.00)	0.362 (1.00)	0.409 (1.00)	0.812 (1.00)	0.173 (1.00)
18p	133 (82%)	29	0.0761 (1.00)	0.244 (1.00)	0.000159 (0.0747)	0.0354 (1.00)	0.799 (1.00)	0.442 (1.00)	0.434 (1.00)	0.162 (1.00)	0.0685 (1.00)	0.0324 (1.00)	0.248 (1.00)	0.905 (1.00)
18q	141 (87%)	21	0.0345 (1.00)	0.0904 (1.00)	3.82e-05 (0.0181)	0.152 (1.00)	1 (1.00)	0.902 (1.00)	0.627 (1.00)	0.207 (1.00)	0.0931 (1.00)	0.0389 (1.00)	0.012 (1.00)	0.859 (1.00)
19p	53 (33%)	109	0.0415 (1.00)	0.0562 (1.00)	4.95e-05 (0.0235)	0.109 (1.00)	0.821 (1.00)	0.629 (1.00)	0.941 (1.00)	0.831 (1.00)	0.034 (1.00)	0.162 (1.00)	0.954 (1.00)	0.743 (1.00)
1p	56 (35%)	106	0.602 (1.00)	0.0373 (1.00)	0.00124 (0.581)	0.288 (1.00)	0.576 (1.00)	0.712 (1.00)	0.83 (1.00)	0.941 (1.00)	0.501 (1.00)	0.467 (1.00)	0.729 (1.00)	0.975 (1.00)
1q	57 (35%)	105	0.602 (1.00)	0.291 (1.00)	0.0116 (1.00)	0.46 (1.00)	0.286 (1.00)	0.687 (1.00)	0.877 (1.00)	0.902 (1.00)	0.205 (1.00)	0.472 (1.00)	0.365 (1.00)	0.896 (1.00)
2p	50 (31%)	112	0.894 (1.00)	0.18 (1.00)	0.0105 (1.00)	0.212 (1.00)	0.603 (1.00)	0.987 (1.00)	0.271 (1.00)	0.35 (1.00)	0.566 (1.00)	0.0823 (1.00)	0.951 (1.00)	0.0183 (1.00)
2q	47 (29%)	115	0.242 (1.00)	0.18 (1.00)	0.00706 (1.00)	0.113 (1.00)	0.266 (1.00)	0.839 (1.00)	0.0659 (1.00)	0.0834 (1.00)	0.181 (1.00)	0.306 (1.00)	0.455 (1.00)	0.0107 (1.00)
3p	42 (26%)	120	1 (1.00)	0.537 (1.00)	0.37 (1.00)	0.576 (1.00)	0.106 (1.00)	0.0796 (1.00)	0.176 (1.00)	0.228 (1.00)	0.0917 (1.00)	0.115 (1.00)	0.513 (1.00)	0.733 (1.00)
3q	44 (27%)	118	0.868 (1.00)	0.927 (1.00)	0.24 (1.00)	0.555 (1.00)	0.244 (1.00)	0.176 (1.00)	0.268 (1.00)	0.568 (1.00)	0.0742 (1.00)	0.182 (1.00)	0.822 (1.00)	0.978 (1.00)
5p	60 (37%)	102	0.216 (1.00)	0.329 (1.00)	0.0125 (1.00)	0.0331 (1.00)	0.854 (1.00)	0.373 (1.00)	0.217 (1.00)	0.201 (1.00)	0.88 (1.00)	0.435 (1.00)	1 (1.00)	0.939 (1.00)
5q	62 (38%)	100	0.0883 (1.00)	0.0048 (1.00)	0.00139 (0.646)	0.0899 (1.00)	0.434 (1.00)	0.74 (1.00)	0.266 (1.00)	0.456 (1.00)	0.906 (1.00)	0.296 (1.00)	0.931 (1.00)	0.969 (1.00)
6p	53 (33%)	109	0.897 (1.00)	0.607 (1.00)	0.00273 (1.00)	0.0235 (1.00)	0.606 (1.00)	0.85 (1.00)	0.886 (1.00)	0.828 (1.00)	0.435 (1.00)	0.818 (1.00)	0.17 (1.00)	0.941 (1.00)
6q	57 (35%)	105	0.286 (1.00)	0.348 (1.00)	0.00954 (1.00)	0.143 (1.00)	0.56 (1.00)	0.743 (1.00)	0.808 (1.00)	0.584 (1.00)	0.617 (1.00)	0.816 (1.00)	0.329 (1.00)	0.472 (1.00)
9p	64 (40%)	98	0.179 (1.00)	0.549 (1.00)	0.149 (1.00)	0.0492 (1.00)	0.84 (1.00)	0.395 (1.00)	0.762 (1.00)	0.853 (1.00)	0.137 (1.00)	0.129 (1.00)	1 (1.00)	0.159 (1.00)
9q	55 (34%)	107	0.264 (1.00)	0.648 (1.00)	0.337 (1.00)	0.164 (1.00)	0.868 (1.00)	0.499 (1.00)	0.954 (1.00)	1 (1.00)	0.208 (1.00)	0.312 (1.00)	1 (1.00)	0.229 (1.00)
10p	44 (27%)	118	0.276 (1.00)	0.0644 (1.00)	0.185 (1.00)	0.311 (1.00)	0.208 (1.00)	0.13 (1.00)	0.164 (1.00)	0.179 (1.00)	0.841 (1.00)	0.597 (1.00)	0.8 (1.00)	0.412 (1.00)
