Correlations between copy number and mRNA expression
Ovarian Serous Cystadenocarcinoma (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/C1PC319N
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 0.0169, 0.066, 0.1239, 0.20298, 0.2942, 0.38462, 0.45889, 0.531, 0.60113, 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 579 569 550
Genes 24771 18632 15598

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
PAF1 0.8565 0 0 54623 19q13.2 0.046 2.662
TBP 0.8348 0 0 6908 6q27 -0.792 -0.367
ASCC2 0.8324 0 0 84164 22q12.2 -0.715 0.033
MED29 0.8101 0 0 55588 19q13.2 0.046 2.662
RANBP3 0.8073 0 0 8498 19p13.3 -0.698 -0.643
TIMM50 0.807 0 0 92609 19q13.2 0.046 2.662
MTMR3 0.8038 0 0 8897 22q12.2 -0.715 0.033
CUL4A 0.803 0 0 8451 13q34 0.039 -0.261
FAM120B 0.802 0 0 84498 6q27 -0.792 -0.367
SUPT5H 0.8014 0 0 6829 19q13.2 0.046 2.662
ANKRD27 0.8003 0 0 84079 19q13.11 0.008 0.527
CCDC130 0.7995 0 0 81576 19p13.2 0.008 -0.234
TOX4 0.7974 0 0 9878 14q11.2 0.014 1.633
C18ORF8 0.7946 0 0 29919 18q11.2 -0.027 3.657
KIAA1967 0.7932 0 0 57805 8p21.3 -0.081 -0.633
TYK2 0.7921 0 0 7297 19p13.2 0.008 -0.234
AKT2 0.7915 0 0 208 19q13.2 0.046 3.578
CNOT2 0.79 0 0 4848 12q15 0.003 0.119
ZNF623 0.7894 0 0 9831 8q24.3 0.040 0.370
MBD1 0.7866 0 0 4152 18q21.1 -0.027 -0.340
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.