| plotSample {EMA} | R Documentation |
Sample representation for Principal Component Analysis (PCA)
plotSample(acp, axes = c(1, 2), new.plot = FALSE, lab = "quality", palette="rainbow", lim.cos2.sample = 0, text = TRUE, lab.title = NULL, ellipse=FALSE, ...)
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'). |
Sample representation on axes axes[1] and axes[2] colored by quality index (= cos2 of samples) or colored by lab
EMA group
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"))
plotSample(pca, lab = marty.type.cl, palette="perso.colors", ellipse=TRUE)