title: Identifying and reconstructing lateral transfers from distance matrices by combining the minimum contradiction method and neighbor-net.
abstract: Identifying lateral gene transfers is an important problem in evolutionary biology. Under a simple model of evolution, the expected values of an evolutionary distance matrix describing a phylogenetic tree fulfill the so-called Kalmanson inequalities. The Minimum Contradiction method for identifying lateral gene transfers exploits the fact that lateral transfers may generate large deviations from the Kalmanson inequalities. Here a new approach is presented to deal with such cases that combines the Neighbor-Net algorithm for computing phylogenetic networks with the Minimum Contradiction method. A subset of taxa, prescribed using Neighbor-Net, is obtained by measuring how closely the Kalmanson inequalities are fulfilled by each taxon. A criterion is then used to identify the taxa, possibly involved in a lateral transfer between nonconsecutive taxa. We illustrate the utility of the new approach by applying it to a distance matrix for Archaea, Bacteria, and Eukaryota.
authors.affiliation: School of Computing Sciences, University of East Anglia, Norwich NR47TJ, UK. Thuillweb@hotmail.com
authors.forename: Marc
authors.initials: M
authors.lastname: Thuillard
authors.forename: Vincent
authors.initials: V
authors.lastname: Moulton
mesh_terms: D000465:Algorithms; D001419:Bacteria / Q000145:classification / Q000235:genetics; D005075:Biological Evolution; D019295:Computational Biology / Q000379:methods* / Q000706:statistics & numerical data; D022761:Gene Transfer, Horizontal; D016680:Genome, Bacterial; D008957:Models, Genetic; D015233:Models, Statistical; D010802:Phylogeny