EMA (version 1.4.7)

plotSample: Sample representation for Principal Component Analysis

Description

Sample representation for Principal Component Analysis (PCA)

Usage

plotSample(acp, axes = c(1, 2), new.plot = FALSE, lab = "quality",
palette="rainbow", lim.cos2.sample = 0, text = TRUE,
lab.title = NULL, ellipse=FALSE, ...)

Arguments

acp

result from PCA or do.pca function

axes

axes for sample representation, by default 1 and 2

new.plot

if TRUE, a new graphical device is created, by default = FALSE

lab

character. Sample label, by default = quality (points are labelled by quality index). If lab=NULL, no label is displayed.

lim.cos2.sample

keep samples with cos2 >= lim.cos2.sample, by default = 0

palette

characters. Name of a palette, By default, "rainbow" palette

text

add sample name or not, by default = TRUE

lab.title

title for the legend, by default = NULL

ellipse

if TRUE and lab provided, draw 95$%$ confidence ellipse around barycentre of each group

...

Arguments to be passed to methods, such as graphical parameters (see 'par').

Value

Sample representation on axes axes[1] and axes[2] colored by quality index (= cos2 of samples) or colored by lab

See Also

runPCA,PCA

Examples

# NOT RUN {
data(marty)

## PCA on sample - example set
example.subset <- marty[1:100,]
pca <- runPCA(t(example.subset), verbose = FALSE, plotInertia = FALSE, plotSample = FALSE)

## Sample plot of PCA object colored by tumour type
perso.colors <- colorRampPalette(c("red", "green"))
# }
# NOT RUN {
plotSample(pca, lab = marty.type.cl, palette="perso.colors", ellipse=TRUE)
# }