Correlation between gene methylation status and clinical features
Prostate Adenocarcinoma (Primary solid tumor)
22 February 2013 | analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C1736P4M
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between gene methylation status and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1736P4M
Overview
Introduction

This pipeline uses various statistical tests to identify genes whose promoter methylation levels correlated to selected clinical features.

Summary

Testing the association between 17323 genes and 2 clinical features across 114 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.

- 2 genes correlated to 'AGE'.

- CACNA1B , RASGRF1

- 54 genes correlated to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

- NAA20 , ZNF280D , SCD , HIST1H2BB , ZKSCAN4 , ...

Results
Overview of the results

Complete statistical result table is provided in Supplement Table 1

Table 1. Get Full Table This table shows the clinical features, statistical methods used, and the number of genes that are significantly associated with each clinical feature at Q value < 0.05.

Clinical feature | Statistical test | Significant genes | Associated with |  | Associated with |
--- | --- | --- | --- | --- | --- | ---
AGE | Spearman correlation test | N=2 | older | N=2 | younger | N=0
RADIATIONS RADIATION REGIMENINDICATION | t test | N=54 | yes | N=42 | no | N=12

Clinical variable #1: 'AGE'

2 genes related to 'AGE'.

Table S1. Basic characteristics of clinical feature: 'AGE'

AGE | Mean (SD) | 60.44 (7.1)
| Significant markers | N = 2
| pos. correlated | 2
| neg. correlated | 0

List of 2 genes significantly correlated to 'AGE' by Spearman correlation test

Table S2. Get Full Table List of 2 genes significantly correlated to 'AGE' by Spearman correlation test

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
CACNA1B | 0.4795 | 6.731e-08 | 0.00117
RASGRF1 | 0.4381 | 1.089e-06 | 0.0189

Figure S1. Get High-res Image As an example, this figure shows the association of CACNA1B to 'AGE'. P value = 6.73e-08 with Spearman correlation analysis. The straight line presents the best linear regression.

Clinical variable #2: 'RADIATIONS.RADIATION.REGIMENINDICATION'

54 genes related to 'RADIATIONS.RADIATION.REGIMENINDICATION'.

Table S3. Basic characteristics of clinical feature: 'RADIATIONS.RADIATION.REGIMENINDICATION'

RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N
| NO | 5
| YES | 109
| Significant markers | N = 54
| Higher in YES | 42
| Higher in NO | 12

List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

Table S4. Get Full Table List of top 10 genes differentially expressed by 'RADIATIONS.RADIATION.REGIMENINDICATION'

| T(pos if higher in 'YES') | ttestP | Q | AUC
--- | --- | --- | --- | ---
NAA20 | 9.34 | 2.343e-14 | 4.06e-10 | 0.8606
ZNF280D | 9.24 | 1.219e-13 | 2.11e-09 | 0.7963
SCD | -8.93 | 2.37e-12 | 4.1e-08 | 0.8385
HIST1H2BB | 7.7 | 6.301e-12 | 1.09e-07 | 0.7174
ZKSCAN4 | 9.27 | 2.297e-11 | 3.98e-07 | 0.8606
CLEC4C | -7.34 | 6.21e-11 | 1.08e-06 | 0.7596
AASDHPPT | 7.41 | 7.077e-11 | 1.23e-06 | 0.8569
ZNF525 | 9.23 | 1.761e-10 | 3.05e-06 | 0.8826
VWDE | 6.83 | 4.661e-10 | 8.07e-06 | 0.7725
PIK3CA | 6.82 | 7.493e-09 | 0.00013 | 0.7908

Figure S2. Get High-res Image As an example, this figure shows the association of NAA20 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 2.34e-14 with T-test analysis.

Methods & Data
Input

- Expresson data file = PRAD-TP.meth.for_correlation.filtered_data.txt

- Clinical data file = PRAD-TP.clin.merged.picked.txt

- Number of patients = 114

- Number of genes = 17323

- Number of clinical features = 2

Correlation analysis

For continuous numerical clinical features, Spearman's rank correlation coefficients (Spearman 1904) and two-tailed P values were estimated using 'cor.test' function in R

Student's t-test analysis

For two-class clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the log2-expression levels between the two clinical classes using 't.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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

References
[1] Spearman, C, The proof and measurement of association between two things, Amer. J. Psychol 15:72-101 (1904)
[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[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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