Correlations between copy number and mRNAseq expression
Uterine Carcinosarcoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_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/C1Q81BFP
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 1158.2, 2165.4, 2884.6, 3567.8, 4264, 4973.2, 5726, 6444, 7222, 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 56 56 55
Genes 23778 18660 18583

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
83636 C19orf12 19q12 0.9195 0 0
23509 POFUT1 20q11.21 0.9147 0 0
91782 CHMP7 8p21.3 0.9025 0 0
10775 POP4 19q12 0.8983 0 0
6829 SUPT5H 19q13.2 0.8944 0 0
348793 WDR53 3q29 0.8929 0 0
26065 LSM14A 19q13.11 0.8926 0 0
55588 MED29 19q13.2 0.8909 0 0
55174 INTS10 8p21.3 0.8858 0 0
51125 GOLGA7 8p11.21 0.8849 0 0
208 AKT2 19q13.2 0.8827 0 0
57693 ZNF317 19p13.2 0.8803 0 0
9777 TM9SF4 20q11.21 0.8792 0 0
8725 URI1 19q12 0.878 0 0
6917 TCEA1 8q11.23 0.877 0 0
526 ATP6V1B2 8p21.3 0.8702 0 0
55756 INTS9 8p21.1 0.8674 0 0
55739 CARKD 13q34 0.8666 0 0
2339 FNTA 8p11.21 0.8658 0 0
4848 CNOT2 12q15 0.8658 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

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.