hierfstat (version 0.5-11)

genet.dist: Classical genetic distances estimation

Description

Estimates one of several genetic distances among all pairs of populations.

Usage

genet.dist(dat,diploid=TRUE,method="Dch")

Arguments

dat

A data frame containing population of origin as the first column and multi-locus genotypes in following columns

diploid

whether the data is from a diploid (default) or haploid organism.

method

One of “Dch”,“Da”,“Ds”,“Fst”,“Dm”,“Dr”,“Cp” or “X2”, all described in Takezaki and Nei (1996). Additionally “Nei87” and “WC84” return pairwise FSTs estimated following Nei (1987) pairwise.neifst and Weir & Cockerham (1984) pp.fst respectively

Value

A matrix of pairwise genetic distance

Details

the method argument specify which genetic distance to use, among eight, all briefly described in Takezaki and Nei (1996)

“Dch” By default, Cavalli-Sforza and Edwards Chord distance (eqn 6 in the reference) is returned. This distance is used as default since Takezaki & Nei (1996) found that it was the best to retrieve the relation among samples.

“Da” This is Nei's et al genetic distance (eqn 7), performing nearly as well as “Dch”

“Ds” Nei's standard genetic distance (eqn 1). Increases linearly with diverence time but has larger variance

“Fst” Latter's and also approximately Reynolds et al Genetic distance (eqn 3)

“Dm” Nei's minimum distance (eqn 2)

“Dr” Rogers's distance (eqn 4)

“Cp” Prevosti et al's distance (eqn 5)

“X2” Sanghvi's distance (eqn 8)

“Nei87” see pairwise.neifst

“WC84” see pairwise.WCfst

References

Takezaki & Nei (1996) Genetic distances and reconstruction of Phylogenetic trees from microsatellite DNA. Genetics 144:389-399

Nei, M. (1987) Molecular Evolutionary Genetics. Columbia University Press

Weir B.S. and Cockerham C.C. (1984) Estimating F-Statistics for the Analysis of Population Structure. Evolution 38:1358

See Also

pairwise.WCfst pairwise.neifst

Examples

# NOT RUN {
data(gtrunchier)
genet.dist(gtrunchier[,-1])
genet.dist(gtrunchier[,-1],method="Dr")
# }