Correlations between copy number and mRNAseq expression
Pancreatic Adenocarcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
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 (2014): Correlations between copy number and mRNAseq expression. Broad Institute of MIT and Harvard. doi:10.7908/C1ZG6QW6
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 894, 2089, 2720, 3299, 3868, 4445, 5076, 5775, 6604, 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 91 85 84
Genes 23778 18495 18401

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
79602 ADIPOR2 12p13.33 0.9476 0 0
144699 FBXL14 12p13.33 0.911 0 0
6882 TAF11 6p21.31 0.9084 0 0
4848 CNOT2 12q15 0.906 0 0
196513 DCP1B 12p13.33 0.8773 0 0
84318 CCDC77 12p13.33 0.8766 0 0
50813 COPS7A 12p13.31 0.8667 0 0
11011 TLK2 17q23.2 0.8652 0 0
54902 TTC19 17p12 0.8644 0 0
171017 ZNF384 12p13.31 0.8617 0 0
79591 C10orf76 10q24.32 0.8551 0 0
64771 C6orf106 6p21.31 0.845 0 0
4704 NDUFA9 12p13.32 0.8438 0 0
5908 RAP1B 12q15 0.835 0 0
11325 DDX42 17q23.3 0.8191 0 0
10552 ARPC1A 7q22.1 0.813 0 0
4839 NOP2 12p13.31 0.8114 0 0
25821 MTO1 6q13 0.8112 0 0
9918 NCAPD2 12p13.31 0.8093 0 0
7156 TOP3A 17p11.2 0.8072 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.