PT  - JOURNAL ARTICLE
AU  - Wesley L Crouse
AU  - Gregory R Keele
AU  - Madeleine S Gastonguay
AU  - Gary A Churchill
AU  - William Valdar
TI  - A Bayesian model selection approach for mediation analysis
AID  - 10.1101/2021.07.19.452969
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.07.19.452969
4099  - http://biorxiv.org/content/early/2021/07/20/2021.07.19.452969.short
4100  - http://biorxiv.org/content/early/2021/07/20/2021.07.19.452969.full
AB  - 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.