Correlation between copy number variations of arm-level result and selected clinical features
Pheochromocytoma and Paraganglioma (Primary solid tumor)
15 July 2014 | analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C16M35NV
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 selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C16M35NV
Overview
Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.

Summary

Testing the association between copy number variation 43 arm-level events and 3 clinical features across 57 patients, no significant finding detected with Q value < 0.25.

- No arm-level cnvs related to clinical features.

Results
Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 43 arm-level events and 3 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, no significant finding detected.

|  | Clinical Features | AGE | GENDER | RACE
| nCNV (%) | nWild-Type | Wilcoxon-test | Fisher's exact test | Fisher's exact test
1p gain | 3 (5%) | 54 | 0.217 (1.00) | 0.279 (1.00) |
1q gain | 6 (11%) | 51 | 0.907 (1.00) | 1 (1.00) | 1 (1.00)
5p gain | 3 (5%) | 54 | 0.334 (1.00) | 0.545 (1.00) | 1 (1.00)
5q gain | 3 (5%) | 54 | 1 (1.00) | 0.545 (1.00) | 1 (1.00)
7p gain | 11 (19%) | 46 | 0.856 (1.00) | 0.168 (1.00) | 0.556 (1.00)
7q gain | 9 (16%) | 48 | 0.991 (1.00) | 0.0536 (1.00) | 0.614 (1.00)
8p gain | 5 (9%) | 52 | 0.778 (1.00) | 0.647 (1.00) | 0.647 (1.00)
8q gain | 6 (11%) | 51 | 0.658 (1.00) | 1 (1.00) | 1 (1.00)
10p gain | 5 (9%) | 52 | 0.0515 (1.00) | 1 (1.00) | 1 (1.00)
10q gain | 5 (9%) | 52 | 0.0515 (1.00) | 1 (1.00) | 1 (1.00)
12p gain | 4 (7%) | 53 | 0.888 (1.00) | 1 (1.00) | 1 (1.00)
12q gain | 5 (9%) | 52 | 0.544 (1.00) | 0.647 (1.00) | 1 (1.00)
13q gain | 4 (7%) | 53 | 0.731 (1.00) | 0.607 (1.00) | 1 (1.00)
18p gain | 3 (5%) | 54 | 0.0829 (1.00) | 1 (1.00) | 1 (1.00)
18q gain | 5 (9%) | 52 | 0.767 (1.00) | 0.647 (1.00) | 1 (1.00)
19p gain | 7 (12%) | 50 | 0.609 (1.00) | 1 (1.00) | 0.718 (1.00)
19q gain | 5 (9%) | 52 | 0.429 (1.00) | 1 (1.00) | 1 (1.00)
20p gain | 4 (7%) | 53 | 0.9 (1.00) | 0.607 (1.00) | 1 (1.00)
20q gain | 3 (5%) | 54 | 0.453 (1.00) | 0.279 (1.00) | 1 (1.00)
1p loss | 33 (58%) | 24 | 0.378 (1.00) | 0.411 (1.00) | 0.836 (1.00)
1q loss | 5 (9%) | 52 | 0.438 (1.00) | 1 (1.00) | 0.645 (1.00)
2p loss | 3 (5%) | 54 | 0.391 (1.00) | 1 (1.00) | 0.461 (1.00)
2q loss | 3 (5%) | 54 | 0.734 (1.00) | 0.279 (1.00) | 0.46 (1.00)
3p loss | 28 (49%) | 29 | 0.774 (1.00) | 0.783 (1.00) | 0.19 (1.00)
3q loss | 39 (68%) | 18 | 0.973 (1.00) | 0.14 (1.00) | 1 (1.00)
4p loss | 5 (9%) | 52 | 0.413 (1.00) | 0.332 (1.00) | 1 (1.00)
4q loss | 6 (11%) | 51 | 0.376 (1.00) | 0.654 (1.00) | 0.705 (1.00)
5p loss | 3 (5%) | 54 | 0.217 (1.00) | 0.279 (1.00) | 1 (1.00)
5q loss | 4 (7%) | 53 | 0.118 (1.00) | 0.607 (1.00) | 0.565 (1.00)
6q loss | 7 (12%) | 50 | 0.111 (1.00) | 0.0447 (1.00) | 1 (1.00)
8p loss | 5 (9%) | 52 | 0.374 (1.00) | 0.647 (1.00) | 0.347 (1.00)
8q loss | 3 (5%) | 54 | 0.0928 (1.00) | 1 (1.00) | 1 (1.00)
9p loss | 4 (7%) | 53 | 0.223 (1.00) | 0.286 (1.00) | 0.562 (1.00)
9q loss | 5 (9%) | 52 | 0.652 (1.00) | 0.151 (1.00) | 0.348 (1.00)
11p loss | 16 (28%) | 41 | 0.763 (1.00) | 0.216 (1.00) | 0.219 (1.00)
11q loss | 16 (28%) | 41 | 0.894 (1.00) | 0.216 (1.00) | 0.693 (1.00)
14q loss | 10 (18%) | 47 | 0.564 (1.00) | 0.298 (1.00) | 1 (1.00)
16p loss | 3 (5%) | 54 | 0.858 (1.00) | 0.279 (1.00) | 1 (1.00)
17p loss | 21 (37%) | 36 | 0.551 (1.00) | 0.778 (1.00) | 0.255 (1.00)
17q loss | 9 (16%) | 48 | 0.801 (1.00) | 0.705 (1.00) | 1 (1.00)
21q loss | 15 (26%) | 42 | 0.793 (1.00) | 0.537 (1.00) | 0.348 (1.00)
22q loss | 23 (40%) | 34 | 0.474 (1.00) | 0.585 (1.00) | 0.458 (1.00)
xq loss | 20 (35%) | 37 | 0.88 (1.00) | 0.383 (1.00) | 0.0283 (1.00)

Methods & Data
Input

- Copy number data file = transformed.cor.cli.txt

- Clinical data file = PCPG-TP.merged_data.txt

- Number of patients = 57

- Number of significantly arm-level cnvs = 43

- Number of selected clinical features = 3

- Exclude regions 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

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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

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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