Correlations between copy number and mRNA expression
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
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/C1D79927
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 -0.17849, -0.0653, 0.0121, 0.0805, 0.1431, 0.20916, 0.2793, 0.36464, 0.47988, 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 514 72 30
Genes 24174 17815 15702

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
ZNF193 0.8861 7.44937445062988e-11 7.61203183602989e-07 7746 6p22.1 -0.686 -0.054
FBXO42 0.8427 5.16365483704817e-09 1.2660232242841e-05 54455 1p36.13 0.009 0.015
RPAIN 0.8405 6.19939544144188e-09 1.2660232242841e-05 84268 17p13.2 -0.008 0.024
TBP 0.839 6.96874580263795e-09 1.2660232242841e-05 6908 6q27 -0.686 -0.048
TMUB1 0.8382 7.43382155832251e-09 1.2660232242841e-05 83590 7q36.1 0.000 -0.001
MAP3K7 0.8346 9.91858950527558e-09 1.44788032841921e-05 6885 6q15 -0.686 -0.054
CDC5L 0.8276 1.68614957551938e-08 2.15370839763541e-05 988 6p21.1 -0.686 -0.054
CSNK2B 0.8232 2.34323052072938e-08 2.43821602102556e-05 1460 6p21.33 -0.686 -0.054
IFI44L 0.8223 2.50225475895149e-08 2.43821602102556e-05 10964 1p31.1 0.009 0.015
RING1 0.8216 2.62472661383129e-08 2.43821602102556e-05 6015 6p21.32 -0.686 -0.054
IFI44 0.8109 5.54130870078495e-08 4.57865775299786e-05 10561 1p31.1 0.009 0.015
UBR2 0.8101 5.82506456403564e-08 4.57865775299786e-05 23304 6p21.1 -0.686 -0.054
FASTK 0.8045 8.43254865934284e-08 5.6867418314276e-05 10922 7q36.1 0.000 -0.001
GNL2 0.8026 9.52888945526809e-08 5.6867418314276e-05 29889 1p34.3 0.009 0.015
PRPF38A 0.8026 9.52638883333634e-08 5.6867418314276e-05 84950 1p32.3 0.009 0.015
CDC40 0.8013 1.03460028544333e-07 5.6867418314276e-05 51362 6q21 -0.686 -0.054
TBCC 0.8009 1.06681918854434e-07 5.6867418314276e-05 6903 6p21.1 -0.686 -0.054
C6orf62 0.8002 1.11304498506826e-07 5.6867418314276e-05 81688 6p22.3 -0.686 -0.054
GTF2E2 0.7984 1.24582162364106e-07 6.06201994288858e-05 2961 8p12 0.000 -0.004
MAD2L1BP 0.7961 1.43843635669327e-07 6.68111214256278e-05 9587 6p21.1 -0.686 -0.054
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.