Correlations between copy number and mRNAseq expression
Liver Hepatocellular Carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
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 (2016): Correlations between copy number and mRNAseq expression. Broad Institute of MIT and Harvard. doi:10.7908/C1ZG6RNG
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 850.1, 1555, 2076, 2616, 3191.5, 3812, 4451.7, 5109.8, 5827.9, 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 370 371 364
Genes 24776 17745 15232

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
80185 TTI2 8p12 0.8505 0 0
91782 CHMP7 8p21.3 0.8483 0 0
22827 PUF60 8q24.3 0.8393 0 0
27257 LSM1 8p11.23 0.8309 0 0
51123 ZNF706 8q22.3 0.83 0 0
7553 ZNF7 8q24.3 0.8275 0 0
10987 COPS5 8q13.1 0.8256 0 0
60528 ELAC2 17p12 0.8222 0 0
84549 MAK16 8p12 0.8214 0 0
79648 MCPH1 8p23.1 0.8213 0 0
9191 DEDD 1q23.3 0.8197 0 0
286053 NSMCE2 8q24.13 0.8158 0 0
81858 SHARPIN 8q24.3 0.8157 0 0
56658 TRIM39 6p22.1 0.8149 0 0
10671 DCTN6 8p12 0.8131 0 0
5440 POLR2K 8q22.2 0.8105 0 0
57226 LYRM2 6q15 0.8101 0 0
7419 VDAC3 8p11.21 0.8098 0 0
9070 ASH2L 8p11.23 0.8083 0 0
7323 UBE2D3 4q24 0.8055 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. The input file "LIHC-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt " is generated in the pipeline mRNAseq_Preprocess in the stddata run.

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.