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MBE Advance Access originally published online on January 19, 2006
Molecular Biology and Evolution 2006 23(5):919-926; doi:10.1093/molbev/msj095
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© The Author 2006. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org

Proceedings of the SMBE Tri-National Young Investigators' Workshop 2005

Control of the False Discovery Rate Applied to the Detection of Positively Selected Amino Acid Sites

Stéphane Guindon*,{dagger}, Mik Black*,{ddagger} and Allen Rodrigo*,{dagger}

* Bioinformatics Institute, University of Auckland, New Zealand; {dagger} Allan Wilson Centre for Molecular Ecology and Evolution, University of Auckland, New Zealand; and {ddagger} Department of Statistics, University of Auckland, New Zealand

E-mail: s.guindon{at}auckland.ac.nz.

In this article, we consider the probabilistic identification of amino acid positions that evolve under positive selection as a multiple hypothesis testing problem. The null hypothesis "H0,s: site s evolves under a negative selection or under a neutral process of evolution" is tested at each codon site of the alignment of homologous coding sequences. Standard hypothesis testing is based on the control of the expected proportion of falsely rejected null hypotheses or type-I error rate. As the number of tests increases, however, the power of an individual test may become unacceptably low. Recent advances in statistics have shown that the false discovery rate—in this case, the expected proportion of sites that do not evolve under positive selection among those that are estimated to evolve under this selection regime—is a quantity that can be controlled. Keeping the proportion of false positives low among the significant results generally leads to an increase in power. In this article, we show that controlling the false detection rate is relevant when searching for positively selected sites. We also compare this new approach to traditional methods using extensive simulations.

Key Words: positive selection • molecular phylogeny • false detection rate


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Home page
 Mol Biol EvolHome page
M. Anisimova and Z. Yang
Multiple Hypothesis Testing to Detect Lineages under Positive Selection that Affects Only a Few Sites
Mol. Biol. Evol., May 1, 2007; 24(5): 1219 - 1228.
[Abstract] [Full Text] [PDF]


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