Correlations between copy number and mRNAseq expression
Rectum Adenocarcinoma (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/C1JM2932
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 852.3, 1652, 2225, 2803, 3364, 3911, 4463.1, 5060, 5765, 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 165 166 164
Genes 24776 18106 15454

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
55968 NSFL1C 20p13 0.8945 0 0
9491 PSMF1 20p13 0.8902 0 0
55756 INTS9 8p21.1 0.8793 0 0
91782 CHMP7 8p21.3 0.869 0 0
57805 KIAA1967 8p21.3 0.8655 0 0
2064 ERBB2 17q12 0.8596 0 0
55140 ELP3 8p21.1 0.8559 0 0
5786 PTPRA 20p13 0.8529 0 0
84299 MIEN1 17q12 0.8337 0 0
128637 TBC1D20 20p13 0.8305 0 0
55617 TASP1 20p12.1 0.827 0 0
23039 XPO7 8p21.3 0.8194 0 0
8795 TNFRSF10B 8p21.3 0.8185 0 0
64412 GZF1 20p11.21 0.8165 0 0
51669 TMEM66 8p12 0.8149 0 0
5516 PPP2CB 8p12 0.8148 0 0
79648 MCPH1 8p23.1 0.814 0 0
25980 AAR2 20q11.23 0.8134 0 0
55174 INTS10 8p21.3 0.8131 0 0
2886 GRB7 17q12 0.8113 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 "READ-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.