amova: Analysis of molecular variance

Description

The analysis of molecular variance tests the differences among population and/or groups of populations in a way similar to ANOVA. It includes evolutionary distances among alleles.

Usage

amova(samples, distances, structures)
print.amova(x, full = FALSE, ...)

Arguments

samples

a data frame with haplotypes (or genotypes) as rows, populations as columns and abundance as entries

distances

an object of class dist computed from Euclidean distance. If distances is null, equidistances are used.

structures

a data frame containing, in the jth row and the kth column, the name of the group of level k to which the jth population belongs

an object of class amova

full

a logical value indicating whether the original data ('distances','samples','structures') should be printed

...

further arguments passed to or from other methods

Value

Returns a list of class amova
callcall
resultsa data frame with the degrees of freedom, the sums of squares, and the mean squares. Rows represent levels of variability.
componentsofcovariancea data frame containing the components of covariance and their contribution to the total covariance
statphia data frame containing the phi-statistics

References

Excoffier, L., Smouse, P.E. and Quattro, J.M. (1992) Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics, 131, 479--491.

Examples

Run this code

data(humDNAm)
amovahum <- amova(humDNAm$samples, sqrt(humDNAm$distances), humDNAm$structures)
amovahum