Correlation between mRNAseq expression and clinical features
Prostate Adenocarcinoma (Primary solid tumor)
22 February 2013 | analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C1TT4P5T
Maintained by Juok Cho (Broad Institute)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between mRNAseq expression and clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1TT4P5T
Overview
Introduction

This pipeline uses various statistical tests to identify mRNAs whose expression levels correlated to selected clinical features.

Summary

Testing the association between 18266 genes and 2 clinical features across 117 samples, statistically thresholded by Q value < 0.05, 2 clinical features related to at least one genes.

- 1 gene correlated to 'AGE'.

- ADAP2|55803

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

- C14ORF126|112487 , CEBPZ|10153 , SFRS2|6427 , ABHD11|83451 , CDC40|51362 , ...

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=1 | older | N=1 | younger | N=0
RADIATIONS RADIATION REGIMENINDICATION | t test | N=25 | yes | N=6 | no | N=19

Clinical variable #1: 'AGE'

One gene related to 'AGE'.

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

AGE | Mean (SD) | 60.68 (7.2)
| Significant markers | N = 1
| pos. correlated | 1
| neg. correlated | 0

List of one gene significantly correlated to 'AGE' by Spearman correlation test

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

| SpearmanCorr | corrP | Q
--- | --- | --- | ---
ADAP2|55803 | 0.4576 | 2.137e-07 | 0.0039

Figure S1. Get High-res Image As an example, this figure shows the association of ADAP2|55803 to 'AGE'. P value = 2.14e-07 with Spearman correlation analysis. The straight line presents the best linear regression.

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

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

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

RADIATIONS.RADIATION.REGIMENINDICATION | Labels | N
| NO | 5
| YES | 112
| Significant markers | N = 25
| Higher in YES | 6
| Higher in NO | 19

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
--- | --- | --- | --- | ---
C14ORF126|112487 | -8.6 | 4.054e-13 | 7.1e-09 | 0.8321
CEBPZ|10153 | -8.3 | 4.183e-12 | 7.32e-08 | 0.8179
SFRS2|6427 | -9.72 | 1.026e-11 | 1.8e-07 | 0.85
ABHD11|83451 | 10.36 | 3.235e-11 | 5.66e-07 | 0.8911
CDC40|51362 | -7.63 | 1.711e-08 | 0.000299 | 0.8161
SFRS13A|10772 | -8.51 | 1.764e-08 | 0.000309 | 0.8536
MCOLN2|255231 | -6.02 | 3.092e-08 | 0.000541 | 0.6839
CLK4|57396 | -9.1 | 3.244e-08 | 0.000567 | 0.8821
ZNF596|169270 | -9.54 | 3.95e-08 | 0.000691 | 0.8964
COL11A2|1302 | -6.43 | 6.235e-08 | 0.00109 | 0.7982

Figure S2. Get High-res Image As an example, this figure shows the association of C14ORF126|112487 to 'RADIATIONS.RADIATION.REGIMENINDICATION'. P value = 4.05e-13 with T-test analysis.

Methods & Data
Input

- Expresson data file = PRAD-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt

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

- Number of patients = 117

- Number of genes = 18266

- 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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