Thyroid Adenocarcinoma: Correlation between copy number variations of arm-level result and selected clinical features
Maintained by TCGA GDAC Team (Broad Institute/Dana-Farber Cancer Institute/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 28 arm-level results and 6 clinical features across 182 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 28 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
NEOADJUVANT
THERAPY
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 5 (3%) 177 1
(1.00)
0.244
(1.00)
0.62
(1.00)
0.431
(1.00)
0.333
(1.00)
1
(1.00)
4p gain 4 (2%) 178 0.0143
(1.00)
0.119
(1.00)
1
(1.00)
0.801
(1.00)
0.276
(1.00)
1
(1.00)
4q gain 4 (2%) 178 0.0143
(1.00)
0.119
(1.00)
1
(1.00)
0.801
(1.00)
0.276
(1.00)
1
(1.00)
5p gain 7 (4%) 175 0.0143
(1.00)
0.077
(1.00)
1
(1.00)
0.532
(1.00)
0.435
(1.00)
1
(1.00)
5q gain 7 (4%) 175 0.0143
(1.00)
0.077
(1.00)
1
(1.00)
0.532
(1.00)
0.435
(1.00)
1
(1.00)
7p gain 8 (4%) 174 1
(1.00)
0.167
(1.00)
1
(1.00)
0.695
(1.00)
1
(1.00)
1
(1.00)
7q gain 10 (5%) 172 1
(1.00)
0.0995
(1.00)
0.728
(1.00)
0.261
(1.00)
1
(1.00)
1
(1.00)
12p gain 7 (4%) 175 1
(1.00)
0.365
(1.00)
0.675
(1.00)
0.532
(1.00)
1
(1.00)
1
(1.00)
12q gain 7 (4%) 175 1
(1.00)
0.365
(1.00)
0.675
(1.00)
0.532
(1.00)
1
(1.00)
1
(1.00)
14q gain 4 (2%) 178 1
(1.00)
0.555
(1.00)
0.578
(1.00)
0.801
(1.00)
1
(1.00)
1
(1.00)
16p gain 7 (4%) 175 1
(1.00)
0.516
(1.00)
0.193
(1.00)
0.483
(1.00)
1
(1.00)
1
(1.00)
16q gain 5 (3%) 177 1
(1.00)
0.348
(1.00)
0.324
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
17p gain 6 (3%) 176 1
(1.00)
0.545
(1.00)
0.187
(1.00)
0.776
(1.00)
1
(1.00)
1
(1.00)
17q gain 7 (4%) 175 1
(1.00)
0.758
(1.00)
0.193
(1.00)
0.811
(1.00)
1
(1.00)
1
(1.00)
19q gain 3 (2%) 179 0.0143
(1.00)
0.0172
(1.00)
1
(1.00)
0.566
(1.00)
0.215
(1.00)
1
(1.00)
20p gain 3 (2%) 179 1
(1.00)
0.593
(1.00)
0.561
(1.00)
0.566
(1.00)
1
(1.00)
1
(1.00)
20q gain 3 (2%) 179 1
(1.00)
0.593
(1.00)
0.561
(1.00)
0.566
(1.00)
1
(1.00)
1
(1.00)
2p loss 5 (3%) 177 1
(1.00)
0.394
(1.00)
1
(1.00)
0.517
(1.00)
1
(1.00)
1
(1.00)
2q loss 4 (2%) 178 1
(1.00)
0.0908
(1.00)
1
(1.00)
0.298
(1.00)
1
(1.00)
1
(1.00)
9q loss 4 (2%) 178 1
(1.00)
0.079
(1.00)
1
(1.00)
0.236
(1.00)
0.276
(1.00)
1
(1.00)
11p loss 3 (2%) 179 0.0143
(1.00)
0.102
(1.00)
0.19
(1.00)
0.566
(1.00)
0.215
(1.00)
1
(1.00)
11q loss 4 (2%) 178 0.0143
(1.00)
0.0587
(1.00)
0.0673
(1.00)
0.298
(1.00)
0.276
(1.00)
1
(1.00)
13q loss 6 (3%) 176 0.0143
(1.00)
0.243
(1.00)
0.352
(1.00)
0.039
(1.00)
0.386
(1.00)
1
(1.00)
17p loss 3 (2%) 179 1
(1.00)
0.858
(1.00)
0.561
(1.00)
0.566
(1.00)
0.0158
(1.00)
1
(1.00)
18p loss 3 (2%) 179 1
(1.00)
0.942
(1.00)
0.561
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
18q loss 3 (2%) 179 1
(1.00)
0.942
(1.00)
0.561
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
21q loss 3 (2%) 179 1
(1.00)
0.0289
(1.00)
0.19
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
22q loss 28 (15%) 154 1
(1.00)
0.772
(1.00)
0.649
(1.00)
0.121
(1.00)
0.132
(1.00)
1
(1.00)
Methods & Data
Input
  • Mutation data file = broad_values_by_arm.mutsig.cluster.txt

  • Clinical data file = THCA.clin.merged.picked.txt

  • Number of patients = 182

  • Number of significantly arm-level cnvs = 28

  • 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)