WebFeb 16, 2024 · The Discriminant Analysis of Principal Components (DAPC) is designed to investigate the genetic structure of biological populations. This multivariate method consists in a two-steps procedure. First, genetic data are transformed (centred, possibly scaled) and submitted to a Principal Component Analysis (PCA). WebOn the contrary, DAPC optimizes B(X) while minimizing W(X): it seeks synthetic variables, the discriminant functions, which show di erences between groups as best as possible while minimizing variation within clusters. 2 Identifying clusters using find.clusters 2.1 Rationale DAPC in itself requires prior groups to be de ned. However, groups are ...
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