English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

By providing a framework of accounting for the shared ancestry inherent toall life, phylogenetics is becoming the statistical foundation of biology. Theimportance of model choice continues to grow as phylogenetic models continue toincrease in complexity to better capture micro and macroevolutionary processes.In a Bayesian framework, the marginal likelihood is how data update our priorbeliefs about models, which gives us an intuitive measure of comparing modelfit that is grounded in probability theory. Given the rapid increase in thenumber and complexity of phylogenetic models, methods for approximatingmarginal likelihoods are increasingly important. Here we try to provide anintuitive description of marginal likelihoods and why they are important inBayesian model testing. We also categorize and review methods for estimatingmarginal likelihoods of phylogenetic models, highlighting several recentmethods that provide well-behaved estimates. Furthermore, we review someempirical studies that demonstrate how marginal likelihoods can be used tolearn about models of evolution from biological data. We discuss promisingalternatives that can complement marginal likelihoods for Bayesian modelchoice, including posterior-predictive methods. Using simulations, we find onealternative method based on approximate-Bayesian computation (ABC) to bebiased. We conclude by discussing the challenges of Bayesian model choice andfuture directions that promise to improve the approximation of marginallikelihoods and Bayesian phylogenetics as a whole.

Marginal likelihoods in phylogenetics: a review of methods and applications