histogramPlot {RUVcorr} | R Documentation |
histogramPlot
plots histograms of correlation values in expression data and
its reference.
histogramPlot(X, Y, legend, breaks = 40, title, col.X = "red", col.Y = "black", line = NULL)
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 |
title |
A character string describing title. |
col.X |
A vector or character string defining the color/colors associated with the data contained in |
col.Y |
The color associated with the data in |
line |
A vector giving the line type. |
breaks |
one of:
In the last three cases the number is a suggestion only; the
breakpoints will be set to |
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
.
histogramPlot
returns a plot.
Saskia Freytag
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"))