adegenet (version 2.1.10)

genpop class: adegenet formal class (S4) for allele counts in populations

Description

An object of class genpop contain alleles counts for several loci.
It contains several components (see 'slots' section).
Such object is obtained using genind2genpop which converts individuals genotypes of known population into a genpop object. Note that the function summary of a genpop object returns a list of components. Note that as in other S4 classes, slots are accessed using @ instead of $.

Slots

tab:

matrix of alleles counts for each combinaison of population (in rows) and alleles (in columns).

loc.fac:

locus factor for the columns of tab

loc.n.all:

integer vector giving the number of alleles per locus

all.names:

list having one component per locus, each containing a character vector of alleles names

call:

the matched call

ploidy:

an integer indicating the degree of ploidy of the genotypes. Beware: 2 is not an integer, but as.integer(2) is.

type:

a character string indicating the type of marker: 'codom' stands for 'codominant' (e.g. microstallites, allozymes); 'PA' stands for 'presence/absence' (e.g. AFLP).

other:

(optional) a list containing other information

Extends

Class "gen", directly. Class "popInfo", directly.

Methods

names

signature(x = "genpop"): give the names of the components of a genpop object

print

signature(x = "genpop"): prints a genpop object

show

signature(object = "genpop"): shows a genpop object (same as print)

summary

signature(object = "genpop"): summarizes a genpop object, invisibly returning its content or suppress printing of auxiliary information by specifying verbose = FALSE

Author

Thibaut Jombart

See Also

as.genpop, is.genpop,makefreq, genind, import2genind, read.genetix, read.genepop, read.fstat

Examples

obj1 <- import2genind(system.file("files/nancycats.gen",
package="adegenet"))
obj1


obj2 <- genind2genpop(obj1)
obj2

if (FALSE) {
data(microsatt)
# use as.genpop to convert convenient count tab to genpop
obj3 <- as.genpop(microsatt$tab)
obj3

all(obj3@tab==microsatt$tab)

# perform a correspondance analysis
obj4 <- genind2genpop(obj1,missing="chi2")
ca1 <- dudi.coa(as.data.frame(obj4@tab),scannf=FALSE)
s.label(ca1$li,sub="Correspondance Analysis",csub=2)
add.scatter.eig(ca1$eig,2,xax=1,yax=2,posi="top")

}