adegenet (version 1.4-2)

makefreq: Function to generate allelic frequencies

Description

The function makefreq generates a table of allelic frequencies from an object of class genpop.

Usage

makefreq(x,quiet=FALSE,missing=NA,truenames=TRUE)

Arguments

x

an object of class genpop.

quiet

logical stating whether a conversion message must be printed (TRUE,default) or not (FALSE).

missing

treatment for missing values. Can be NA, 0 or "mean" (see details)

truenames

a logical indicating whether true labels (as opposed to generic labels) should be used to name the output.

Value

• Returns a list with the following components:
• tab
  matrix of allelic frequencies (rows: populations; columns: alleles).
• nobs
  number of observations (i.e. alleles) for each population x locus combinaison.
• call
  the matched call

encoding

UTF-8

Details

There are 3 treatments for missing values: - NA: kept as NA. - 0: missing values are considered as zero. Recommended for a PCA on compositionnal data. - "mean": missing values are given the mean frequency of the corresponding allele. Recommended for a centred PCA.

See Also

genpop

Examples

data(microbov)
obj1 <- microbov

obj2 <- genind2genpop(obj1)

Xfreq <- makefreq(obj2,missing="mean")


# perform a correspondance analysis on counts data

Xcount <- genind2genpop(obj1,missing="chi2")
ca1 <- dudi.coa(as.data.frame(Xcount@tab),scannf=FALSE)
s.label(ca1$li,sub="Correspondance Analysis",csub=1.2)
add.scatter.eig(ca1$eig,nf=2,xax=1,yax=2,posi="topleft")

# perform a principal component analysis on frequency data
pca1 <- dudi.pca(Xfreq$tab,scale=FALSE,scannf=FALSE)
s.label(pca1$li,sub="Principal Component Analysis",csub=1.2)
add.scatter.eig(pca1$eig,nf=2,xax=1,yax=2,posi="top")