Hierarchical clustering using constraints

Authors:
Mariana Kant;Maurice LeBon;David Sankoff
Affiliations:
Computer Science and Engineering Department, York University, Toronto, Canada;Computer Science and Engineering Department, York University, Toronto, Canada;Department of Mathematics and Statistics, University of Ottawa, Ottawa, Canada
Venue:
ISBRA'08 Proceedings of the 4th international conference on Bioinformatics research and applications
Year:
2008

Citing 4
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Abstract

We describe a new supertree algorithm that extends the typeof information that can be used for phylogenetic inference. Its input is aset of constraints that expresses either the hierarchical relationships ina family of given phylogenies, or/and other relations between clusters ofsets of species. The output of the algorithm is a multifurcating rootedsupertree which satisfies all constraints. Moreover, if there were contradictionsin the set of constraints the corresponding part of the supertreeis identified and its set of constraints is displayed such as the user maydecide to modify or keep it. Our algorithm is not affected by the orderin which the input phylogenies or other constraints are presented. Weapply our method to a number of data sets.