Data from: Applications of random forest feature selection for fine-scale genetic population assignment
Emma V.A. Sylvester, Paul Bentzen, Ian R. Bradbury, Marie Clément, Jon Pearce, John Horne, Robert G. Beiko & Emma V. A. Sylvester
Genetic population assignment used to inform wildlife management and conservation efforts requires panels of highly informative genetic markers and sensitive assignment tests. We explored the utility of machine-learning algorithms (random forest, regularized random forest, and guided regularized random forest) compared with FST ranking for selection of single nucleotide polymorphisms (SNP) for fine-scale population assignment. We applied these methods to an unpublished SNP dataset for Atlantic salmon (Salmo salar) and a published SNP data set for...
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