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

Esophageal Carcinoma (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/C19S1PGQ

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 6 molecular subtypes across 73 patients, 7 significant findings detected with P value < 0.05 and Q value < 0.25.

3p cnv correlated to 'MIRSEQ_CHIERARCHICAL' and 'MIRSEQ_MATURE_CHIERARCHICAL'.
3q cnv correlated to 'CN_CNMF', 'METHLYATION_CNMF', 'MIRSEQ_CNMF', 'MIRSEQ_CHIERARCHICAL', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 40 focal events and 6 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 7 significant findings detected.


		Clinical Features	CN CNMF	METHLYATION CNMF	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
3q	46 (63%)	27	1.48e-06 (0.000354)	8.06e-05 (0.0191)	0.000616 (0.144)	7.73e-05 (0.0185)	0.0041 (0.948)	7.73e-05 (0.0185)
3p	54 (74%)	19	0.0297 (1.00)	0.0134 (1.00)	0.00183 (0.425)	0.000202 (0.0477)	0.0211 (1.00)	0.000202 (0.0477)
1p	23 (32%)	50	0.745 (1.00)	0.927 (1.00)	1 (1.00)	1 (1.00)	0.142 (1.00)	1 (1.00)
1q	36 (49%)	37	0.0298 (1.00)	0.534 (1.00)	0.272 (1.00)	0.183 (1.00)	0.061 (1.00)	0.183 (1.00)
2p	32 (44%)	41	0.206 (1.00)	0.59 (1.00)	0.181 (1.00)	0.536 (1.00)	0.0307 (1.00)	0.536 (1.00)
2q	27 (37%)	46	0.529 (1.00)	0.605 (1.00)	0.662 (1.00)	0.634 (1.00)	0.219 (1.00)	0.634 (1.00)
4p	48 (66%)	25	0.108 (1.00)	0.615 (1.00)	0.405 (1.00)	0.0809 (1.00)	0.658 (1.00)	0.0809 (1.00)
4q	40 (55%)	33	0.0166 (1.00)	0.518 (1.00)	0.722 (1.00)	0.321 (1.00)	0.915 (1.00)	0.321 (1.00)
5p	51 (70%)	22	0.872 (1.00)	0.339 (1.00)	0.0705 (1.00)	0.258 (1.00)	0.292 (1.00)	0.258 (1.00)
5q	42 (58%)	31	0.936 (1.00)	0.253 (1.00)	0.295 (1.00)	0.184 (1.00)	0.275 (1.00)	0.184 (1.00)
6p	27 (37%)	46	0.0918 (1.00)	0.481 (1.00)	0.717 (1.00)	0.634 (1.00)	0.377 (1.00)	0.634 (1.00)
6q	24 (33%)	49	0.0442 (1.00)	0.373 (1.00)	0.452 (1.00)	0.362 (1.00)	0.779 (1.00)	0.362 (1.00)
7p	53 (73%)	20	0.616 (1.00)	0.467 (1.00)	0.434 (1.00)	0.187 (1.00)	0.546 (1.00)	0.187 (1.00)
7q	44 (60%)	29	1 (1.00)	1 (1.00)	0.558 (1.00)	0.244 (1.00)	0.181 (1.00)	0.244 (1.00)
8p	56 (77%)	17	0.491 (1.00)	0.152 (1.00)	0.612 (1.00)	0.128 (1.00)	0.536 (1.00)	0.128 (1.00)
8q	51 (70%)	22	0.71 (1.00)	0.267 (1.00)	0.757 (1.00)	0.329 (1.00)	0.888 (1.00)	0.329 (1.00)
9p	49 (67%)	24	0.581 (1.00)	0.373 (1.00)	0.559 (1.00)	0.186 (1.00)	0.589 (1.00)	0.186 (1.00)
9q	40 (55%)	33	0.642 (1.00)	0.114 (1.00)	0.319 (1.00)	0.0913 (1.00)	0.251 (1.00)	0.0913 (1.00)
10p	36 (49%)	37	0.868 (1.00)	0.234 (1.00)	0.0916 (1.00)	0.553 (1.00)	0.319 (1.00)	0.553 (1.00)
10q	35 (48%)	38	0.112 (1.00)	0.00141 (0.328)	0.0292 (1.00)	0.00932 (1.00)	0.0494 (1.00)	0.00932 (1.00)
11p	37 (51%)	36	0.348 (1.00)	0.431 (1.00)	0.55 (1.00)	0.553 (1.00)	0.573 (1.00)	0.553 (1.00)
11q	40 (55%)	33	0.072 (1.00)	0.801 (1.00)	0.932 (1.00)	0.747 (1.00)	0.402 (1.00)	0.747 (1.00)
12p	46 (63%)	27	0.468 (1.00)	0.529 (1.00)	0.154 (1.00)	0.428 (1.00)	0.641 (1.00)	0.428 (1.00)
12q	33 (45%)	40	0.382 (1.00)	0.921 (1.00)	0.429 (1.00)	0.719 (1.00)	0.667 (1.00)	0.719 (1.00)
13q	46 (63%)	27	0.603 (1.00)	0.511 (1.00)	0.752 (1.00)	0.397 (1.00)	0.781 (1.00)	0.397 (1.00)
14q	40 (55%)	33	0.82 (1.00)	0.619 (1.00)	0.5 (1.00)	0.615 (1.00)	0.884 (1.00)	0.615 (1.00)
15q	32 (44%)	41	0.77 (1.00)	0.0619 (1.00)	0.0929 (1.00)	0.116 (1.00)	0.366 (1.00)	0.116 (1.00)
16p	34 (47%)	39	0.612 (1.00)	1 (1.00)	0.932 (1.00)	1 (1.00)	0.716 (1.00)	1 (1.00)
16q	32 (44%)	41	0.59 (1.00)	0.848 (1.00)	0.187 (1.00)	0.819 (1.00)	0.424 (1.00)	0.819 (1.00)
17p	41 (56%)	32	0.209 (1.00)	0.0591 (1.00)	0.0642 (1.00)	0.0347 (1.00)	0.0718 (1.00)	0.0347 (1.00)
17q	29 (40%)	44	0.691 (1.00)	0.735 (1.00)	0.283 (1.00)	1 (1.00)	0.325 (1.00)	1 (1.00)
18p	49 (67%)	24	0.0188 (1.00)	0.462 (1.00)	0.476 (1.00)	0.492 (1.00)	0.587 (1.00)	0.492 (1.00)
18q	49 (67%)	24	0.557 (1.00)	0.104 (1.00)	0.0929 (1.00)	0.0973 (1.00)	0.0457 (1.00)	0.0973 (1.00)
19p	37 (51%)	36	0.131 (1.00)	0.0708 (1.00)	0.018 (1.00)	0.553 (1.00)	0.014 (1.00)	0.553 (1.00)
19q	36 (49%)	37	0.573 (1.00)	0.124 (1.00)	0.0525 (1.00)	0.681 (1.00)	0.0368 (1.00)	0.681 (1.00)
20p	48 (66%)	25	0.668 (1.00)	0.741 (1.00)	0.11 (1.00)	0.174 (1.00)	0.779 (1.00)	0.174 (1.00)
20q	45 (62%)	28	0.138 (1.00)	0.23 (1.00)	0.0394 (1.00)	0.0153 (1.00)	0.18 (1.00)	0.0153 (1.00)
21q	52 (71%)	21	0.623 (1.00)	0.0884 (1.00)	0.228 (1.00)	0.0665 (1.00)	0.408 (1.00)	0.0665 (1.00)
22q	43 (59%)	30	0.355 (1.00)	0.841 (1.00)	0.418 (1.00)	0.11 (1.00)	0.662 (1.00)	0.11 (1.00)
xq	36 (49%)	37	0.717 (1.00)	0.415 (1.00)	0.915 (1.00)	1 (1.00)	0.712 (1.00)	1 (1.00)

