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MBE Advance Access originally published online on July 25, 2007
Molecular Biology and Evolution 2007 24(9):2139-2150; doi:10.1093/molbev/msm144
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© The Author 2007. 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

Research Articles

On Reduced Amino Acid Alphabets for Phylogenetic Inference

Edward Susko* and Andrew J. Roger{dagger}

* Department of Mathematics and Statistics, Dalhousie University, Halifax, Nova Scotia, Canada
{dagger} Department of Biochemistry and Molecular Biology, Dalhousie University, Halifax, Nova Scotia, Canada

E-mail: susko{at}mathstat.dal.ca.

Accepted for publication July 12, 2007.

We investigate the use of Markov models of evolution for reduced amino acid alphabets or bins of amino acids. The use of reduced amino acid alphabets can ameliorate effects of model misspecification and saturation. We present algorithms for 2 different ways of automating the construction of bins: minimizing criteria based on properties of rate matrices and minimizing criteria based on properties of alignments. By simulation, we show that in the absence of model misspecification, the loss of information due to binning is found to be insubstantial, and the use of Markov models at the binned level is found to be almost as effective as the more appropriate missing data approach. By applying these approaches to real data sets where compositional heterogeneity and/or saturation appear to be causing biased tree estimation, we find that binning can improve topological estimation in practice.

Key Words: protein evolution • amino acid alphabets • Markov models • compositional heterogeneity

Martin Embley, Associate Editor


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