Phylogenetic tree selection by the adjusted k-means approach

Hsiuying Wang*, Shan Lin Hung

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


The reconstruction of phylogenetic trees is one of the most important and interesting problems of the evolutionary study. There are many methods proposed in the literature for constructing phylogenetic trees. Each approach is based on different criteria and evolutionary models. However, the topologies of trees constructed from different methods may be quite different. The topological errors may be due to unsuitable criterions or evolutionary models. Since there are many tree construction approaches, we are interested in selecting a better tree to fit the true model. In this study, we propose an adjusted k-means approach and a misclassification error score criterion to solve the problem. The simulation study shows this method can select better trees among the potential candidates, which can provide a useful way in phylogenetic tree selection.

Original languageEnglish
Pages (from-to)643-655
Number of pages13
JournalJournal of Applied Statistics
Issue number3
StatePublished - 1 Mar 2012


  • adjusted k-means
  • k-means
  • misclassification error
  • phylogenetic tree


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