Correlations between copy number and mRNAseq expression
Cervical Squamous Cell Carcinoma (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
doi:10.7908/C15Q4T3N
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlations between copy number and mRNAseq expression. Broad Institute of MIT and Harvard. doi:10.7908/C15Q4T3N
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 1155.5, 1884, 2481, 3048, 3656.5, 4320, 5032.5, 5780, 6624.5, 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 126 116 111
Genes 23778 18258 18186

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
329 BIRC2 11q22.2 0.8682 0 0
25904 CNOT10 3p22.3 0.858 0 0
84259 DCUN1D5 11q22.3 0.8478 0 0
10413 YAP1 11q22.1 0.8434 0 0
10425 ARIH2 3p21.31 0.842 0 0
29102 DROSHA 5p13.3 0.8363 0 0
55892 MYNN 3q26.2 0.8319 0 0
6734 SRPR 11q24.2 0.8215 0 0
23185 LARP4B 10p15.3 0.8208 0 0
79072 FASTKD3 5p15.31 0.8179 0 0
5810 RAD1 5p13.2 0.8175 0 0
55858 TMEM165 4q12 0.8168 0 0
84893 FBXO18 10p15.1 0.816 0 0
2935 GSPT1 16p13.13 0.814 0 0
134218 DNAJC21 5p13.2 0.8138 0 0
7917 BAG6 6p21.33 0.8123 0 0
51340 CRNKL1 20p11.23 0.812 0 0
8893 EIF2B5 3q27.1 0.8117 0 0
2580 GAK 4p16.3 0.8112 0 0
9797 TATDN2 3p25.3 0.8109 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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

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