Correlations between copy number and mRNAseq expression
Esophageal Carcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlations between copy number and mRNAseq expression. Broad Institute of MIT and Harvard. doi:10.7908/C1WQ02SH
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 Rnaseq 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 RNAseq expression of the corresponding feature across patients. High positive/low negative correlation coefficients indicate that genomic alterations result in differences in the expressions of mRNAseq the genomic regions transcribe.

Summary

The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are 1061, 1758, 2330, 2894, 3455.5, 4035, 4605.9, 5174, 5790, 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 mRNAseq and number of samples in copy number and expression data sets and common to both

Category Copy number Expression Common
Sample 184 184 183
Genes 24776 22678 16308

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

Locus ID Gene Symbol Cytoband cor p-value q-value
8772 FADD 11q13.3 0.8854 0 0
10948 STARD3 17q12 0.8785 0 0
84299 MIEN1 17q12 0.8763 0 0
220064 ORAOV1 11q13.3 0.8708 0 0
8500 PPFIA1 11q13.3 0.8703 0 0
93210 PGAP3 17q12 0.8256 0 0
220074 LRTOMT 11q13.4 0.825 0 0
55915 LANCL2 7p11.2 0.8161 0 0
23480 SEC61G 7p11.2 0.8129 0 0
2064 ERBB2 17q12 0.807 0 0
3508 IGHMBP2 11q13.3 0.7911 0 0
219927 MRPL21 11q13.3 0.791 0 0
252969 NEIL2 8p23.1 0.7885 0 0
55004 LAMTOR1 11q13.4 0.7874 0 0
2017 CTTN 11q13.3 0.7845 0 0
144363 LYRM5 12p12.1 0.7841 0 0
84060 RBM48 7q21.2 0.7832 0 0
6605 SMARCE1 17q21.2 0.7828 0 0
29919 C18orf8 18q11.2 0.7815 0 0
54965 PIGX 3q29 0.7715 0 0
Methods & Data
Input

Gene level (TCGA Level III) mRNAseq expression data and copy number data of corresponding gene derived by GISTIC pipelinePearson 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.