10q	43 (27%)	119	0.353 (1.00)	0.58 (1.00)	0.0549 (1.00)	0.196 (1.00)	0.173 (1.00)	0.0513 (1.00)	0.0724 (1.00)	0.108 (1.00)	0.612 (1.00)	0.517 (1.00)	0.802 (1.00)	0.334 (1.00)
11p	54 (33%)	108	0.28 (1.00)	0.167 (1.00)	0.0931 (1.00)	0.89 (1.00)	0.459 (1.00)	0.738 (1.00)	0.491 (1.00)	0.389 (1.00)	0.22 (1.00)	0.115 (1.00)	0.0122 (1.00)	0.0975 (1.00)
11q	55 (34%)	107	0.0655 (1.00)	0.0816 (1.00)	0.0487 (1.00)	0.391 (1.00)	0.252 (1.00)	0.574 (1.00)	0.611 (1.00)	0.402 (1.00)	0.161 (1.00)	0.143 (1.00)	0.111 (1.00)	0.248 (1.00)
12p	55 (34%)	107	0.292 (1.00)	0.777 (1.00)	0.0331 (1.00)	0.295 (1.00)	0.222 (1.00)	0.141 (1.00)	0.647 (1.00)	0.856 (1.00)	0.83 (1.00)	0.936 (1.00)	0.894 (1.00)	0.967 (1.00)
12q	43 (27%)	119	0.446 (1.00)	0.241 (1.00)	0.331 (1.00)	0.57 (1.00)	0.239 (1.00)	0.206 (1.00)	0.876 (1.00)	0.581 (1.00)	0.764 (1.00)	0.583 (1.00)	0.837 (1.00)	0.678 (1.00)
14q	73 (45%)	89	0.28 (1.00)	0.627 (1.00)	0.00207 (0.961)	0.574 (1.00)	0.814 (1.00)	0.211 (1.00)	0.952 (1.00)	0.694 (1.00)	0.14 (1.00)	0.292 (1.00)	0.47 (1.00)	0.798 (1.00)
15q	75 (46%)	87	0.422 (1.00)	0.0221 (1.00)	0.00459 (1.00)	0.957 (1.00)	0.158 (1.00)	0.25 (1.00)	0.635 (1.00)	0.481 (1.00)	0.612 (1.00)	1 (1.00)	0.9 (1.00)	0.809 (1.00)
16p	48 (30%)	114	0.248 (1.00)	0.54 (1.00)	0.00798 (1.00)	0.424 (1.00)	0.668 (1.00)	0.983 (1.00)	0.486 (1.00)	0.892 (1.00)	0.0838 (1.00)	0.313 (1.00)	0.0954 (1.00)	0.325 (1.00)
16q	53 (33%)	109	0.409 (1.00)	0.436 (1.00)	0.000656 (0.307)	0.72 (1.00)	0.74 (1.00)	0.907 (1.00)	0.42 (1.00)	0.734 (1.00)	0.147 (1.00)	0.0934 (1.00)	0.074 (1.00)	0.125 (1.00)
17p	112 (69%)	50	0.0663 (1.00)	0.128 (1.00)	0.0141 (1.00)	0.546 (1.00)	0.901 (1.00)	0.559 (1.00)	0.362 (1.00)	0.699 (1.00)	0.994 (1.00)	0.3 (1.00)	0.802 (1.00)	0.694 (1.00)
17q	55 (34%)	107	0.447 (1.00)	1 (1.00)	0.028 (1.00)	0.182 (1.00)	1 (1.00)	0.88 (1.00)	0.61 (1.00)	0.427 (1.00)	0.204 (1.00)	0.698 (1.00)	0.756 (1.00)	0.995 (1.00)
19q	51 (31%)	111	0.14 (1.00)	0.169 (1.00)	0.00249 (1.00)	0.0621 (1.00)	0.799 (1.00)	0.656 (1.00)	0.964 (1.00)	0.791 (1.00)	0.0526 (1.00)	0.183 (1.00)	0.634 (1.00)	0.241 (1.00)
20p	129 (80%)	33	0.0323 (1.00)	0.171 (1.00)	0.152 (1.00)	0.282 (1.00)	0.42 (1.00)	0.966 (1.00)	0.523 (1.00)	0.0245 (1.00)	0.0803 (1.00)	0.362 (1.00)	0.0579 (1.00)	0.249 (1.00)
20q	143 (88%)	19	0.00777 (1.00)	0.376 (1.00)	0.00192 (0.889)	0.138 (1.00)	0.194 (1.00)	0.0766 (1.00)	0.652 (1.00)	0.00136 (0.635)	0.136 (1.00)	0.143 (1.00)	0.338 (1.00)	0.369 (1.00)
21q	76 (47%)	86	0.422 (1.00)	0.111 (1.00)	0.00813 (1.00)	0.937 (1.00)	1 (1.00)	0.247 (1.00)	0.926 (1.00)	0.771 (1.00)	0.242 (1.00)	0.213 (1.00)	0.651 (1.00)	0.274 (1.00)
22q	66 (41%)	96	0.538 (1.00)	0.0784 (1.00)	0.00979 (1.00)	0.617 (1.00)	0.519 (1.00)	0.754 (1.00)	0.228 (1.00)	0.434 (1.00)	0.014 (1.00)	0.46 (1.00)	0.431 (1.00)	0.404 (1.00)
xq	57 (35%)	105	0.286 (1.00)	0.397 (1.00)	0.0474 (1.00)	0.356 (1.00)	0.782 (1.00)	0.647 (1.00)	0.387 (1.00)	0.914 (1.00)	0.997 (1.00)	0.705 (1.00)	0.487 (1.00)	0.493 (1.00)

