A counting renaissance: combining stochastic mapping and empirical Bayes to quickly detect amino acid sites under positive selection.

ABSTRACT:

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 (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

SUBMITTER: Lemey P 

PROVIDER: S-EPMC3579240 | biostudies-literature | 2012 Dec

REPOSITORIES: biostudies-literature