Correlations between copy number and mRNAseq expression
Kidney Renal Clear Cell Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
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 (2014): Correlations between copy number and mRNAseq expression. Broad Institute of MIT and Harvard. doi:10.7908/C1S75F37
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 777, 1597.4, 2027, 2436.8, 2868, 3313, 3828, 4391, 5133, 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 527 518 510
Genes 23778 18274 18178

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
10001 MED6 14q24.2 0.7472 0 0
91833 WDR20 14q32.31 0.746 0 0
22938 SNW1 14q24.3 0.7403 0 0
93487 MAPK1IP1L 14q22.3 0.7219 0 0
9878 TOX4 14q11.2 0.7204 0 0
91782 CHMP7 8p21.3 0.72 0 0
91754 NEK9 14q24.3 0.7151 0 0
11154 AP4S1 14q12 0.7133 0 0
55234 SMU1 9p21.1 0.7082 0 0
10342 TFG 3q12.2 0.7066 0 0
9861 PSMD6 3p14.1 0.7004 0 0
28976 ACAD9 3q21.3 0.7001 0 0
25983 NGDN 14q11.2 0.6962 0 0
5663 PSEN1 14q24.2 0.696 0 0
8846 ALKBH1 14q24.3 0.6936 0 0
55246 CCDC25 8p21.1 0.6909 0 0
11198 SUPT16H 14q11.2 0.6792 0 0
10548 TM9SF1 14q12 0.6719 0 0
122553 TRAPPC6B 14q21.1 0.6712 0 0
55164 SHQ1 3p13 0.6674 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.