histogramPlot: Plot histogram of correlations.

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

Description

histogramPlot plots histograms of correlation values in expression data and its reference.

Usage

histogramPlot(
  X,
  Y,
  legend,
  breaks = 40,
  title,
  col.X = "red",
  col.Y = "black",
  line = NULL
)

Arguments

X	A matrix or a list of matrices of estimated gene-gene correlations.
Y	A matrix of reference gene-gene correlations (i.e. known underlying correlation structure).
legend	A vector of character strings describing the data contained in X and Y.
breaks	one of: a vector giving the breakpoints between histogram cells, a function to compute the vector of breakpoints, a single number giving the number of cells for the histogram, a character string naming an algorithm to compute the number of cells (see ‘Details’), a function to compute the number of cells. In the last three cases the number is a suggestion only; as the breakpoints will be set to pretty values, the number is limited to 1e6 (with a warning if it was larger). If breaks is a function, the x vector is supplied to it as the only argument (and the number of breaks is only limited by the amount of available memory).
title	A character string describing title.
col.X	A vector or character string defining the color/colors associated with the data contained in X.
col.Y	The color associated with the data in Y.
line	A vector giving the line type.

Details

The default for breaks is "Sturges". Other names for which algorithms are supplied are "Scott" and "FD" / "Freedman-Diaconis" Case is ignored and partial matching is used. Alternatively, a function can be supplied which will compute the intended number of breaks or the actual breakpoints as a function of x.

Value

histogramPlot 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=FALSE)
Y.hat.cor<-cor(Y.hat[,1:100])
try(dev.off(), silent=TRUE)
par(mar=c(5.1, 4.1, 4.1, 2.1), mgp=c(3, 1, 0), las=0, mfrow=c(1, 1))
histogramPlot(Y.hat.cor, Y$Sigma[1:100, 1:100], title="Simulated data", 
legend=c("RUV", "Truth"))
try(dev.off(), silent=TRUE)
histogramPlot(list(Y.hat.cor, cor(Y$Y[, 1:100])), Y$Sigma[1:100, 1:100],
title="Simulated data", col.Y="black", legend=c("RUV", "Raw", "Truth"))

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