OmegaSwitch: Bayesian Markov-Modulated Codon Models for Estimating dN/dS

Selective pressures can vary across both sites and evolutionary lineages; however, most codon models accommodate heterogeneity along only one of these dimensions and require the number of selective regimes to be specified in advance. Here, we introduce OmegaSwitch , a Bayesian phylogenetic software framework for inferring changes in the nonsynonymous-to-synonymous substitution-rate ratio ( dN/dS ) across sites and through evolutionary time. We implement a Markov-modulated codon model in which lineages transition among discrete dN/dS regimes and use reversible-jump Markov chain Monte Carlo to infer the number of regimes simultaneously. We further develop a Dirichlet-process mixture extension that allows the parameters governing these time-heterogeneous processes to vary among sites. Ancestral sampling produces joint posterior distributions of dN/dS across sites and nodes of the phylogeny, enabling lineage- and site-specific summaries with quantified un-certainty. Simulation analyses showed that both the posterior intervals for dN/dS and the number of evolutionary regimes were well calibrated under both models. We demonstrate OmegaSwitch using vertebrate α - and β -globins. OmegaSwitch therefore provides a flexible Bayesian framework for investigating how selective pressures vary across protein-coding sequences and phylogenetic history.