Bladder Urothelial Carinoma: Correlations between copy number and mRNAseq expression

Maintained by TCGA GDAC Team (Broad Institute/Dana-Farber Cancer Institute/Harvard Medical School)

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 953.1, 2073.2, 2793, 3464, 4157.5, 4853, 5559, 6276.8, 7075.9, 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	56	55
Genes	22749	19115	18262

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
55508	SLC35E3	12q15	0.9003	0	0
51250	C6orf203	6q21	0.8992	0	0
84299	MIEN1	17q12	0.8813	0	0
4802	NFYC	1p34.2	0.875	0	0
8089	YEATS4	12q15	0.8743	0	0
441061	MARCH11	5p15.1	0.8742	4.47575389039834e-06	1.30983908226919e-05
10818	FRS2	12q15	0.872	0	0
10450	PPIE	1p34.2	0.8706	0	0
10948	STARD3	17q12	0.8706	0	0
91782	CHMP7	8p21.3	0.8677	0	0
5709	PSMD3	17q21.1	0.8633	0	0
220064	ORAOV1	11q13.3	0.8586	0	0
51759	C9orf78	9q34.11	0.8583	0	0
79648	MCPH1	8p23.1	0.8536	0	0
329	BIRC2	11q22.2	0.8517	2.22044604925031e-16	1.02671299558178e-13
8500	PPFIA1	11q13.3	0.8496	2.22044604925031e-16	1.02671299558178e-13
3845	KRAS	12p12.1	0.8481	4.44089209850063e-16	1.71118832596964e-13
23185	LARP4B	10p15.3	0.8469	4.44089209850063e-16	1.71118832596964e-13
4507	MTAP	9p21.3	0.8464	4.44089209850063e-16	1.71118832596964e-13
55246	CCDC25	8p21.1	0.8435	6.66133814775094e-16	2.43168867374633e-13

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.

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