Correlations between copy number and mRNAseq expression
Prostate Adenocarcinoma (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/C1X065V0
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 668, 1422, 1807, 2175, 2572, 2991, 3492, 4093, 4934, 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 419 374 370
Genes 23778 18250 18151

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
9798 IST1 16q22.2 0.895 0 0
55140 ELP3 8p21.1 0.8675 0 0
51125 GOLGA7 8p11.21 0.8513 0 0
9070 ASH2L 8p11.23 0.8507 0 0
55246 CCDC25 8p21.1 0.8503 0 0
5728 PTEN 10q23.31 0.8404 0 0
91782 CHMP7 8p21.3 0.8371 0 0
55756 INTS9 8p21.1 0.8101 0 0
9785 DHX38 16q22.2 0.8036 0 0
57805 KIAA1967 8p21.3 0.8029 0 0
55308 DDX19A 16q22.1 0.8022 0 0
84896 ATAD1 10q23.31 0.7912 0 0
57226 LYRM2 6q15 0.7888 0 0
9474 ATG5 6q21 0.7883 0 0
11269 DDX19B 16q22.1 0.7874 0 0
8720 MBTPS1 16q23.3 0.7871 0 0
29117 BRD7 16q12.1 0.7771 0 0
57707 KIAA1609 16q24.1 0.7752 0 0
5516 PPP2CB 8p12 0.7687 0 0
80011 FAM192A 16q13 0.7675 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.