Journal
BIOINFORMATICS
Volume 28, Issue 24, Pages 3248-3256Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/bts580
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Funding
- European Research Council under the European Community [278433-PREDEMICS]
- ERC [260864]
- National Science Foundation [DMS 0856099]
- National Institutes of Health [R01 GM086887, R01 HG006139]
- Bioinformatics, Statistical Analysis and Evolutionary Core of the UCSD Center for AIDS Research [5P30AI36214]
- National Evolutionary Synthesis Center (NESCent)
- Division Of Mathematical Sciences
- Direct For Mathematical & Physical Scien [0856099] Funding Source: National Science Foundation
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MOTIVATION: 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 ( ) at individual alignment sites. Fitting a codon substitution model that captures heterogeneity in 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 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 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 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.
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