Correlations between copy number and mRNAseq expression
Liver Hepatocellular Carcinoma (Primary solid tumor)
21 April 2013  |  analyses__2013_04_21
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): Liver Hepatocellular Carcinoma (Primary solid tumor cohort) - 21 April 2013: Correlations between copy number and mRNAseq expression. Broad Institute of MIT and Harvard. doi:10.7908/C1CF9N24
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 883, 1995, 2664.1, 3269, 3905, 4548, 5221.9, 5951, 6795, 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 97 69 69
Genes 23778 17848 17758

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
91782 CHMP7 8p21.3 0.91 0 0
220064 ORAOV1 11q13.3 0.8884 0 0
10987 COPS5 8q13.1 0.8806 0 0
5516 PPP2CB 8p12 0.8732 0 0
57805 KIAA1967 8p21.3 0.8608 0 0
10671 DCTN6 8p12 0.8538 0 0
51001 MTERFD1 8q22.1 0.8506 0 0
60528 ELAC2 17p12 0.8492 0 0
5828 PEX2 8q21.11 0.8469 0 0
7257 TSNAX 1q42.2 0.8457 0 0
2339 FNTA 8p11.21 0.8454 0 0
7323 UBE2D3 4q24 0.8453 0 0
80185 TTI2 8p12 0.8447 0 0
92140 MTDH 8q22.1 0.8446 0 0
57226 LYRM2 6q15 0.8393 0 0
8881 CDC16 13q34 0.8383 0 0
3551 IKBKB 8p11.21 0.8382 0 0
375 ARF1 1q42.13 0.838 0 0
84933 C8orf76 8q24.13 0.8355 0 0
116150 NUS1 6q22.1 0.8354 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.