In addition, we show how AMOVA can be used to estimate the summary statistic ρ, which was developed especially for polyploid data, but unfortunately has seen very little use.

The method can be applied to a dataset containing a single ploidy level, but also to datasets with a mixture of ploidy levels. We show how this can be done by adjusting the equations for calculating the Sums of Squares, degrees of freedom and covariance components. In this paper, we show how the Analysis of Molecular Variance (AMOVA) framework can be extended to include autopolyploid data, which will allow calculating several genetic summary statistics for estimating the strength of genetic differentiation among autopolyploid populations ( F ST, φ ST, or R ST). Also many statistical tools for the analysis of genetic data, such as AMOVA and genome scans, are available only for haploids and diploids. 2Department of Bioscience, Aarhus University, Aarhus, DenmarkĪutopolyploids present several challenges to researchers studying population genetics, since almost all population genetics theory, and the expectations derived from this theory, has been developed for haploids and diploids.1Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, Netherlands.

Genodive sample data matrix