Improved consensus network techniques for genome-scale phylogeny

Holland, Barbara R., Jermiin, Lars S. and Moulton, Vincent ORCID: https://orcid.org/0000-0001-9371-6435 (2006) Improved consensus network techniques for genome-scale phylogeny. Molecular Biology and Evolution, 23 (5). pp. 848-855. ISSN 0737-4038

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Abstract

Although recent studies indicate that estimating phylogenies from alignments of concatenated genes greatly reduces the stochastic error, the potential for systematic error still remains, heightening the need for reliable methods to analyze multigene data sets. Consensus methods provide an alternative, more inclusive, approach for analyzing collections of trees arising from multiple genes. We extend a previously described consensus network method for genome-scale phylogeny (Holland, B. R., K. T. Huber, V. Moulton, and P. J. Lockhart. 2004. Using consensus networks to visualize contradictory evidence for species phylogeny. Mol. Biol. Evol. 21:1459–1461) to incorporate additional information. This additional information could come from bootstrap analysis, Bayesian analysis, or various methods to find confidence sets of trees. The new methods can be extended to include edge weights representing genetic distance. We use three data sets to illustrate the approach: 61 genes from 14 angiosperm taxa and one gymnosperm, 106 genes from eight yeast taxa, and 46 members of a gene family from 15 vertebrate taxa.

Item Type:	Article
Faculty \ School:	Faculty of Science > School of Computing Sciences
UEA Research Groups:	Faculty of Science > Research Groups > Norwich Epidemiology Centre Faculty of Medicine and Health Sciences > Research Groups > Norwich Epidemiology Centre Faculty of Science > Research Groups > Computational Biology Faculty of Science > Research Groups > Computational Biology > Computational biology of RNA (former - to 2018) Faculty of Science > Research Groups > Computational Biology > Phylogenetics (former - to 2018)
Depositing User:	Vishal Gautam
Date Deposited:	23 May 2011 07:46
Last Modified:	15 Jun 2023 21:30
URI:	https://ueaeprints.uea.ac.uk/id/eprint/23297
DOI:	10.1093/molbev/msj061

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