## Not run: 
data(microbov)
microbov
summary(microbov)

# make Y, a genpop object
Y <- genind2genpop(microbov)

# make allelic frequency table
temp <- makefreq(Y,missing="mean")
X <- temp$tab
nsamp <- temp$nobs

# perform 1 PCA per marker

kX <- ktab.data.frame(data.frame(X),Y@loc.n.all)

kpca <- list()
for(i in 1:30) {kpca[[i]] <- dudi.pca(kX[[i]],scannf=FALSE,nf=2,center=TRUE,scale=FALSE)}


sel <- sample(1:30,4)
col = rep('red',15)
col[c(2,10)] = 'darkred'
col[c(4,12,14)] = 'deepskyblue4'
col[c(8,15)] = 'darkblue'

# display %PCA
par(mfrow=c(2,2))
for(i in sel) {
s.multinom(kpca[[i]]$c1,kX[[i]],n.sample=nsamp[,i],coulrow=col,sub=locNames(Y)[i])
add.scatter.eig(kpca[[i]]$eig,3,xax=1,yax=2,posi="top")
}

# perform a Multiple Coinertia Analysis
kXcent <- kX
for(i in 1:30) kXcent[[i]] <- as.data.frame(scalewt(kX[[i]],center=TRUE,scale=FALSE))
mcoa1 <- mcoa(kXcent,scannf=FALSE,nf=3, option="uniform")

# coordinated %PCA
mcoa.axes <- split(mcoa1$axis, Y@loc.fac)
mcoa.coord <- split(mcoa1$Tli,mcoa1$TL[,1])
var.coord <- lapply(mcoa.coord,function(e) apply(e,2,var))

par(mfrow=c(2,2))
for(i in sel) {
s.multinom(mcoa.axes[[i]][,1:2],kX[[i]],n.sample=nsamp[,i],coulrow=col,sub=locNames(Y)[i])
add.scatter.eig(var.coord[[i]],2,xax=1,yax=2,posi="top")
}

# reference typology
par(mfrow=c(1,1))
s.label(mcoa1$SynVar,lab=popNames(microbov),sub="Reference typology",csub=1.5)
add.scatter.eig(mcoa1$pseudoeig,nf=3,xax=1,yax=2,posi="top")

# typologial values
tv <- mcoa1$cov2
tv <- apply(tv,2,function(c) c/sum(c))*100
rownames(tv) <- locNames(Y)
tv <- tv[order(locNames(Y)),]

par(mfrow=c(3,1),mar=c(5,3,3,4),las=3)
for(i in 1:3){
barplot(round(tv[,i],3),ylim=c(0,12),yaxt="n",main=paste("Typological value -
structure",i))
axis(side=2,at=seq(0,12,by=2),labels=paste(seq(0,12,by=2),"%"),cex=3)
abline(h=seq(0,12,by=2),col="grey",lty=2)
}

## End(Not run)