Correlations between copy number and mRNAseq expression
Kidney Renal Papillary Cell Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
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/C1VX0F83
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 872.8, 1936, 2528, 3075, 3597, 4136.8, 4732, 5358.4, 6116, 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 224 213 211
Genes 23778 18037 17949

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
129685 TAF8 6p21.1 0.8261 0 0
55173 MRPS10 6p21.1 0.7899 0 0
51031 GLOD4 17p13.3 0.787 0 0
9798 IST1 16q22.2 0.7814 0 0
55776 SAYSD1 6p21.2 0.7803 0 0
26168 SENP3 17p13.1 0.7749 0 0
23070 FTSJD2 6p21.2 0.7718 0 0
57798 GATAD1 7q21.2 0.7707 0 0
9477 MED20 6p21.1 0.7664 0 0
91949 COG7 16p12.2 0.7638 0 0
9025 RNF8 6p21.2 0.7597 0 0
5528 PPP2R5D 6p21.1 0.7567 0 0
78996 C7orf49 7q33 0.7522 0 0
60528 ELAC2 17p12 0.7507 0 0
4507 MTAP 9p21.3 0.7492 0 0
84461 NEURL4 17p13.1 0.7486 0 0
9810 RNF40 16p11.2 0.7458 0 0
25844 YIPF3 6p21.1 0.7428 0 0
1801 DPH1 17p13.3 0.7416 0 0
9587 MAD2L1BP 6p21.1 0.7405 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.