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Phylogenetic trees based on gene content
Author(s) -
Daniel H. Huson,
Mike Steel
Publication year - 2004
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bth198
Subject(s) - phylogenetic tree , tree (set theory) , tree rearrangement , character (mathematics) , measure (data warehouse) , post hoc , computer science , maximum parsimony , genetic distance , phylogenetics , gene , algorithm , statistics , artificial intelligence , mathematics , data mining , biology , combinatorics , genetics , clade , medicine , geometry , dentistry , genetic variation
Comparing gene content between species can be a useful approach for reconstructing phylogenetic trees. In this paper, we derive a maximum-likelihood estimation of evolutionary distance between species under a simple model of gene genesis and gene loss. Using simulated data on a biological tree with 107 taxa (and on a number of randomly generated trees), we compare the accuracy of tree reconstruction using this ML distance measure to an earlier ad hoc distance. We then compare these distance-based approaches to a character-based tree reconstruction method (Dollo parsimony) which seems well suited to the analysis of gene content data. To simplify simulations, we give a formal proof of the well-known 'fact' that the Dollo parsimony score is independent of the choice of root. Our results show a consistent trend, with the character-based method and ML distance measure outperforming the earlier ad hoc distance method.

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