PCAPlot {RUVcorr} | R Documentation |
PCAPlot
generates principle component plots for with the possibility
to color arrays according to a known factor.
PCAPlot(Y, comp = c(1, 2), anno = NULL, Factor = NULL, numeric = FALSE, new.legend = NULL, title)
Y |
A matrix of gene expression values or an object of class |
comp |
A vector of length 2 specifying which principle components to be used. |
anno |
A dataframe or a matrix containing the annotation of the arrays. |
Factor |
A character string describing the column name of
|
numeric |
A logical scalar indicating whether |
new.legend |
A vector describing the names used for labelling; if |
title |
A character string giving the title. |
PCAPlot
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) PCAPlot(Y$Y, title="") ## Create random annotation file anno<-as.matrix(sample(1:4, dim(Y$Y)[1], replace=TRUE)) colnames(anno)<-"Factor" 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)) PCAPlot(Y$Y, anno=anno, Factor="Factor", numeric=TRUE, title="")