Correlations between copy number and mRNAseq expression
Skin Cutaneous Melanoma (Metastatic)
23 May 2013  |  analyses__2013_05_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/C1SF2T8Z
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 971.8, 1685, 2238, 2826, 3432, 4069, 4732, 5409.4, 6169, 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 260 241 241
Genes 23778 18090 17999

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
92105 INTS4 11q14.1 0.8299 0 0
2547 XRCC6 22q13.2 0.8084 0 0
1211 CLTA 9p13.3 0.7924 0 0
55585 UBE2Q1 1q21.3 0.7881 0 0
6257 RXRB 6p21.32 0.7858 0 0
54476 RNF216 7p22.1 0.7811 0 0
54926 UBE2R2 9p13.3 0.7742 0 0
55122 AKIRIN2 6q15 0.772 0 0
1019 CDK4 12q14.1 0.7696 0 0
51271 UBAP1 9p13.3 0.7666 0 0
10102 TSFM 12q14.1 0.7649 0 0
5546 PRCC 1q23.1 0.7648 0 0
55069 C7orf42 7q11.21 0.7647 0 0
10171 RCL1 9p24.1 0.7646 0 0
5537 PPP6C 9q33.3 0.763 0 0
220064 ORAOV1 11q13.3 0.7614 0 0
1432 MAPK14 6p21.31 0.761 0 0
10352 WARS2 1p12 0.7608 0 0
57645 POGK 1q24.1 0.7605 0 0
6730 SRP68 17q25.1 0.7604 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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.