Correlations between copy number and mRNA expression
Lung Squamous Cell Carcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
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/C1G44P7Q
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 -0.0198, 0.0476, 0.108, 0.17566, 0.2485, 0.32334, 0.4037, 0.47952, 0.56726, 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 501 154 154
Genes 24771 17814 15175

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
LSM1 0.9116 0 0 27257 8p11.23 0.047 0.182
PPFIA1 0.8934 0 0 8500 11q13.3 -0.200 -0.090
ORAOV1 0.8833 0 0 220064 11q13.3 -0.200 -0.090
ASH2L 0.8769 0 0 9070 8p11.23 0.047 0.182
EIF3K 0.8677 0 0 27335 19q13.2 0.404 0.156
ZNF639 0.865 0 0 51193 3q26.33 0.605 1.029
BRF2 0.8588 0 0 -2821 8p11.23 0.047 0.182
FADD 0.8572 0 0 8772 11q13.3 -0.200 -0.090
WHSC1L1 0.8532 0 0 54904 8p11.23 0.047 0.182
ACTL6A 0.8448 0 0 86 3q26.33 0.605 1.029
BAG4 0.8429 0 0 9530 8p11.23 0.047 0.182
PSMD8 0.8375 0 0 5714 19q13.2 0.404 0.156
DCUN1D1 0.8337 0 0 -1436 3q26.33 0.605 1.029
UQCRFS1 0.8283 0 0 -5963 19q12 -0.036 0.159
TM2D2 0.8245 0 0 83877 8p11.22 0.047 0.182
DDHD2 0.823 0 0 23259 8p11.23 0.047 0.182
POLR2H 0.8207 0 0 5437 3q27.1 0.605 1.029
SENP2 0.8191 0 0 -1447 3q27.2 0.605 1.029
TOPORS 0.8167 0 0 10210 9p21.1 0.906 0.189
DNAJC19 0.8165 0 0 131118 3q26.33 0.605 1.029
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.