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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

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