Identifying Stocks in Genetic Data

Provides a mixture model for clustering individuals (or sampling groups) into stocks based on their genetic profile. Here, sampling groups are individuals that are sure to come from the same stock (e.g. breeding adults or larvae). The mixture (log-)likelihood is maximised using the EM-algorithm after find good starting values via a K-means clustering of the genetic data. Details can be found in Foster, Feutry, Grewe, Berry, Hui, Davies (2019) Reliably Discriminating Stock Structure with Genetic Markers: Mixture Models with Robust and Fast Computation. Molecular Ecology Resources.


Reference manual

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1.0.74 by Scott D. Foster, 2 years ago

Browse source code at

Authors: Scott D. Foster [aut, cre]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports stats, gtools, parallel, RColorBrewer, methods

Suggests knitr

See at CRAN