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Bioinformatics. 2014 Jun 15;30(12):i87-95. doi: 10.1093/bioinformatics/btu289.

Pareto-optimal phylogenetic tree reconciliation.

Author information

1
Department of Computer Science, Harvey Mudd College, Claremont, CA 91711, Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA 02139, Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269 and Broad Institute, Cambridge, MA 02142, USA.
2
Department of Computer Science, Harvey Mudd College, Claremont, CA 91711, Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA 02139, Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269 and Broad Institute, Cambridge, MA 02142, USADepartment of Computer Science, Harvey Mudd College, Claremont, CA 91711, Department of Electrical Engineering and Computer Science, MIT, Cambridge, MA 02139, Department of Computer Science and Engineering, University of Connecticut, Storrs, CT 06269 and Broad Institute, Cambridge, MA 02142, USA.

Abstract

MOTIVATION:

Phylogenetic tree reconciliation is a widely used method for reconstructing the evolutionary histories of gene families and species, hosts and parasites and other dependent pairs of entities. Reconciliation is typically performed using maximum parsimony, in which each evolutionary event type is assigned a cost and the objective is to find a reconciliation of minimum total cost. It is generally understood that reconciliations are sensitive to event costs, but little is understood about the relationship between event costs and solutions. Moreover, choosing appropriate event costs is a notoriously difficult problem.

RESULTS:

We address this problem by giving an efficient algorithm for computing Pareto-optimal sets of reconciliations, thus providing the first systematic method for understanding the relationship between event costs and reconciliations. This, in turn, results in new techniques for computing event support values and, for cophylogenetic analyses, performing robust statistical tests. We provide new software tools and demonstrate their use on a number of datasets from evolutionary genomic and cophylogenetic studies.

AVAILABILITY AND IMPLEMENTATION:

Our Python tools are freely available at www.cs.hmc.edu/∼hadas/xscape. .

PMID:
24932009
PMCID:
PMC4058917
DOI:
10.1093/bioinformatics/btu289
[Indexed for MEDLINE]
Free PMC Article

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