Correlations between copy number and mRNA expression
Lung Adenocarcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
Maintained by John Zhang (MD Anderson Cancer Center)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlations between copy number and mRNA expression. Broad Institute of MIT and Harvard. doi:10.7908/C14X56PZ
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 expression 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 intensity of the expressions of the corresponding feature across patients. High positive/low negative correlation coefficients indicate that genomic alterations result in differences in the expressions of mRNA the genomic regions transcribe.

Summary

The correlation coefficients in 10, 20, 30, 40, 50, 60, 70, 80, 90 percentiles are -0.12386, -0.0213, 0.0588, 0.12796, 0.1998, 0.27354, 0.3463, 0.42448, 0.53104, 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 mRNA and number of samples in copy number and expression data sets and common to both

Category Copy number Expression Common
Sample 515 32 32
Genes 24771 17814 15175

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

feature r p-value q-value chrom start end geneid
C14ORF166 0.9206 8.72635297355373e-14 3.78742242152304e-10 51637 14q22.1 0.012 0.074
EDC3 0.9205 8.92619311798626e-14 3.78742242152304e-10 80153 15q24.1 -0.271 -0.272
PIK3C3 0.9116 4.09672296086683e-13 1.15883820360033e-09 -5773 18q12.3 0.033 -0.195
C18ORF21 0.8846 1.85531590091159e-11 3.93609288374103e-08 83608 18q12.2 0.033 -0.195
FBXO33 0.881 2.88977730633633e-11 4.904580135589e-08 -4610 14q21.1 0.012 0.074
SCFD1 0.8721 7.96775978528785e-11 1.06937212570286e-07 23256 14q12 0.044 0.074
FKBP3 0.8712 8.82103279309376e-11 1.06937212570286e-07 2287 14q21.2 0.012 0.074
PSMC6 0.8642 1.86242798960734e-10 1.97559066700493e-07 5706 14q22.1 0.012 0.074
C14ORF28 0.8563 4.10091072211571e-10 3.85983190849532e-07 122525 14q21.2 0.012 0.074
LSG1 0.8553 4.54842385977372e-10 3.85983190849532e-07 55341 3q29 0.006 -0.230
MOCS3 0.8483 8.75288286295017e-10 6.52595808753857e-07 27304 20q13.13 -0.311 0.334
STX5 0.8477 9.22822263049738e-10 6.52595808753857e-07 6811 11q12.3 0.280 0.067
POP4 0.8429 1.43093403792705e-09 9.34079251122529e-07 -5965 19q12 -0.016 0.000
SMAD2 0.8378 2.22337082078639e-09 1.34769410601872e-06 4087 18q21.1 0.033 -0.195
ZNF24 0.8314 3.78379727550282e-09 2.14064210805396e-06 7572 18q12.2 0.033 -0.195
PSMA6 0.8306 4.05536382253047e-09 2.15088555471875e-06 5687 14q13.2 0.044 0.074
C6ORF203 0.8292 4.53580017989452e-09 2.26418784961216e-06 51250 6q21 -0.251 0.290
RPL36AL 0.8273 5.25916044047392e-09 2.39384158118795e-06 -4621 14q21.3 0.012 0.074
SIAH2 0.8271 5.35971311776962e-09 2.39384158118795e-06 6478 3q25.1 0.006 -0.230
IER3IP1 0.8262 5.75888403631097e-09 2.44351945266852e-06 -5779 18q21.1 0.033 -0.195
Methods & Data
Input

Gene level (TCGA Level III) expression data and copy number data of the corresponding loci 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.

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.