plotIndiv

plotIndiv

Individuals representation

In this plot the samples are represented as point placed according to their relation to two dimensions among those chosen in the analysis (the ncomp parameter). Such points tends to aggregate together when they are share similarities.

Usage in mixOmics

Individual 2D plots can be obtained in mixOmics via the function plotIndiv() as displayed below:

library(mixOmics)
data(nutrimouse)

diet = unmap(nutrimouse$diet)
blocks = list(gene = nutrimouse$gene, lipid = nutrimouse$lipid, diet = diet)

design = matrix(c(0,1,1,1,0,1,1,1,0), ncol = 3, nrow = 3, byrow = TRUE)


nutri.sgcca <- wrapper.sgcca(blocks,design=design, ncomp = 3)
plotIndiv(nutri.sgcca, 
          group = nutrimouse$diet, 
          ind.names = nutrimouse$diet,
          legend =TRUE, 
          ellipse = TRUE,
          ellipse.level = 0.5, 
          blocks = "lipid", 
          main = 'sgcca',
          star = TRUE, 
          centroid = TRUE)

plot of chunk unnamed-chunk-2

X <- nutrimouse$lipid
Y <- nutrimouse$gene
nutri.res <- rcc(X, Y, ncomp = 3, lambda1 = 0.064, lambda2 = 0.008)

plotIndiv(nutri.res,
          group = nutrimouse$genotype,
          ind.names = FALSE,
          legend = TRUE)

plot of chunk unnamed-chunk-3

data(liver.toxicity)

X <- liver.toxicity$gene
Y <- liver.toxicity$clinic
toxicity.spls <- spls(X, Y, ncomp = 3,
keepX = c(50, 50, 50), keepY = c(10, 10, 10))
group=rep(c("group 1","group 2","group 3","group 4"),each = 16)
##test add.legend,group

plotIndiv(toxicity.spls, 
          legend=TRUE,
          ind.names=FALSE,
          group=group)

plot of chunk unnamed-chunk-4

data("breast.tumors")
X = breast.tumors$gene.exp
Y = breast.tumors$sample$treatment
breast.plsda<- plsda(X,Y, ncomp=10)    
 ##plot.ellipse and ellipse.level

plotIndiv(breast.plsda,
          comp= c(1,2),
          ind.names = breast.tumors$sample$treatment,
          ellipse.level=0.5,
          ellipse=TRUE)

plot of chunk unnamed-chunk-5

liver.spca= spca(liver.toxicity$gene,ncomp=3)

plotIndiv(liver.spca,
          ind.names=FALSE,
          legend=TRUE,
          ellipse=TRUE,
          group=liver.toxicity$treatment[, 3],
          style="graphics") 

plot of chunk unnamed-chunk-6

### Multilevel
data(vac18)
X <- vac18$genes
Y <- vac18$stimulation

# sample indicates the repeated measurements
# setup the design matrix by indicating the repeated measurements
design <- data.frame(sample = vac18$sample)

# multilevel sPLS-DA model
vac18.splsda.multilevel <- splsda(X, 
                                  Y = vac18$stimulation, 
                                  multilevel = design, 
                                  ncomp = 3, 
                                  keepX = c(30, 137, 123))

plotIndiv(vac18.splsda.multilevel, 
          rep.space = 'XY-variate',
          ind.names = vac18$stimulation,
          pch = 20,
          main = 'Both Gene expression and Stimulation subspaces',
          legend = TRUE)

plot of chunk unnamed-chunk-7

plotIndiv(nutri.sgcca, 
          group = nutrimouse$diet, 
          ind.names = nutrimouse$diet,
          legend =TRUE, 
          ellipse = TRUE,
          ellipse.level = 0.5, 
          blocks = "lipid", 
          main = '3D-Nutrimouse',
          star = TRUE, 
          centroid = TRUE,
          style='3d')

Nutrimouse 3D-Plot