'4p' versus 'CN_CNMF'

P value = 9e-05 (Chi-square test), Q value = 0.042

Table S1. Gene #7: '4p' versus Molecular Subtype #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5	CLUS_6
ALL	10	34	42	30	24	22
4P MUTATED	4	15	8	17	18	5
4P WILD-TYPE	6	19	34	13	6	17

Figure S1. Get High-res Image Gene #7: '4p' versus Molecular Subtype #3: 'CN_CNMF'

'4q' versus 'CN_CNMF'

P value = 1.49e-05 (Chi-square test), Q value = 0.0071

Table S2. Gene #8: '4q' versus Molecular Subtype #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5	CLUS_6
ALL	10	34	42	30	24	22
4Q MUTATED	5	17	7	18	18	5
4Q WILD-TYPE	5	17	35	12	6	17

Figure S2. Get High-res Image Gene #8: '4q' versus Molecular Subtype #3: 'CN_CNMF'

'7p' versus 'CN_CNMF'

P value = 2.58e-05 (Chi-square test), Q value = 0.012

Table S3. Gene #13: '7p' versus Molecular Subtype #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5	CLUS_6
ALL	10	34	42	30	24	22
7P MUTATED	7	31	16	14	18	16
7P WILD-TYPE	3	3	26	16	6	6

Figure S3. Get High-res Image Gene #13: '7p' versus Molecular Subtype #3: 'CN_CNMF'

