Thyroid Adenocarcinoma: Correlation between copy number variations of arm-level result and selected clinical features<BR>(primary solid tumor cohort)

Thyroid Adenocarcinoma: Correlation between copy number variations of arm-level result and selected clinical features
(primary solid tumor cohort)

Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)

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 29 arm-level results and 6 clinical features across 214 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 29 arm-level results and 6 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, no significant finding detected.


		Clinical Features	Time to Death	AGE	GENDER	HISTOLOGICAL TYPE	RADIATIONS RADIATION REGIMENINDICATION	RADIATIONEXPOSURE
	nCNV (%)	nWild-Type	logrank test	t-test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
1q gain	6 (3%)	208	1 (1.00)	0.426 (1.00)	0.644 (1.00)	0.285 (1.00)	0.337 (1.00)	1 (1.00)
4p gain	4 (2%)	210	0.0143 (1.00)	0.119 (1.00)	1 (1.00)	0.783 (1.00)	0.239 (1.00)	1 (1.00)
4q gain	4 (2%)	210	0.0143 (1.00)	0.119 (1.00)	1 (1.00)	0.783 (1.00)	0.239 (1.00)	1 (1.00)
5p gain	7 (3%)	207	0.0143 (1.00)	0.0768 (1.00)	1 (1.00)	0.492 (1.00)	0.382 (1.00)	1 (1.00)
5q gain	7 (3%)	207	0.0143 (1.00)	0.0768 (1.00)	1 (1.00)	0.492 (1.00)	0.382 (1.00)	1 (1.00)
7p gain	9 (4%)	205	1 (1.00)	0.0815 (1.00)	1 (1.00)	0.324 (1.00)	1 (1.00)	1 (1.00)
7q gain	11 (5%)	203	1 (1.00)	0.0464 (1.00)	0.734 (1.00)	0.124 (1.00)	1 (1.00)	1 (1.00)
12p gain	7 (3%)	207	1 (1.00)	0.36 (1.00)	0.682 (1.00)	0.492 (1.00)	1 (1.00)	1 (1.00)
12q gain	7 (3%)	207	1 (1.00)	0.36 (1.00)	0.682 (1.00)	0.492 (1.00)	1 (1.00)	1 (1.00)
14q gain	4 (2%)	210	1 (1.00)	0.549 (1.00)	0.574 (1.00)	0.783 (1.00)	1 (1.00)	1 (1.00)
16p gain	7 (3%)	207	1 (1.00)	0.508 (1.00)	0.196 (1.00)	0.449 (1.00)	1 (1.00)	1 (1.00)
16q gain	5 (2%)	209	1 (1.00)	0.344 (1.00)	0.333 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
17p gain	6 (3%)	208	1 (1.00)	0.54 (1.00)	0.341 (1.00)	0.564 (1.00)	1 (1.00)	1 (1.00)
17q gain	7 (3%)	207	1 (1.00)	0.75 (1.00)	0.196 (1.00)	0.794 (1.00)	1 (1.00)	1 (1.00)
19q gain	3 (1%)	211	0.0143 (1.00)	0.0178 (1.00)	1 (1.00)	0.528 (1.00)	0.185 (1.00)	1 (1.00)
20p gain	3 (1%)	211	1 (1.00)	0.59 (1.00)	0.574 (1.00)	0.528 (1.00)	1 (1.00)	1 (1.00)
20q gain	3 (1%)	211	1 (1.00)	0.59 (1.00)	0.574 (1.00)	0.528 (1.00)	1 (1.00)	1 (1.00)
2p loss	6 (3%)	208	1 (1.00)	0.196 (1.00)	1 (1.00)	0.251 (1.00)	1 (1.00)	1 (1.00)
2q loss	5 (2%)	209	1 (1.00)	0.0272 (1.00)	1 (1.00)	0.107 (1.00)	1 (1.00)	1 (1.00)
3q loss	3 (1%)	211	1 (1.00)	0.204 (1.00)	1 (1.00)	0.0837 (1.00)	1 (1.00)	1 (1.00)
9q loss	4 (2%)	210	1 (1.00)	0.079 (1.00)	1 (1.00)	0.207 (1.00)	0.239 (1.00)	0.181 (1.00)
11p loss	4 (2%)	210	0.0143 (1.00)	0.0302 (1.00)	0.265 (1.00)	0.259 (1.00)	0.239 (1.00)	1 (1.00)
11q loss	5 (2%)	209	0.0143 (1.00)	0.0181 (1.00)	0.103 (1.00)	0.107 (1.00)	0.289 (1.00)	1 (1.00)
13q loss	7 (3%)	207	0.0143 (1.00)	0.133 (1.00)	0.372 (1.00)	0.0225 (1.00)	0.382 (1.00)	0.0283 (1.00)
17p loss	3 (1%)	211	1 (1.00)	0.851 (1.00)	0.574 (1.00)	0.528 (1.00)	0.0115 (1.00)	1 (1.00)
18p loss	3 (1%)	211	1 (1.00)	0.95 (1.00)	0.574 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
18q loss	3 (1%)	211	1 (1.00)	0.95 (1.00)	0.574 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
21q loss	4 (2%)	210	1 (1.00)	0.0044 (0.765)	0.265 (1.00)	0.783 (1.00)	1 (1.00)	1 (1.00)
22q loss	29 (14%)	185	1 (1.00)	0.634 (1.00)	0.491 (1.00)	0.0727 (1.00)	0.225 (1.00)	1 (1.00)

Methods & Data

Input

Mutation data file = broad_values_by_arm.mutsig.cluster.txt
Clinical data file = THCA-TP.clin.merged.picked.txt
Number of patients = 214
Number of significantly arm-level cnvs = 29
Number of selected clinical features = 6
Exclude genes that fewer than K tumors have mutations, K = 3

Survival analysis

For survival clinical features, the Kaplan-Meier survival curves of tumors with and without gene mutations were plotted and the statistical significance P values were estimated by logrank test (Bland and Altman 2004) using the 'survdiff' function in R

Student's t-test analysis

For continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between tumors with and without gene mutations using 't.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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References

[1] Bland and Altman, Statistics notes: The logrank test, BMJ 328(7447):1073 (2004)

[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)

[3] 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)

[4] 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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