Correlations between copy number and mRNAseq expression
Brain Lower Grade Glioma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
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 (2014): Correlations between copy number and mRNAseq expression. Broad Institute of MIT and Harvard. doi:10.7908/C1QZ28DP
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 779.2, 1686, 2132, 2572, 3039, 3560.2, 4173, 4876.6, 5784.8, 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 365 365 363
Genes 23778 18310 18213

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
60313 GPBP1L1 1p34.1 0.8866 0 0
4898 NRD1 1p32.3 0.8693 0 0
5690 PSMB2 1p34.3 0.866 0 0
54455 FBXO42 1p36.13 0.8599 0 0
10489 LRRC41 1p34.1 0.8586 0 0
22826 DNAJC8 1p35.3 0.8571 0 0
10102 TSFM 12q14.1 0.8539 0 0
7268 TTC4 1p32.3 0.8502 0 0
998 CDC42 1p36.12 0.8489 0 0
23480 SEC61G 7p11.2 0.8466 0 0
51231 VRK3 19q13.33 0.8436 0 0
26065 LSM14A 19q13.11 0.8433 0 0
56900 TMEM167B 1p13.3 0.8418 0 0
56181 FAM54B 1p36.11 0.8409 0 0
8872 CDC123 10p13 0.8361 0 0
51249 TMEM69 1p34.1 0.835 0 0
7812 CSDE1 1p13.2 0.835 0 0
6302 TSPAN31 12q14.1 0.8308 0 0
23185 LARP4B 10p15.3 0.8305 0 0
51441 YTHDF2 1p35.3 0.8305 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.