Glioblastoma Multiforme: Correlations between copy number and mRNA expression
(primary solid tumor cohort)
Maintained by John Zhang (MD Anderson Cancer Center)
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 expression 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 intensity of the expressions of the corresponding feature across patients. High positive/low negative correlation coefficients indicate that genomic alterations result in differences in the expressions of mRNA the genomic regions transcribe.

Summary

The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are -0.0239, 0.0158, 0.05463, 0.1034, 0.1552, 0.20402, 0.2514, 0.30306, 0.3724, 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 mRNA and number of samples in copy number and expression data sets and common to both

Category Copy number Expression Common
Sample 563 529 493
Genes 29390 12043 10944

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

feature r p-value q-value chrom start end geneid
SEC61G 0.842 0 0 7 54787434 54794433 23480
MRPS17 0.8183 0 0 7 55987105 55990528 51373
EGFR 0.7827 0 0 7 55054219 55242525 1956
LANCL2 0.7793 0 0 7 55400635 55468929 55915
CCT6A 0.7752 0 0 7 56086872 56099176 908
ECOP 0.7592 0 0 7 55505801 55607641 81552
KLHL9 0.7423 0 0 9 21321020 21325371 55958
PARK7 0.7341 0 0 1 7944380 7967926 11315
GBAS 0.7085 0 0 7 55999790 56035365 2631
SRP72 0.7008 0 0 4 57028547 57064604 6731
CHCHD2 0.6872 0 0 7 56136760 56141681 51142
FIP1L1 0.6817 0 0 4 53938620 54020599 81608
CHIC2 0.6588 0 0 4 54570713 54625545 26511
NOL6 0.6529 0 0 9 33451351 33463941 65083
CDKN2A 0.6471 0 0 9 21957751 21984490 1029
EXOC1 0.6369 0 0 4 56414573 56466001 55763
LARP5 0.6282 0 0 10 845484 921702 23185
APTX 0.6277 0 0 9 32962608 32991626 54840
NAG 0.6264 0 0 2 15224483 15618905 51594
C9orf82 0.6171 0 0 9 26830683 26882725 79886
Methods & Data
Input

Gene level (TCGA Level III) expression data and copy number data of the corresponding loci derived by using the CNTools package of Bioconductor were used for the calculations. Pearson 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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.