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Summary: Syst. Biol. 55(4):539552, 2006
Copyright c Society of Systematic Biologists
ISSN: 1063-5157 print / 1076-836X online
DOI: 10.1080/10635150600755453
Approximate Likelihood-Ratio Test for Branches: A Fast, Accurate,
and Powerful Alternative
MARIA ANISIMOVA1,2
AND OLIVIER GASCUEL1
1
Equipe M´ethodes et Algorithmes pour la Bioinformatique LIRMM-CNRS, Universit´e Montpellier II, Montpellier 34392, France;
E-mail: manisimova@hotmail.com (M.A.); gascuel@lirmm.fr (O.G.)
2
Current Address: Biology Department, University College London, Darwin building, Gower Street, London WC1E 6BT, United Kingdom
Abstract.--We revisit statistical tests for branches of evolutionary trees reconstructed upon molecular data. A new, fast, ap-
proximate likelihood-ratio test (aLRT) for branches is presented here as a competitive alternative to nonparametric bootstrap
and Bayesian estimation of branch support. The aLRT is based on the idea of the conventional LRT, with the null hypothesis
corresponding to the assumption that the inferred branch has length 0. We show that the LRT statistic is asymptotically dis-
tributed as a maximum of three random variables drawn from the 1
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