Correlations between copy number and mRNAseq expression
Lung Squamous Cell Carcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
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/C1BC3XGJ
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 1032, 1662.8, 2221, 2807.6, 3454.5, 4145, 4805.3, 5443, 6107, 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 501 501 498
Genes 24776 18514 15820

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
8500 PPFIA1 11q13.3 0.9212 0 0
8772 FADD 11q13.3 0.9031 0 0
8451 CUL4A 13q34 0.8794 0 0
9070 ASH2L 8p11.23 0.879 0 0
27257 LSM1 8p11.23 0.8746 0 0
220064 ORAOV1 11q13.3 0.8734 0 0
54904 WHSC1L1 8p11.23 0.8725 0 0
55588 MED29 19q13.2 0.8516 0 0
51193 ZNF639 3q26.33 0.8493 0 0
208 AKT2 19q13.2 0.8415 0 0
11212 PROSC 8p11.23 0.8407 0 0
83877 TM2D2 8p11.22 0.8392 0 0
8087 FXR1 3q26.33 0.8377 0 0
55234 SMU1 9p21.1 0.8364 0 0
54623 PAF1 19q13.2 0.835 0 0
54926 UBE2R2 9p13.3 0.8276 0 0
7415 VCP 9p13.3 0.8248 0 0
5584 PRKCI 3q26.2 0.8167 0 0
9878 TOX4 14q11.2 0.8147 0 0
84513 PPAPDC1B 8p11.23 0.8119 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.