Correlations between copy number and mRNAseq expression
Testicular Germ Cell Tumors (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
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 (2016): Correlations between copy number and mRNAseq expression. Broad Institute of MIT and Harvard. doi:10.7908/C1P84BB5
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 869, 1842, 2434, 2940, 3442, 3955, 4484, 5093, 5842, 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 150 150 150
Genes 24776 19071 16211

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
4848 CNOT2 12q15 0.9234 0 0
10059 DNM1L 12p11.21 0.8579 0 0
26511 CHIC2 4q12 0.8141 0 0
55763 EXOC1 4q12 0.8066 0 0
8726 EED 11q14.2 0.7953 0 0
171017 ZNF384 12p13.31 0.792 0 0
51202 DDX47 12p13.1 0.791 0 0
55858 TMEM165 4q12 0.7869 0 0
55863 TMEM126B 11q14.1 0.7798 0 0
51729 WBP11 12p12.3 0.7754 0 0
112936 VPS26B 11q25 0.7745 0 0
55846 ITFG2 12p13.33 0.7633 0 0
8079 MLF2 12p13.31 0.7622 0 0
10526 IPO8 12p11.21 0.7621 0 0
8301 PICALM 11q14.2 0.7619 0 0
1822 ATN1 12p13.31 0.7522 0 0
55823 VPS11 11q23.3 0.7508 0 0
54477 PLEKHA5 12p12.3 0.7489 0 0
55297 CCDC91 12p11.22 0.7484 0 0
10818 FRS2 12q15 0.7472 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. The input file "TGCT-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt " is generated in the pipeline mRNAseq_Preprocess in the stddata run.

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.