Correlations between copy number and mRNA expression
Uterine Corpus Endometrioid Carcinoma (Primary solid tumor)
21 April 2013  |  analyses__2013_04_21
Maintainer Information
Citation Information
Maintained by John Zhang (MD Anderson Cancer Center)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Uterine Corpus Endometrioid Carcinoma (Primary solid tumor cohort) - 21 April 2013: Correlations between copy number and mRNA expression. Broad Institute of MIT and Harvard. doi:10.7908/C1GM859R

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.


The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are -0.08547, -0.0041, 0.0617, 0.11884, 0.1754, 0.2308, 0.2946, 0.3669, 0.4598, respectively.

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 492 54 53
Genes 24174 17815 15702

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 0.859 2.22044604925031e-16 1.73421317786939e-12 83636 19q12 0.003 -0.079
POP4 0.8243 3.35287353436797e-14 1.30933094929139e-10 10775 19q12 0.003 -0.079
EIF4A3 0.8043 4.06341627012807e-13 1.05787003850033e-09 9775 17q25.3 0.009 -0.032
SAP30BP 0.7955 1.11022302462516e-12 2.16776647233673e-09 29115 17q25.1 0.009 -0.032
ERBB2 0.7887 2.3365753776261e-12 2.78883156666121e-09 2064 17q12 0.009 -0.032
WHSC2 0.7887 2.34878783089698e-12 2.78883156666121e-09 7469 4p16.3 -0.001 -0.418
POFUT1 0.7874 2.68762789801258e-12 2.78883156666121e-09 23509 20q11.21 0.006 0.333
PSMB4 0.7868 2.85660384236053e-12 2.78883156666121e-09 5692 1q21.3 0.002 0.240
RAF1 0.7795 6.17372819533557e-12 5.35756257749783e-09 5894 3p25.2 -0.002 0.042
STARD3 0.7746 1.01283426090504e-11 7.91043998953342e-09 10948 17q12 0.009 -0.032
MAP2K4 0.7719 1.32196475988167e-11 8.32302264464992e-09 6416 17p12 0.009 -0.032
ZNF764 0.7715 1.37239108966014e-11 8.32302264464992e-09 92595 16p11.2 -0.003 -0.023
HDAC11 0.7714 1.38535849458776e-11 8.32302264464992e-09 79885 3p25.1 -0.002 0.042
UBA52 0.7692 1.71136438353869e-11 9.54721516128052e-09 7311 19p13.11 0.003 -0.079
RANBP10 0.7685 1.83966175626438e-11 9.57875306664377e-09 57610 16q22.1 -0.003 -0.023
POLR2I 0.7654 2.47468712188947e-11 1.20798786670964e-08 5438 19q13.12 0.003 -0.079
RPL32 0.7597 4.25144364157859e-11 1.95321369847233e-08 6161 3p25.2 -0.002 0.042
B4GALT3 0.7568 5.52782264406915e-11 2.39852280468756e-08 8703 1q23.3 0.002 0.240
INTS9 0.7524 8.24826873468965e-11 3.39056018405244e-08 55756 8p21.1 -0.004 0.020
ASXL1 0.7512 9.18460862919801e-11 3.58668235233769e-08 171023 20q11.21 0.006 0.333
Methods & Data

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.