TY - JOUR T1 - A Bayesian model selection approach to mediation analysis JF - bioRxiv DO - 10.1101/2021.07.19.452969 SP - 2021.07.19.452969 AU - Wesley L Crouse AU - Gregory R Keele AU - Madeleine S Gastonguay AU - Gary A Churchill AU - William Valdar Y1 - 2021/01/01 UR - http://biorxiv.org/content/early/2021/07/20/2021.07.19.452969.1.abstract N2 - Mediation analysis is a powerful tool for discovery of causal relationships. We describe a Bayesian model selection approach to mediation analysis that is implemented in our bmediatR software. Using simulations, we show that bmediatR performs as well or better than established methods including the Sobel test, while allowing greater flexibility in both model specification and in the types of inference that are possible. We applied bmediatR to genetic data from mice and human cell lines to demonstrate its ability to derive biologically meaningful findings. The Bayesian model selection framework is extensible to support a wide variety of mediation models.Competing Interest StatementThe authors have declared no competing interest. ER -