RFsupertrees (Robinson-Foulds Supertrees) takes as input a collection of rooted trees and heuristically searches for a binary supertree that minimizes the total (rooted) Robinson-Foulds distance between the supertree and the input trees. The intuition behind seeking a binary supertree, even though the input trees may be non-binary (unresolved), is that, under this setting, minimizing the RF distance is equivalent to maximizing the number of shared clades (or clusters) between the input trees and the supertree. Thus, an RF supertree is a supertree that is consistent with the largest number of clusters from the input trees. The program can quickly compute accurate supertrees for even large datasets containing thousands of input trees with many hundreds of taxa.
Computational Biology Laboratory, Department of Computer Science,Iowa State University
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Mukul S. Bansal, J. G. Burleigh, Oliver Eulenstein, David Fernandez-Baca.
Algorithms for Molecular Biology 2010, 5:18.