Correlations between copy number and mRNAseq expression
Kidney Chromophobe (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/C14F1Q36
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 835, 1949, 2601.5, 3200, 3789, 4356, 4967.5, 5622, 6355.5, 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 66 66 66
Genes 24776 17843 15286

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
23185 LARP4B 10p15.3 0.848 0 0
6945 MLX 17q21.2 0.8361 0 0
83607 AMMECR1L 2q14.3 0.8324 0 0
84991 RBM17 10p15.1 0.8314 0 0
7327 UBE2G2 21q22.3 0.8178 0 0
55571 CNOT11 2q11.2 0.808 2.22044604925031e-16 3.3930636078594e-12
54619 CCNJ 10q24.1 0.8065 4.44089209850063e-16 6.78568312650896e-12
22993 HMGXB3 5q32 0.7962 1.33226762955019e-15 2.03557171118973e-11
51021 MRPS16 10q22.2 0.7878 4.21884749357559e-15 6.44555520068479e-11
56888 KCMF1 2p11.2 0.7787 1.37667655053519e-14 2.10314876625262e-10
57466 SCAF4 21q22.11 0.776 1.95399252334028e-14 2.9849189786546e-10
84947 SERAC1 6q25.3 0.7701 4.08562073062058e-14 6.24078566602293e-10
201163 FLCN 17p11.2 0.7638 8.72635297355373e-14 1.33277588965086e-09
5211 PFKL 21q22.3 0.7638 8.70414851306123e-14 1.32947164388497e-09
23181 DIP2A 21q22.3 0.7636 8.97060203897126e-14 1.3699006373713e-09
670 BPHL 6p25.2 0.7636 8.90398865749376e-14 1.35981714777245e-09
57700 FAM160B1 10q25.3 0.7632 9.37028232783632e-14 1.43084211146061e-09
8575 PRKRA 2q31.2 0.7606 1.27453603226968e-13 1.94608906767257e-09
51081 MRPS7 17q25.1 0.7595 1.4388490399142e-13 2.196834714141e-09
23483 TGDS 13q32.1 0.7585 1.61426427780498e-13 2.46449727292486e-09
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 "KICH-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.