amova: Analysis of molecular variance

In ade4: Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

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 [e-mail]

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.

See Also

randtest.amova

Examples

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

ade4 documentation built on Feb. 16, 2023, 7:58 p.m.