Correlations between copy number and mRNAseq expression
Ovarian Serous Cystadenocarcinoma (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/C14B30S6
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 997.5, 1676, 2293.5, 2986, 3731.5, 4481, 5164.5, 5798, 6428, 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 579 303 300
Genes 24776 18585 15836

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
54623 PAF1 19q13.2 0.889 0 0
9878 TOX4 14q11.2 0.8826 0 0
8498 RANBP3 19p13.3 0.8776 0 0
91782 CHMP7 8p21.3 0.8743 0 0
55588 MED29 19q13.2 0.8702 0 0
4848 CNOT2 12q15 0.87 0 0
84164 ASCC2 22q12.2 0.8687 0 0
6829 SUPT5H 19q13.2 0.8667 0 0
23172 FAM175B 10q26.13 0.8642 0 0
4152 MBD1 18q21.1 0.8639 0 0
6730 SRP68 17q25.1 0.8608 0 0
1487 CTBP1 4p16.3 0.8605 0 0
90379 DCAF15 19p13.12 0.8596 0 0
91445 RNF185 22q12.2 0.8568 0 0
8725 URI1 19q12 0.8567 0 0
3845 KRAS 12p12.1 0.8535 0 0
51729 WBP11 12p12.3 0.8526 0 0
25793 FBXO7 22q12.3 0.8516 0 0
54455 FBXO42 1p36.13 0.8514 0 0
51362 CDC40 6q21 0.8496 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 "OV-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.