Correlations between copy number and mRNA expression
Uterine Corpus Endometrioid Carcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
Maintained by John Zhang (MD Anderson Cancer Center)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlations between copy number and mRNA expression. Broad Institute of MIT and Harvard. doi:10.7908/C1V123R1
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 -0.0935, -0.0092, 0.0541, 0.11262, 0.169, 0.2241, 0.28758, 0.3591, 0.45322, 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 539 54 53
Genes 24771 17814 15175

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 0.8568 2.22044604925031e-16 1.73827901313337e-12 -5966 19q12 0.966 -0.005
POP4 0.8261 2.64233079860787e-14 1.03427601281435e-10 -5965 19q12 0.966 -0.005
SAP30BP 0.7976 8.76410055639099e-13 1.7608766403041e-09 29115 17q25.1 0.950 -0.007
EIF4A3 0.7974 8.99724739156227e-13 1.7608766403041e-09 9775 17q25.3 0.017 -0.007
ERBB2 0.7892 2.20712337295481e-12 3.45569867810913e-09 2064 17q12 1.670 -0.001
POFUT1 0.7873 2.71449529520851e-12 3.54174348925923e-09 23509 20q11.21 0.024 -0.002
UBA52 0.7823 4.6109782658732e-12 4.95931002446949e-09 7311 19p13.11 3.657 -0.005
RAF1 0.7814 5.06794606280891e-12 4.95931002446949e-09 5894 3p25.2 -0.965 -0.001
ZNF764 0.7708 1.46918033294696e-11 1.11350993074027e-08 92595 16p11.2 0.043 -0.005
STARD3 0.7706 1.50226497908079e-11 1.11350993074027e-08 10948 17q12 1.670 -0.001
PSMD8 0.7702 1.56461510414374e-11 1.11350993074027e-08 5714 19q13.2 0.840 -0.005
POLR2I 0.7686 1.83111303897476e-11 1.19457430914213e-08 5438 19q13.12 0.966 -0.005
HDAC11 0.7647 2.64870347876922e-11 1.59503145107415e-08 79885 3p25.1 -1.030 -0.001
PSMB4 0.7621 3.39399619520009e-11 1.89785302653901e-08 5692 1q21.3 0.018 0.829
RPL32 0.7565 5.67164093467909e-11 2.96003421177753e-08 6161 3p25.2 -1.030 -0.001
PREP 0.7512 9.15936215761803e-11 4.20190323002477e-08 5550 6q21 -0.028 0.001
EDF1 0.7507 9.62434576479154e-11 4.20190323002477e-08 8721 9q34.3 -0.911 -0.003
ASXL1 0.7506 9.66138280489304e-11 4.20190323002477e-08 171023 20q11.21 0.024 -0.002
MAP2K4 0.7499 1.03463237977053e-10 4.26296460064518e-08 6416 17p12 -0.940 -0.001
LSM14A 0.7485 1.16985088283172e-10 4.57909625592683e-08 26065 19q13.11 0.966 -0.005
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

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.