Correlations between copy number and mRNAseq expression
Breast Invasive Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
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/C19S1PR9
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 1037, 1602.4, 2132, 2708, 3344.5, 4032.2, 4736.9, 5435.6, 6219, 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 1044 1058 1040
Genes 23778 18294 18218

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
9070 ASH2L 8p11.23 0.9168 0 0
5709 PSMD3 17q21.1 0.8886 0 0
55290 BRF2 8p11.23 0.8851 0 0
11212 PROSC 8p11.23 0.8849 0 0
65264 UBE2Z 17q21.32 0.8802 0 0
10948 STARD3 17q12 0.8778 0 0
22794 CASC3 17q21.1 0.8721 0 0
27257 LSM1 8p11.23 0.8718 0 0
8772 FADD 11q13.3 0.8674 0 0
54883 CWC25 17q12 0.8637 0 0
339287 MSL1 17q21.1 0.8623 0 0
83877 TM2D2 8p11.22 0.8545 0 0
1207 CLNS1A 11q14.1 0.8538 0 0
51125 GOLGA7 8p11.21 0.8513 0 0
23259 DDHD2 8p11.23 0.8512 0 0
2064 ERBB2 17q12 0.8493 0 0
80185 TTI2 8p12 0.8478 0 0
92105 INTS4 11q14.1 0.8427 0 0
54904 WHSC1L1 8p11.23 0.8422 0 0
57805 KIAA1967 8p21.3 0.8416 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.