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

Uterine Carcinosarcoma (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/C1K35S4K

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 8 molecular subtypes across 56 patients, one significant finding detected with P value < 0.05 and Q value < 0.25.

4q cnv correlated to 'MIRSEQ_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 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, one significant finding 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	Chi-square test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
4q	36 (64%)	20	0.0319 (1.00)	0.021 (1.00)	0.0175 (1.00)	0.0483 (1.00)	0.000546 (0.175)	0.116 (1.00)	0.0577 (1.00)	0.116 (1.00)
1p	33 (59%)	23	0.175 (1.00)	0.612 (1.00)	0.69 (1.00)	0.549 (1.00)	0.496 (1.00)	0.83 (1.00)	0.667 (1.00)	0.444 (1.00)
1q	40 (71%)	16	0.866 (1.00)	0.549 (1.00)	0.767 (1.00)	0.842 (1.00)	0.868 (1.00)	0.604 (1.00)	0.833 (1.00)	0.428 (1.00)
2p	25 (45%)	31	0.606 (1.00)	0.0432 (1.00)	0.219 (1.00)	0.144 (1.00)	0.364 (1.00)	0.0479 (1.00)	0.245 (1.00)	0.0308 (1.00)
2q	23 (41%)	33	0.758 (1.00)	0.0468 (1.00)	0.116 (1.00)	0.341 (1.00)	0.411 (1.00)	0.0395 (1.00)	0.312 (1.00)	0.0293 (1.00)
3p	32 (57%)	24	0.35 (1.00)	0.105 (1.00)	0.335 (1.00)	0.123 (1.00)	0.531 (1.00)	0.765 (1.00)	0.729 (1.00)	0.825 (1.00)
3q	37 (66%)	19	0.693 (1.00)	0.107 (1.00)	0.0669 (1.00)	0.0514 (1.00)	0.1 (1.00)	0.0828 (1.00)	0.302 (1.00)	0.0817 (1.00)
4p	40 (71%)	16	0.0507 (1.00)	0.0815 (1.00)	0.0577 (1.00)	0.09 (1.00)	0.00932 (1.00)	0.198 (1.00)	0.246 (1.00)	0.169 (1.00)
5p	32 (57%)	24	0.709 (1.00)	0.913 (1.00)	0.352 (1.00)	0.447 (1.00)	0.862 (1.00)	0.699 (1.00)	0.834 (1.00)	0.366 (1.00)
5q	26 (46%)	30	0.792 (1.00)	0.386 (1.00)	0.791 (1.00)	0.261 (1.00)	0.525 (1.00)	0.327 (1.00)	0.0666 (1.00)	0.183 (1.00)
6p	35 (62%)	21	0.0884 (1.00)	0.425 (1.00)	0.886 (1.00)	0.661 (1.00)	0.959 (1.00)	0.298 (1.00)	0.935 (1.00)	0.579 (1.00)
6q	34 (61%)	22	0.0229 (1.00)	0.248 (1.00)	0.937 (1.00)	0.57 (1.00)	0.866 (1.00)	1 (1.00)	0.509 (1.00)	0.779 (1.00)
7p	34 (61%)	22	0.248 (1.00)	0.164 (1.00)	0.323 (1.00)	0.165 (1.00)	0.959 (1.00)	0.755 (1.00)	0.935 (1.00)	0.795 (1.00)
7q	30 (54%)	26	0.428 (1.00)	0.553 (1.00)	0.286 (1.00)	0.406 (1.00)	0.924 (1.00)	0.601 (1.00)	0.854 (1.00)	0.513 (1.00)
8p	42 (75%)	14	0.449 (1.00)	0.542 (1.00)	0.094 (1.00)	0.646 (1.00)	0.204 (1.00)	0.723 (1.00)	0.309 (1.00)	0.51 (1.00)
8q	39 (70%)	17	0.116 (1.00)	0.165 (1.00)	0.0553 (1.00)	0.531 (1.00)	0.251 (1.00)	0.643 (1.00)	0.156 (1.00)	0.457 (1.00)
9p	40 (71%)	16	0.177 (1.00)	0.0407 (1.00)	0.82 (1.00)	0.849 (1.00)	0.568 (1.00)	1 (1.00)	0.833 (1.00)	0.641 (1.00)
9q	41 (73%)	15	0.166 (1.00)	0.00528 (1.00)	1 (1.00)	0.813 (1.00)	0.636 (1.00)	1 (1.00)	0.935 (1.00)	0.78 (1.00)
10p	44 (79%)	12	0.91 (1.00)	0.202 (1.00)	0.147 (1.00)	0.413 (1.00)	0.33 (1.00)	0.0957 (1.00)	0.892 (1.00)	0.165 (1.00)
10q	38 (68%)	18	1 (1.00)	0.0116 (1.00)	0.0439 (1.00)	0.21 (1.00)	0.882 (1.00)	0.333 (1.00)	0.53 (1.00)	0.481 (1.00)
