Correlations between copy number and mRNAseq expression
Pheochromocytoma and Paraganglioma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
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 (2016): Correlations between copy number and mRNAseq expression. Broad Institute of MIT and Harvard. doi:10.7908/C1125S3T
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 746.8, 1608.6, 2177, 2724.2, 3239, 3774, 4357, 5063.4, 5924.2, 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 162 179 162
Genes 24776 17994 15369

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
10946 SF3A3 1p34.3 0.8932 0 0
7879 RAB7A 3q21.3 0.8753 0 0
7251 TSG101 11p15.1 0.8638 0 0
55108 BSDC1 1p35.1 0.8596 0 0
200081 TXLNA 1p35.1 0.8471 0 0
28976 ACAD9 3q21.3 0.8471 0 0
4898 NRD1 1p32.3 0.8388 0 0
10342 TFG 3q12.2 0.8356 0 0
90231 KIAA2013 1p36.22 0.8352 0 0
60313 GPBP1L1 1p34.1 0.8303 0 0
51441 YTHDF2 1p35.3 0.8288 0 0
25921 ZDHHC5 11q12.1 0.8258 0 0
4927 NUP88 17p13.2 0.8249 0 0
22916 NCBP2 3q29 0.8232 0 0
9861 PSMD6 3p14.1 0.8224 0 0
10425 ARIH2 3p21.31 0.8218 0 0
26155 NOC2L 1p36.33 0.8206 0 0
2782 GNB1 1p36.33 0.8198 0 0
9567 GTPBP1 22q13.1 0.8193 0 0
26284 ERAL1 17q11.2 0.8183 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. The input file "PCPG-TP.uncv2.mRNAseq_RSEM_normalized_log2.txt " is generated in the pipeline mRNAseq_Preprocess in the stddata run.

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.