A counting renaissance: combining stochastic mapping and empirical Bayes to quickly detect amino acid sites under positive selection.
BACKGROUND
Statistical methods for comparing relative rates of synonymous and non-synonymous substitutions maintain a central role in detecting positive selection. To identify selection, researchers often estimate the ratio of these relative rates (dN/dS) at individual alignment sites. Fitting a codon substitution model that captures heterogeneity in dN/dS across sites provides a reliable way to perform such estimation, but it remains computationally prohibitive for massive datasets. By using crude estimates of the numbers of synonymous and non-synonymous substitutions at each site, counting approaches scale well to large datasets, but they fail to account for ancestral state reconstruction uncertainty and to provide site-specific dN/dS estimates.


RESULTS
We propose a hybrid solution that borrows the computational strength of counting methods, but augments these methods with empirical Bayes modeling to produce a relatively fast and reliable method capable of estimating site-specific dN/dS values in large datasets. Importantly, our hybrid approach, set in a Bayesian framework, integrates over the posterior distribution of phylogenies and ancestral reconstructions to quantify uncertainty about site-specific dN/dS estimates. Simulations demonstrate that this method competes well with more-principled statistical procedures and, in some cases, even outperforms them. We illustrate the utility of our method using human immunodeficiency virus, feline panleukopenia and canine parvovirus evolution examples.
Department of Microbiology and Immunology, Rega Institute, KU Leuven, B-3000 Leuven, Belgium. philippe.lemey@rega.kuleuven.be
Philippe
P
Lemey
Vladimir N
VN
Minin
Filip
F
Bielejec
Sergei L
SL
Kosakovsky Pond
Marc A
MA
Suchard
D019943:Amino Acid Substitution; D000596:Amino Acids / Q000235:genetics; D001499:Bayes Theorem; D003062:Codon; D019143:Evolution, Molecular; D008957:Models, Genetic; D010802:Phylogeny; D012641:Selection, Genetic; D016415:Sequence Alignment; D013269:Stochastic Processes; D014780:Viruses / Q000235:genetics
D000596:Amino Acids; D003062:Codon