Brain Lower Grade Glioma: Correlations between copy number and mRNA expression
Maintained by John Zhang (Dana-Farber Cancer Institute)
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 -0.1707, -0.0485, 0.04256, 0.12488, 0.206, 0.28914, 0.3794, 0.48086, 0.61688, 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 | 144 | 27 | 27
Genes | 29390 | 17815 | 15551

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
--- | --- | --- | --- | --- | --- | --- | ---
MRPS15 | 0.9545 | 1.22124532708767e-14 | 9.66051525431063e-11 | 1 | 36693960 | 36702556 | 64960
CSDE1 | 0.9423 | 2.18935980456081e-13 | 8.65933458250026e-10 | 1 | 115061060 | 115102147 | 7812
APITD1 | 0.9359 | 7.90922882742962e-13 | 1.74987060401945e-09 | 1 | 10412746 | 10434797 | 378708
LSM10 | 0.9353 | 8.8484775062625e-13 | 1.74987060401945e-09 | 1 | 36631618 | 36636080 | 84967
TRIM8 | 0.9245 | 5.74118530494161e-12 | 9.08299208783475e-09 | 10 | 104394356 | 104408065 | 81603
FKBP4 | 0.9208 | 1.02904351706457e-11 | 1.14701054071749e-08 | 12 | 2774414 | 2783385 | 2288
GPBP1L1 | 0.9202 | 1.1231238161713e-11 | 1.14701054071749e-08 | 1 | 45865567 | 45899398 | 60313
NRD1 | 0.92 | 1.16000542504935e-11 | 1.14701054071749e-08 | 1 | 52027470 | 52117010 | 4898
RRAGA | 0.9176 | 1.65245594985208e-11 | 1.4523950408602e-08 | 9 | 19039372 | 19041023 | 10670
DNAJC16 | 0.9168 | 1.85336190838825e-11 | 1.46607979499418e-08 | 1 | 15725895 | 15767447 | 23341
PARP11 | 0.9153 | 2.30597763106744e-11 | 1.6582873226292e-08 | 12 | 3788288 | 3852863 | 57097
NOL1 | 0.9123 | 3.50515172442556e-11 | 2.31059032881056e-08 | 12 | 6536298 | 6547741 | 4839
TMEM41B | 0.9114 | 3.96638277777583e-11 | 2.41350746836015e-08 | 11 | 9258777 | 9292872 | 440026
PEX14 | 0.9059 | 8.079892310775e-11 | 4.31430291196528e-08 | 1 | 10457606 | 10613400 | 5195
TRSPAP1 | 0.9052 | 8.8135276854473e-11 | 4.31430291196528e-08 | 1 | 28752192 | 28777638 | 54952
YME1L1 | 0.9044 | 9.85167503131379e-11 | 4.31430291196528e-08 | 10 | 27439389 | 27483327 | 10730
KPNA6 | 0.9042 | 9.99520466393733e-11 | 4.31430291196528e-08 | 1 | 32346244 | 32411380 | 23633
LRRC8D | 0.9042 | 1.00421004844975e-10 | 4.31430291196528e-08 | 1 | 90060101 | 90174148 | 55144
FBXL3 | 0.904 | 1.03625552583253e-10 | 4.31430291196528e-08 | 13 | 76477397 | 76499258 | 26224
RPP38 | 0.9029 | 1.18530962822661e-10 | 4.68812510090462e-08 | 10 | 15179390 | 15186260 | 10557

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)

Meta

- Maintainer = John Zhang

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