ECDFPlot: Plot empirical cumulative distribution function for...

In RUVcorr: Removal of unwanted variation for gene-gene correlations and related analysis

Description

ECDFPlot generates empirical cumulative distribution functions (ECDF) for gene-gene correlation values.

Usage

ECDFPlot(X, Y, index = "all", col.X = "red", col.Y = "black", title, legend)

Arguments

X	A matrix or list of matrices of estimated gene-gene correlations.
Y	A matrix of reference gene-gene correlations (i.e. underlying known correlation structure).
index	A vector of indicies of genes of interest.
col.X	The color or colors for ECDF as estimated from X.
col.Y	The color for ECDF as estimated from Y.
title	A character string describing title of plot.
legend	A vector describing X and Y.

Value

ECDFPlot returns a plot.

Author(s)

Saskia Freytag

Examples

Y<-simulateGEdata(500, 500, 10, 2, 5, g=NULL, Sigma.eps=0.1, 
250, 100, intercept=FALSE, check.input=FALSE)
Y.hat<-RUVNaiveRidge(Y, center=TRUE, nc_index=251:500, 0, 10, check.input=TRUE)
Y.hat.cor<-cor(Y.hat)
par(mar=c(5.1, 4.1, 4.1, 2.1), mgp=c(3, 1, 0), las=0, mfrow=c(1, 1))
ECDFPlot(Y.hat.cor, Y$Sigma, index=1:100, title="Simulated data", 
legend=c("RUV", "Truth"))
ECDFPlot(list(Y.hat.cor, cor(Y$Y)), Y$Sigma, index=1:100, 
title="Simulated data", legend=c("RUV", "Raw", "Truth"), col.Y="black")

RUVcorr documentation built on Nov. 8, 2020, 5:10 p.m.