Correlations between copy number and mRNA expression
Brain Lower Grade Glioma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
Maintained by John Zhang (MD Anderson Cancer Center)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlations between copy number and mRNA expression. Broad Institute of MIT and Harvard. doi:10.7908/C1GB22T6
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 -0.1632, -0.05234, 0.0362, 0.1128, 0.19, 0.2744, 0.36491, 0.47584, 0.61798, 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 512 27 27
Genes 24174 17814 15704

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
MRPS15 0.9585 3.99680288865056e-15 2.84324959125141e-11 64960 1p34.3 0.004 0.459
CCDC97 0.9569 6.21724893790088e-15 2.84324959125141e-11 90324 19q13.2 0.008 0.022
APITD1 0.9521 2.24265050974282e-14 6.83733830277125e-11 378708 1p36.22 0.004 0.459
CSDE1 0.9486 5.37347943918576e-14 1.22869000193365e-10 7812 1p13.2 0.003 0.447
PPP1R15B 0.9465 8.65973959207622e-14 1.58409620084007e-10 84919 1q32.1 0.003 0.444
LSM10 0.9425 2.1138646388863e-13 3.2223495367516e-10 84967 1p34.3 0.004 0.459
EIF3I 0.9314 1.79789516607798e-12 2.0624842273046e-09 8668 1p35.1 0.004 0.459
NRD1 0.9309 1.96020977227818e-12 2.0624842273046e-09 4898 1p32.3 0.004 0.447
RWDD1 0.9307 2.02948768901479e-12 2.0624842273046e-09 51389 6q22.1 0.000 -0.009
KPNA6 0.9297 2.40252262528884e-12 2.19742575552431e-09 23633 1p35.1 0.004 0.459
PPIE 0.9289 2.78310707813034e-12 2.31410976472371e-09 10450 1p34.2 0.004 0.459
PAF1 0.9258 4.66560123868476e-12 3.55609288162945e-09 54623 19q13.2 0.008 0.022
PEX14 0.9235 6.70041799821774e-12 4.54977960102088e-09 5195 1p36.22 0.004 0.459
CDC123 0.9233 6.96420698886868e-12 4.54977960102088e-09 8872 10p13 -0.004 -0.583
PARP1 0.9219 8.6941565058396e-12 5.3013065593071e-09 142 1q42.12 0.003 0.444
TXNDC12 0.9196 1.21840315614463e-11 6.96494605228337e-09 51060 1p32.3 0.004 0.447
RPP38 0.9188 1.38105082925222e-11 7.43031911038084e-09 10557 10p13 -0.004 -0.583
ATG5 0.9161 2.03332906067999e-11 9.89771525002625e-09 9474 6q21 0.000 -0.009
TMEM147 0.9161 2.0560886326848e-11 9.89771525002625e-09 10430 19q13.12 0.008 0.022
FBXL3 0.9135 2.97266655735484e-11 1.29471335213594e-08 26224 13q22.3 -0.007 -0.006
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.

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.