Correlations between copy number and mRNA expression
Glioma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
Maintained by John Zhang (MD Anderson Cancer Center)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlations between copy number and mRNA expression. Broad Institute of MIT and Harvard. doi:10.7908/C1154GF7
Overview
Introduction

A TCGA sample is profiled to detect the copy number variations and expressions of genes. This pipeline attempts to correlate copy number and expression data of genes across samples to determine if the copy number variations also result in differential expressions. This report contains the calculated correlation coefficients based on measurements of genomic copy number (log2) values and intensity of the expressions of the corresponding feature across patients. High positive/low negative correlation coefficients indicate that genomic alterations result in differences in the expressions of mRNA the genomic regions transcribe.

Summary

The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are -0.0124, 0.02434, 0.06, 0.0979, 0.13795, 0.17972, 0.2217, 0.2684, 0.33793, respectively.

Results
Correlation results

Number of genes and samples used for the calculation are shown in Table 1. Figure 1 shows the distribution of calculated correlation coefficients and quantile-quantile plot of the calculated correlation coefficients against a normal distribution. Table 2 shows the top 20 features ordered by the value of correlation coefficients.

Table 1.  Counts of mRNA and number of samples in copy number and expression data sets and common to both

Category Copy number Expression Common
Sample 1090 528 492
Genes 24771 12043 10838

Figure 1.  Summary figures. Left: histogram showing the distribution of the calculated correlations across samples for all Genes. Right: QQ plot of the calculated correlations across samples. The QQ plot is used to plot the quantiles of the calculated correlation coefficients against that derived from a normal distribution. Points deviating from the blue line indicate deviation from normality.

Table 2.  Get Full Table Top 20 features (defined by the feature column) ranked by correlation coefficients

feature r p-value q-value chrom start end geneid
SEC61G 0.836 0 0 23480 7p11.2 1.267 3.657
METTL1 0.8304 0 0 4234 12q14.1 0.335 3.657
CDK4 0.8064 0 0 1019 12q14.1 0.335 3.657
TSPAN31 0.796 0 0 6302 12q14.1 0.335 3.657
TSFM 0.795 0 0 10102 12q14.1 0.335 3.657
MDM2 0.7849 0 0 4193 12q15 0.335 0.000
MRPS17 0.7604 0 0 -2505 7p11.2 1.267 0.813
EGFR 0.7567 0 0 1956 7p11.2 1.267 3.657
CDKN2A 0.7545 0 0 1029 9p21.3 -1.106 0.001
LANCL2 0.7323 0 0 55915 7p11.2 1.267 0.813
CYP27B1 0.7167 0 0 1594 12q14.1 0.335 3.657
CCT6A 0.7156 0 0 908 7p11.2 1.267 0.813
DCTN2 0.7107 0 0 10540 12q13.3 0.335 3.657
CHIC2 0.7009 0 0 26511 4q12 -0.077 -0.008
CTDSP2 0.6882 0 0 10106 12q14.1 0.335 3.657
ETNK2 0.6878 0 0 55224 1q32.1 0.232 0.008
CHCHD2 0.6833 0 0 51142 7p11.2 1.267 0.813
KLHL9 0.6696 0 0 -3036 9p21.3 -0.044 0.001
MDM4 0.6694 0 0 4194 1q32.1 0.232 0.008
GBAS 0.6651 0 0 2631 7p11.2 1.267 0.813
Methods & Data
Input

Gene level (TCGA Level III) expression data and copy number data of the corresponding loci derived by using the CNTools package of Bioconductor were used for the calculations. Pearson correlation coefficients were calculated for each pair of genes shared by the two data sets across all the samples that were common. The input file "*.medianexp.txt" is generated in the pipeline mRNA_Preprocess_Median in the stddata run.

Correlation across sample

Pairwise correlations between the log2 copy numbers and expressions of each gene across samples were calculated using Pearson correlation.

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.