Correlations between copy number and mRNAseq expression
Acute Myeloid Leukemia (Primary blood derived cancer - Peripheral blood)
15 July 2014  |  analyses__2014_07_15
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/C1M907FG
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 455, 1263.8, 1861.7, 2195, 2504, 2830.4, 3194.3, 3645, 4361.1, 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 191 173 166
Genes 23778 17276 17190

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
55069 C7orf42 7q11.21 0.769 0 0
51631 LUC7L2 7q34 0.7628 0 0
55696 RBM22 5q33.1 0.7565 0 0
51780 KDM3B 5q31.2 0.7158 0 0
1452 CSNK1A1 5q32 0.7032 0 0
84105 PCBD2 5q31.1 0.7022 0 0
9140 ATG12 5q22.3 0.7014 0 0
11333 PDAP1 7q22.1 0.699 0 0
27342 RABGEF1 7q11.21 0.6989 0 0
5395 PMS2 7p22.1 0.6939 0 0
125150 ZSWIM7 17p12 0.6862 0 0
5515 PPP2CA 5q31.1 0.6829 0 0
159090 FAM122B Xq26.3 0.6774 0 0
27297 CRCP 7q11.21 0.6752 0 0
9552 SPAG7 17p13.2 0.6727 0 0
23608 MKRN1 7q34 0.6707 0 0
55253 TYW1 7q11.21 0.669 0 0
51657 STYXL1 7q11.23 0.6617 0 0
5683 PSMA2 7p14.1 0.6577 0 0
54927 CHCHD3 7q32.3 0.6565 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.