ade4: amova – R documentation

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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)
## S3 method for class 'amova'
print(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
`x`	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

`call`	call
`results`	a data frame with the degrees of freedom, the sums of squares, and the mean squares. Rows represent levels of variability.
`componentsofcovariance`	a data frame containing the components of covariance and their contribution to the total covariance
`statphi`	a data frame containing the phi-statistics

Author(s)

Sandrine Pavoine pavoine@mnhn.fr

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

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

ade4

Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

v1.7-16

GPL (>= 2)

Authors

Stéphane Dray <stephane.dray@univ-lyon1.fr>, Anne-Béatrice Dufour <anne-beatrice.dufour@univ-lyon1.fr>, and Jean Thioulouse <jean.thioulouse@univ-lyon1.fr>, with contributions from Thibaut Jombart, Sandrine Pavoine, Jean R. Lobry, Sébastien Ollier, Daniel Borcard, Pierre Legendre, Stéphanie Bougeard and Aurélie Siberchicot. Based on earlier work by Daniel Chessel.

Initial release