Correlations between copy number and mRNAseq expression
Lung 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/C1X34W7W
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 1076, 1701, 2253, 2820.4, 3431, 4098, 4749, 5412, 6168, 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 493 488 486
Genes 23778 18308 18217

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
9070 ASH2L 8p11.23 0.841 0 0
4848 CNOT2 12q15 0.8387 0 0
6729 SRP54 14q13.2 0.8349 0 0
8451 CUL4A 13q34 0.8291 0 0
8725 URI1 19q12 0.8193 0 0
83636 C19orf12 19q12 0.8053 0 0
11336 EXOC3 5p15.33 0.7961 0 0
54994 C20orf11 20q13.33 0.7929 0 0
55958 KLHL9 9p21.3 0.7921 0 0
10775 POP4 19q12 0.7915 0 0
134218 DNAJC21 5p13.2 0.7878 0 0
79648 MCPH1 8p23.1 0.7865 0 0
55756 INTS9 8p21.1 0.7855 0 0
8881 CDC16 13q34 0.7826 0 0
7572 ZNF24 18q12.2 0.7825 0 0
23259 DDHD2 8p11.23 0.7824 0 0
55341 LSG1 3q29 0.7812 0 0
55585 UBE2Q1 1q21.3 0.78 0 0
122553 TRAPPC6B 14q21.1 0.7757 0 0
11212 PROSC 8p11.23 0.7755 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.