Uterine Corpus Endometrioid Carcinoma: 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 -0.09654, -0.00476, 0.06168, 0.1255, 0.186, 0.24686, 0.3128, 0.3866, 0.48244, 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 | 363 | 54 | 53
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
--- | --- | --- | --- | --- | --- | --- | ---
C19orf12 | 0.9176 | 0 | 0 | 19 | 34883910 | 34897971 | 83636
POP4 | 0.8786 | 0 | 0 | 19 | 34789041 | 34798547 | 10775
C17orf37 | 0.8646 | 0 | 0 | 17 | 35138935 | 35140314 | 84299
GSTT1 | 0.8524 | 4.44089209850063e-16 | 7.91356668707678e-13 | 22 | 22706141 | 22714231 | 2952
SAP30BP | 0.828 | 2.04281036531029e-14 | 2.91219254084425e-11 | 17 | 71174994 | 71215734 | 29115
LCMT1 | 0.8046 | 3.90354415458205e-13 | 4.63735007862699e-10 | 16 | 25030548 | 25097052 | 51451
PSMB4 | 0.8025 | 4.9737991503207e-13 | 5.06468267972914e-10 | 1 | 149638665 | 149641036 | 5692
SCNM1 | 0.7925 | 1.54098955817972e-12 | 1.37300382020782e-09 | 1 | 149405141 | 149408238 | 79005
ASXL1 | 0.7901 | 2.00151006879423e-12 | 1.58517533594022e-09 | 20 | 30409821 | 30490783 | 171023
POLR2I | 0.7859 | 3.13882253522024e-12 | 2.23732357377035e-09 | 19 | 41296451 | 41298046 | 5438
STARD3 | 0.784 | 3.86002341201674e-12 | 2.50126260523896e-09 | 17 | 35046938 | 35073263 | 10948
UBA52 | 0.781 | 5.27311527775964e-12 | 2.95626501993228e-09 | 19 | 18543668 | 18547050 | 7311
MAP2K4 | 0.7808 | 5.39168709678961e-12 | 2.95626501993228e-09 | 17 | 11864860 | 11987776 | 6416
RANBP10 | 0.7797 | 6.0382809863313e-12 | 3.06265582212121e-09 | 16 | 66314506 | 66398056 | 57610
ISG20L2 | 0.779 | 6.44506670255396e-12 | 3.06265582212121e-09 | 1 | 154959037 | 154964329 | 81875
ZNF687 | 0.778 | 7.18092252327551e-12 | 3.19905933325079e-09 | 1 | 149521415 | 149531005 | 57592
SUMO2 | 0.7757 | 9.07141028960723e-12 | 3.80353945216276e-09 | 17 | 70675420 | 70690693 | 6613
B4GALT3 | 0.7735 | 1.12305720278982e-11 | 4.44724862109966e-09 | 1 | 159407725 | 159413938 | 8703
BECN1 | 0.7705 | 1.51754164789963e-11 | 5.693103175385e-09 | 17 | 38215678 | 38229807 | 8678
C19orf2 | 0.7675 | 2.02473593446939e-11 | 7.21606491927783e-09 | 19 | 35125265 | 35198456 | 8725

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. Location of data archives could not be determined.

Meta

- Maintainer = John Zhang

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