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Oxford University Press, Molecular Biology and Evolution, 5(31), p. 1261-1271, 2014

DOI: 10.1093/molbev/msu061

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Novel Information Theory-Based Measures for Quantifying Incongruence among Phylogenetic Trees

Journal article published in 2014 by Leonidas Salichos, Alexandros Stamatakis, Antonis Rokas ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Phylogenies inferred from different data matrices often conflict with each other necessitating the development of measures that quantify this incongruence. Here, we introduce novel measures that use information theory to quantify the degree of conflict or incongruence among all non-trivial bipartitions present in a set of trees. The first measure, Internode Certainty (IC), calculates the degree of certainty for a given internode by considering the frequency of the bipartition defined by the internode (internal branch) in a given set of trees jointly with that of the most prevalent conflicting bipartition in the same tree set. The second measure, Internode Certainty All (ICA), calculates the degree of certainty for a given internode by considering the frequency of the bipartition defined by the internode in a given set of trees in conjunction with that of all conflicting bipartitions in the same underlying tree set. Finally, the Tree Certainty (TC) and Tree Certainty All (TCA) measures are the sum of IC and ICA values across all internodes of a phylogeny, respectively. IC, ICA, TC, and TCA can be calculated from different types of data that contain non-trivial bipartitions, including from bootstrap replicate trees, gene trees or individual characters. Given a set of phylogenetic trees, the IC and ICA values of a given internode reflect its specific degree of incongruence, and the TC and TCA values describe the global degree of incongruence between trees in the set. All four measures are implemented and freely available in version 8.0.0 and subsequent versions of the widely-used program RAxML.