Literature DB >> 12116935

Random sampling of constrained phylogenies: conducting phylogenetic analyses when the phylogeny is partially known.

E A Housworth1, E P Martins.   

Abstract

Statistical randomization tests in evolutionary biology often require a set of random, computer-generated trees. For example, earlier studies have shown how large numbers of computer-generated trees can be used to conduct phylogenetic comparative analyses even when the phylogeny is uncertain or unknown. These methods were limited, however, in that (in the absence of molecular sequence or other data) they allowed users to assume that no phylogenetic information was available or that all possible trees were known. Intermediate situations where only a taxonomy or other limited phylogenetic information (e.g., polytomies) are available are technically more difficult. The current study describes a procedure for generating random samples of phylogenies while incorporating limited phylogenetic information (e.g., four taxa belong together in a subclade). The procedure can be used to conduct comparative analyses when the phylogeny is only partially resolved or can be used in other randomization tests in which large numbers of possible phylogenies are needed.

Mesh:

Year:  2001        PMID: 12116935     DOI: 10.1080/106351501753328776

Source DB:  PubMed          Journal:  Syst Biol        ISSN: 1063-5157            Impact factor:   15.683


  4 in total

1.  The limits of elaboration: curved allometries reveal the constraints on mandible size in stag beetles.

Authors:  Robert J Knell; Joanne C Pomfret; Joseph L Tomkins
Journal:  Proc Biol Sci       Date:  2004-03-07       Impact factor: 5.349

2.  Bayesian models for comparative analysis integrating phylogenetic uncertainty.

Authors:  Pierre de Villemereuil; Jessie A Wells; Robert D Edwards; Simon P Blomberg
Journal:  BMC Evol Biol       Date:  2012-06-28       Impact factor: 3.260

3.  Sperm competition and the evolution of sperm design in mammals.

Authors:  Maximiliano Tourmente; Montserrat Gomendio; Eduardo R S Roldan
Journal:  BMC Evol Biol       Date:  2011-01-13       Impact factor: 3.260

4.  SUNPLIN: simulation with uncertainty for phylogenetic investigations.

Authors:  Wellington S Martins; Welton C Carmo; Humberto J Longo; Thierson C Rosa; Thiago F Rangel
Journal:  BMC Bioinformatics       Date:  2013-11-15       Impact factor: 3.169

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.