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Estimating Amino Acid Substitution Models: A Comparison of Dayhoff's Estimator, the Resolvent Approach and a Maximum Likelihood Method

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons50564

Spang,  Rainer
Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons50613

Vingron,  Martin
Gene regulation (Martin Vingron), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Citation

Müller, T., Spang, R., & Vingron, M. (2002). Estimating Amino Acid Substitution Models: A Comparison of Dayhoff's Estimator, the Resolvent Approach and a Maximum Likelihood Method. Molecular Biology and Evolution, 19(1), 8-13.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0010-8C8E-F
Abstract
Evolution of proteins is generally modeled as a Markov process acting on each site of the sequence. Replacement frequencies need to be estimated based on sequence alignments. Here we compare three approaches: First, the original method by Dayhoff, Schwartz, and Orcutt (1978) Atlas Protein Seq. Struc. 5:345–352, secondly, the resolvent method (RV) by Müller and Vingron (2000) J. Comput. Biol. 7(6):761–776, and finally a maximum likelihood approach (ML) developed in this paper. We evaluate the methods using a highly divergent and inhomogeneous set of sequence alignments as an input to the estimation procedure. ML is the method of choice for small sets of input data. Although the RV method is computationally much less demanding it performs only slightly worse than ML. Therefore, it is perfectly appropriate for large-scale applications.