'3p' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000202 (Fisher's exact test), Q value = 0.048

Table S1. Gene #5: '3p' versus Molecular Subtype #4: 'MIRSEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	1	28	43
3P MUTATED	0	15	39
3P WILD-TYPE	1	13	4

Figure S1. Get High-res Image Gene #5: '3p' versus Molecular Subtype #4: 'MIRSEQ_CHIERARCHICAL'

'3p' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.000202 (Fisher's exact test), Q value = 0.048

Table S2. Gene #5: '3p' versus Molecular Subtype #6: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	1	28	43
3P MUTATED	0	15	39
3P WILD-TYPE	1	13	4

Figure S2. Get High-res Image Gene #5: '3p' versus Molecular Subtype #6: 'MIRSEQ_MATURE_CHIERARCHICAL'

'3q' versus 'CN_CNMF'

P value = 1.48e-06 (Fisher's exact test), Q value = 0.00035

Table S3. Gene #6: '3q' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	15	34	24
3Q MUTATED	13	11	22
3Q WILD-TYPE	2	23	2

Figure S3. Get High-res Image Gene #6: '3q' versus Molecular Subtype #1: 'CN_CNMF'

'3q' versus 'METHLYATION_CNMF'

P value = 8.06e-05 (Fisher's exact test), Q value = 0.019

Table S4. Gene #6: '3q' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	34	15	24
3Q MUTATED	30	7	9
3Q WILD-TYPE	4	8	15

Figure S4. Get High-res Image Gene #6: '3q' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'3q' versus 'MIRSEQ_CNMF'

P value = 0.000616 (Fisher's exact test), Q value = 0.14

Table S5. Gene #6: '3q' versus Molecular Subtype #3: 'MIRSEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	30	14	28
3Q MUTATED	25	10	10
3Q WILD-TYPE	5	4	18

Figure S5. Get High-res Image Gene #6: '3q' versus Molecular Subtype #3: 'MIRSEQ_CNMF'

'3q' versus 'MIRSEQ_CHIERARCHICAL'

P value = 7.73e-05 (Fisher's exact test), Q value = 0.018

Table S6. Gene #6: '3q' versus Molecular Subtype #4: 'MIRSEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	1	28	43
3Q MUTATED	0	10	35
3Q WILD-TYPE	1	18	8

Figure S6. Get High-res Image Gene #6: '3q' versus Molecular Subtype #4: 'MIRSEQ_CHIERARCHICAL'

'3q' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 7.73e-05 (Fisher's exact test), Q value = 0.018

Table S7. Gene #6: '3q' versus Molecular Subtype #6: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	1	28	43
3Q MUTATED	0	10	35
3Q WILD-TYPE	1	18	8

Figure S7. Get High-res Image Gene #6: '3q' versus Molecular Subtype #6: 'MIRSEQ_MATURE_CHIERARCHICAL'

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Molecular subtype file = ESCA-TP.transferedmergedcluster.txt
Number of patients = 73
Number of significantly focal cnvs = 40
Number of molecular subtypes = 6
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

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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