'7p' versus 'MRNASEQ_CHIERARCHICAL'

P value = 7.32e-05 (Fisher's exact test), Q value = 0.035

Table S4. Gene #13: '7p' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	66	7	50	31
7P MUTATED	38	1	43	17
7P WILD-TYPE	28	6	7	14

Figure S4. Get High-res Image Gene #13: '7p' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

'7q' versus 'CN_CNMF'

P value = 0.000171 (Chi-square test), Q value = 0.08

Table S5. Gene #14: '7q' versus Molecular Subtype #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5	CLUS_6
ALL	10	34	42	30	24	22
7Q MUTATED	4	25	13	11	18	15
7Q WILD-TYPE	6	9	29	19	6	7

Figure S5. Get High-res Image Gene #14: '7q' versus Molecular Subtype #3: 'CN_CNMF'

'8p' versus 'CN_CNMF'

P value = 6.17e-08 (Chi-square test), Q value = 3e-05

Table S6. Gene #15: '8p' versus Molecular Subtype #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5	CLUS_6
ALL	10	34	42	30	24	22
8P MUTATED	7	28	14	25	18	22
8P WILD-TYPE	3	6	28	5	6	0

Figure S6. Get High-res Image Gene #15: '8p' versus Molecular Subtype #3: 'CN_CNMF'

'8q' versus 'CN_CNMF'

P value = 1.03e-06 (Chi-square test), Q value = 5e-04

Table S7. Gene #16: '8q' versus Molecular Subtype #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5	CLUS_6
ALL	10	34	42	30	24	22
8Q MUTATED	7	24	12	21	13	22
8Q WILD-TYPE	3	10	30	9	11	0

Figure S7. Get High-res Image Gene #16: '8q' versus Molecular Subtype #3: 'CN_CNMF'

'13q' versus 'CN_CNMF'

P value = 1.81e-05 (Chi-square test), Q value = 0.0086

Table S8. Gene #25: '13q' versus Molecular Subtype #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5	CLUS_6
ALL	10	34	42	30	24	22
13Q MUTATED	8	28	19	20	24	19
13Q WILD-TYPE	2	6	23	10	0	3

Figure S8. Get High-res Image Gene #25: '13q' versus Molecular Subtype #3: 'CN_CNMF'

'13q' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000172 (Fisher's exact test), Q value = 0.081

Table S9. Gene #25: '13q' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	66	7	50	31
13Q MUTATED	46	0	41	25
13Q WILD-TYPE	20	7	9	6

Figure S9. Get High-res Image Gene #25: '13q' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

'18p' versus 'CN_CNMF'

P value = 0.000159 (Chi-square test), Q value = 0.075

Table S10. Gene #32: '18p' versus Molecular Subtype #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5	CLUS_6
ALL	10	34	42	30	24	22
18P MUTATED	10	33	25	24	20	21
18P WILD-TYPE	0	1	17	6	4	1

Figure S10. Get High-res Image Gene #32: '18p' versus Molecular Subtype #3: 'CN_CNMF'

'18q' versus 'CN_CNMF'

P value = 3.82e-05 (Chi-square test), Q value = 0.018

Table S11. Gene #33: '18q' versus Molecular Subtype #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5	CLUS_6
ALL	10	34	42	30	24	22
18Q MUTATED	10	34	27	27	22	21
18Q WILD-TYPE	0	0	15	3	2	1

Figure S11. Get High-res Image Gene #33: '18q' versus Molecular Subtype #3: 'CN_CNMF'

'19p' versus 'CN_CNMF'

P value = 4.95e-05 (Chi-square test), Q value = 0.023

Table S12. Gene #34: '19p' versus Molecular Subtype #3: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5	CLUS_6
ALL	10	34	42	30	24	22
19P MUTATED	4	22	4	10	8	5
19P WILD-TYPE	6	12	38	20	16	17

Figure S12. Get High-res Image Gene #34: '19p' versus Molecular Subtype #3: 'CN_CNMF'

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Molecular subtype file = READ-TP.transferedmergedcluster.txt
Number of patients = 162
Number of significantly focal cnvs = 40
Number of molecular subtypes = 12
Exclude genes that fewer than K tumors have alterations, 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)

Made with Nozzle