Correlations between copy number and mRNAseq expression
Skin Cutaneous Melanoma (Metastatic)
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/C1K35T40
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 940, 1508.4, 2036.6, 2582, 3167, 3771, 4388, 5041.6, 5787, 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 367 368 367
Genes 24776 18059 15463

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
2547 XRCC6 22q13.2 0.8169 0 0
92105 INTS4 11q14.1 0.8154 0 0
55585 UBE2Q1 1q21.3 0.7914 0 0
10102 TSFM 12q14.1 0.7773 0 0
4718 NDUFC2 11q14.1 0.7768 0 0
6257 RXRB 6p21.32 0.7746 0 0
79053 ALG8 11q14.1 0.7728 0 0
55122 AKIRIN2 6q15 0.7724 0 0
54915 YTHDF1 20q13.33 0.7723 0 0
51271 UBAP1 9p13.3 0.7703 0 0
54476 RNF216 7p22.1 0.7673 0 0
54455 FBXO42 1p36.13 0.7648 0 0
6730 SRP68 17q25.1 0.764 0 0
1207 CLNS1A 11q14.1 0.7617 0 0
5537 PPP6C 9q33.3 0.7569 0 0
283219 KCTD21 11q14.1 0.7562 0 0
84893 FBXO18 10p15.1 0.756 0 0
27102 EIF2AK1 7p22.1 0.7559 0 0
9191 DEDD 1q23.3 0.7553 0 0
10540 DCTN2 12q13.3 0.7549 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 "SKCM-TM.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.