snapclust.choose.k: Choose the number of clusters for snapclust using AIC, BIC or...

In adegenet: Exploratory Analysis of Genetic and Genomic Data

Choose the number of clusters for snapclust using AIC, BIC or AICc

Description

This function implements methods for investigating the optimal number of genetic clusters ('k') using the fast maximum-likelihood genetic clustering approach described in Beugin et al (2018). The method runs snapclust for varying values of 'k', and computes the requested summary statistics for each clustering solution to assess goodness of fit. The method is fully documented in a dedicated tutorial which can be accessed using adegenetTutorial("snapclust").

Usage

snapclust.choose.k(max, ..., IC = AIC, IC.only = TRUE)

Arguments

max	An integer indicating the maximum number of clusters to seek; snapclust will be run for all k from 2 to max.
...	Arguments passed to snapclust.
IC	A function computing the information criterion for snapclust objects. Available statistics are AIC (default), AICc, and BIC.
IC.only	A logical (TRUE by default) indicating if IC values only should be returned; if FALSE, full snapclust objects are returned.

Details

The method is described in Beugin et al (2018) A fast likelihood solution to the genetic clustering problem. Methods in Ecology and Evolution doi: 10.1111/2041-210X.12968. A dedicated tutorial is available by typing adegenetTutorial("snapclust").

Author(s)

Thibaut Jombart [e-mail]

See Also

snapclust to generate individual clustering solutions, and BIC.snapclust for computing BIC for snapclust objects.

adegenet documentation built on Feb. 16, 2023, 6 p.m.