Correlations between copy number and mRNAseq expression
Brain Lower Grade Glioma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlations between copy number and mRNAseq expression. Broad Institute of MIT and Harvard. doi:10.7908/C1SB442Q
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 Rnaseq 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 RNAseq expression of the corresponding feature across patients. High positive/low negative correlation coefficients indicate that genomic alterations result in differences in the expressions of mRNAseq the genomic regions transcribe.

Summary

The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 763, 1738, 2223, 2691, 3158.5, 3702, 4315, 5024, 5960, 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 mRNAseq and number of samples in copy number and expression data sets and common to both

Category Copy number Expression Common
Sample 269 271 269
Genes 23778 18324 18228

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

Locus ID Gene Symbol Cytoband cor p-value q-value
22826 DNAJC8 1p35.3 0.8765 0 0
60313 GPBP1L1 1p34.1 0.8709 0 0
23480 SEC61G 7p11.2 0.8666 0 0
4898 NRD1 1p32.3 0.8556 0 0
51231 VRK3 19q13.33 0.8556 0 0
5690 PSMB2 1p34.3 0.8535 0 0
56900 TMEM167B 1p13.3 0.8488 0 0
23185 LARP4B 10p15.3 0.8464 0 0
84919 PPP1R15B 1q32.1 0.8455 0 0
6429 SRSF4 1p35.3 0.8451 0 0
10489 LRRC41 1p34.1 0.8448 0 0
8872 CDC123 10p13 0.8446 0 0
54455 FBXO42 1p36.13 0.8414 0 0
7268 TTC4 1p32.3 0.8358 0 0
10102 TSFM 12q14.1 0.8343 0 0
51249 TMEM69 1p34.1 0.8323 0 0
998 CDC42 1p36.12 0.8279 0 0
8559 PRPF18 10p13 0.8238 0 0
6302 TSPAN31 12q14.1 0.8222 0 0
148479 PHF13 1p36.31 0.8219 0 0
Methods & Data
Input

Gene level (TCGA Level III) mRNAseq expression data and copy number data of corresponding gene derived by GISTIC pipelinePearson 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.