Correlations between copy number and mRNAseq expression
Uterine Carcinosarcoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
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/C1DR2TFW
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 1104, 1969, 2674, 3338, 4021, 4694, 5390, 6071, 6801, 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 56 57 56
Genes 24776 18665 15941

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
23509 POFUT1 20q11.21 0.9141 0 0
91782 CHMP7 8p21.3 0.9029 0 0
10671 DCTN6 8p12 0.8924 0 0
55174 INTS10 8p21.3 0.8873 0 0
55588 MED29 19q13.2 0.8838 0 0
208 AKT2 19q13.2 0.8835 0 0
51125 GOLGA7 8p11.21 0.8832 0 0
57693 ZNF317 19p13.2 0.8819 0 0
8725 URI1 19q12 0.8788 0 0
9777 TM9SF4 20q11.21 0.8772 0 0
348793 WDR53 3q29 0.8757 0 0
6917 TCEA1 8q11.23 0.8741 0 0
526 ATP6V1B2 8p21.3 0.8697 0 0
55756 INTS9 8p21.1 0.8689 0 0
54984 PINX1 8p23.1 0.8669 0 0
1209 CLPTM1 19q13.32 0.8644 0 0
55739 CARKD 13q34 0.8627 0 0
26065 LSM14A 19q13.11 0.8593 0 0
7419 VDAC3 8p11.21 0.8585 0 0
9810 RNF40 16p11.2 0.8585 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.