plotPCA: Plots for Principle Component Analysis (PCA) in QSEA

In qsea: IP-seq data analysis and vizualization

Description

The principle components can be depicted using the plotting methods plotPCA and plotPCAfactors

Usage

## S4 method for signature 'qseaPCA'
plotPCA(object,plotComponents=c(1,2), fgColor="black",
    bgColor = "white", legend, plotLabels=TRUE, radius=5, labelOffset=.5,
    labelPos=1, labelAdj, labelColor="black", cex=1, ...)

## S4 method for signature 'qseaPCA'
plotPCAfactors(object,plotComponents=c(1,2), 
    fgColor="black",bgColor = "white", plotTopLabels=100, labelsOfInterest, 
    radius=1, labelOffset=.5,labelPos=1,labelColor="black", cex=1, ...)

Arguments

object	the qseaPCA object, resulting from the getPCA function
plotComponents	vector of the two components of the PCA
fgColor	vector of foreground colors for the circles
bgColor	vector of background colors for the circles
legend	add a legend to the plot
plotLabels	if set TRUE, the labels of the samples are written in the plot
radius	defines the size of the plotted circles
labelOffset	defines the offset of the labels to the circles
labelPos	specify position of the labels in the plot (see graphics::text)
labelAdj	alternative way to specify position of the labls in the plot (see graphics::text)
labelColor	a vector of colors for the labels
cex	font size of the labels
plotTopLabels	labels of factors with strongest contribution to plotted components are shown
labelsOfInterest	vector of factor names that are highlighted and labeled in the plot
...	further graphical parameters

Value

The functions return a list with the coordinates of the depicted components

Author(s)

Mathias Lienhard

See Also

plotPCA

Examples

 
qs=getExampleQseaSet( repl=5)
pca=getPCA(qs, norm_method="beta")
colors=c(rep("red", 5), rep("green", 5))

plotPCA(pca, bgColor=colors)
#plotPCAfactors is more interesting, if ROIs have been specified in getPCA
plotPCAfactors(pca)

qsea documentation built on Nov. 8, 2020, 8:28 p.m.