Assessing Clustering Results with Reference Taxonomies

Gabriel Valiente (valiente@lsi.upc.edu)

Algorithms, Bioinformatics, Complexity and Formal Methods Research Group, Technical University of Catalonia, E-08034 Barcelona, Spain


Abstract

The comparative analysis of phylogenies obtained using different phylogenetic methods or different gene sequences for a given set of species, is usually done by computing some quantitative measure of similarity between the phylogenetic trees. Such a quantitative approach provides little insight into the actual similarities and differences between the alternative phylogenies.
In this paper, we present a method for the qualitative assessment of a phylogenetic tree against a reference taxonomy, based on highlighting their common clusters. Our algorithms build a reference taxonomy for the taxa present in a given phylogenetic tree and produce a dendogram for the input phylogenetic tree, with branches in those clusters common to the reference taxonomy highlighted. Our implementation of the algorithms produces publication-quality graphics.
For unrooted phylogenies, the method produces a radial cladogram for the input phylogenetic tree, with branches in common clusters to the reference taxonomy highlighted.

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Japanese Society for Bioinformatics