Correlations between copy number and mRNAseq expression
Bladder Urothelial 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/C1NV9HM8
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 914, 1472, 2005, 2539, 3146, 3814, 4494.1, 5152, 5879, 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 408 408 404
Genes 24776 18215 15594

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
9191 DEDD 1q23.3 0.8794 0 0
55234 SMU1 9p21.1 0.8543 0 0
27257 LSM1 8p11.23 0.853 0 0
5894 RAF1 3p25.2 0.853 0 0
9070 ASH2L 8p11.23 0.843 0 0
8725 URI1 19q12 0.8397 0 0
51123 ZNF706 8q22.3 0.8396 0 0
23609 MKRN2 3p25.2 0.8351 0 0
4848 CNOT2 12q15 0.8339 0 0
10576 CCT2 12q15 0.8328 0 0
11212 PROSC 8p11.23 0.8327 0 0
9785 DHX38 16q22.2 0.8306 0 0
5440 POLR2K 8q22.2 0.8294 0 0
1871 E2F3 6p22.3 0.8263 0 0
10818 FRS2 12q15 0.8218 0 0
25917 THUMPD3 3p25.3 0.8168 0 0
55246 CCDC25 8p21.1 0.8117 0 0
8703 B4GALT3 1q23.3 0.8092 0 0
4720 NDUFS2 1q23.3 0.8085 0 0
27005 USP21 1q23.3 0.8081 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 "BLCA-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.