11p	31 (55%)	25	0.837 (1.00)	0.0912 (1.00)	0.42 (1.00)	0.496 (1.00)	0.329 (1.00)	0.241 (1.00)	0.651 (1.00)	0.3 (1.00)
11q	31 (55%)	25	0.837 (1.00)	0.0427 (1.00)	0.304 (1.00)	0.145 (1.00)	0.329 (1.00)	0.241 (1.00)	0.568 (1.00)	0.3 (1.00)
12p	35 (62%)	21	0.409 (1.00)	0.129 (1.00)	0.0174 (1.00)	0.0306 (1.00)	0.678 (1.00)	0.269 (1.00)	0.418 (1.00)	0.666 (1.00)
12q	25 (45%)	31	0.682 (1.00)	0.947 (1.00)	0.479 (1.00)	0.578 (1.00)	0.934 (1.00)	0.73 (1.00)	0.412 (1.00)	0.455 (1.00)
13q	41 (73%)	15	0.914 (1.00)	0.484 (1.00)	1 (1.00)	0.622 (1.00)	0.958 (1.00)	0.574 (1.00)	0.967 (1.00)	1 (1.00)
14q	34 (61%)	22	0.681 (1.00)	0.377 (1.00)	0.628 (1.00)	0.0768 (1.00)	0.862 (1.00)	1 (1.00)	0.611 (1.00)	0.671 (1.00)
15q	36 (64%)	20	0.0212 (1.00)	0.535 (1.00)	0.495 (1.00)	0.54 (1.00)	1 (1.00)	1 (1.00)	0.628 (1.00)	1 (1.00)
16p	42 (75%)	14	0.356 (1.00)	0.298 (1.00)	0.795 (1.00)	0.835 (1.00)	0.645 (1.00)	0.704 (1.00)	0.188 (1.00)	1 (1.00)
16q	43 (77%)	13	0.649 (1.00)	0.814 (1.00)	0.922 (1.00)	0.831 (1.00)	0.801 (1.00)	1 (1.00)	0.278 (1.00)	1 (1.00)
17p	43 (77%)	13	0.742 (1.00)	0.0782 (1.00)	0.922 (1.00)	0.248 (1.00)	0.892 (1.00)	0.546 (1.00)	1 (1.00)	0.757 (1.00)
17q	35 (62%)	21	1 (1.00)	0.104 (1.00)	0.323 (1.00)	0.031 (1.00)	0.222 (1.00)	0.269 (1.00)	0.63 (1.00)	0.666 (1.00)
18p	36 (64%)	20	0.725 (1.00)	0.304 (1.00)	1 (1.00)	0.308 (1.00)	0.719 (1.00)	0.264 (1.00)	0.932 (1.00)	0.266 (1.00)
18q	34 (61%)	22	0.593 (1.00)	0.819 (1.00)	0.86 (1.00)	0.138 (1.00)	0.319 (1.00)	0.132 (1.00)	0.611 (1.00)	0.147 (1.00)
19p	39 (70%)	17	0.843 (1.00)	0.208 (1.00)	0.806 (1.00)	0.796 (1.00)	0.212 (1.00)	0.756 (1.00)	0.374 (1.00)	0.532 (1.00)
19q	41 (73%)	15	0.392 (1.00)	0.0702 (1.00)	0.732 (1.00)	0.338 (1.00)	0.0867 (1.00)	0.723 (1.00)	0.0687 (1.00)	0.51 (1.00)
20p	44 (79%)	12	0.49 (1.00)	0.73 (1.00)	0.271 (1.00)	0.488 (1.00)	0.801 (1.00)	0.546 (1.00)	0.783 (1.00)	0.757 (1.00)
20q	48 (86%)	8	0.604 (1.00)	0.761 (1.00)	0.0414 (1.00)	0.394 (1.00)	0.179 (1.00)	0.261 (1.00)	0.148 (1.00)	0.369 (1.00)
21q	35 (62%)	21	0.553 (1.00)	0.574 (1.00)	0.563 (1.00)	0.563 (1.00)	0.854 (1.00)	0.546 (1.00)	0.912 (1.00)	0.308 (1.00)
22q	41 (73%)	15	0.793 (1.00)	0.883 (1.00)	0.384 (1.00)	0.501 (1.00)	0.795 (1.00)	0.574 (1.00)	0.596 (1.00)	0.524 (1.00)
xq	33 (59%)	23	0.499 (1.00)	0.137 (1.00)	0.925 (1.00)	0.364 (1.00)	0.625 (1.00)	0.332 (1.00)	0.667 (1.00)	0.384 (1.00)

'4q' versus 'MIRSEQ_CNMF'

P value = 0.000546 (Fisher's exact test), Q value = 0.17

Table S1. Gene #8: '4q' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	10	22	4	19
4Q MUTATED	10	17	0	9
4Q WILD-TYPE	0	5	4	10

Figure S1. Get High-res Image Gene #8: '4q' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Molecular subtype file = UCS-TP.transferedmergedcluster.txt
Number of patients = 56
Number of significantly focal cnvs = 40
Number of molecular subtypes = 8
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)

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