LUSC/00: Correlations between copy number and mRNA expression
Overview
Introduction

The same TCGA sample is profiled to detect the copy number variations and expressions of genes. This pipeline tries to correlate the copy number and expression data of genes across samples to if the copy number variations of genes also result in differential expressions

Summary

This page contains the calculated correlation coefficients based on measurements of genomic copy number (log2) values and intensitiy of the expressions of the the corresponding feature across patients. High positive/low negative correlation coefficients indicate that genomic alterations result in differences in the expressions of the features (microRNA or mRAN) the genomic regions transcribe.

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 correltion coefficients.

Table 1.  Counts of mRNA and number of samples in copy number and expression data sets and common to both

Category Copy number Expression Common
Sample 142 134 117
Genes 29390 17932 15649

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. Points deviating from the blue line indicate deviation from normality.

Table 2.  Get Full Table Top 20 features (defined by the Hybridization.REF column) ranked by correlation coefficients

Hybridization.REF cor p q chrom start end geneid
LSM1 0.9237 0 0 8 38140014 38153183 27257
FADD 0.915 0 0 11 69726917 69731144 8772
ASH2L 0.9139 0 0 8 38082223 38116216 9070
PPFIA1 0.9026 0 0 11 69794471 69908150 8500
WHSC1L1 0.9017 0 0 8 38251717 38358947 54904
DCUN1D1 0.9015 0 0 3 184143253 184181020 54165
ORAOV1 0.8936 0 0 11 69189512 69199346 220064
C9orf82 0.8842 0 0 9 26830683 26882725 79886
DDHD2 0.8776 0 0 8 38208264 38238143 23259
ATP11B 0.8765 0 0 3 183993985 184122117 23200
PAF1 0.8752 0 0 19 44568109 44573519 54623
PPIE 0.8738 0 0 1 39977117 40002173 10450
ZNF639 0.8724 0 0 3 180524245 180536014 51193
EIF2B5 0.8722 0 0 3 185335818 185345790 8893
KRIT1 0.8697 0 0 7 91666219 91713350 889
STARD3 0.8689 0 0 17 35046938 35073263 10948
CTTN 0.8676 0 0 11 69922292 69960338 2017
BRF2 0.8623 0 0 8 37820558 37826569 55290
PLAA 0.8611 0 0 9 26894518 26937138 9373
ABCF3 0.8607 0 0 3 185386580 185394487 55324
Methods & Data
Input

Level III gene level expression data and gene by sample copy number data derived by using the CNTools package of Bioconductor were used for the calculations. Pearson 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.