Correlations between copy number and mRNAseq expression
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 895, 1605, 2133, 2652, 3227.5, 3832.6, 4412.7, 5041.8, 5776.9, 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 441 274 272
Genes 24776 22490 16232

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
84299 MIEN1 17q12 0.8725 0 0
9862 MED24 17q21.1 0.862 0 0
147179 WIPF2 17q21.1 0.859 0 0
6605 SMARCE1 17q21.2 0.8519 0 0
22794 CASC3 17q21.1 0.833 0 0
93210 PGAP3 17q12 0.8325 0 0
51507 RTFDC1 20q13.31 0.8284 0 0
9070 ASH2L 8p11.23 0.8237 0 0
6780 STAU1 20q13.13 0.8195 0 0
8725 URI1 19q12 0.8184 0 0
2064 ERBB2 17q12 0.8168 0 0
339287 MSL1 17q21.1 0.8166 0 0
3845 KRAS 12p12.1 0.8129 0 0
9491 PSMF1 20p13 0.8096 0 0
252969 NEIL2 8p23.1 0.8072 0 0
91782 CHMP7 8p21.3 0.8068 0 0
5786 PTPRA 20p13 0.8035 0 0
84060 RBM48 7q21.2 0.8007 0 0
29883 CNOT7 8p22 0.7937 0 0
55661 DDX27 20q13.13 0.7925 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.