CaPri: Bayesian Mendelian randomization for joint estimation of causal and pleiotropic effects
Ou Ren, Wenmin Zhang, Tianyuan Lu
CaPri is a Bayesian Mendelian randomization framework that jointly estimates causal and pleiotropic effects, showing robust performance across varying pleiotropy proportions and real data applications.
medRxiv · Oct 14, 2026 · PreprintGenetic & Genomic Medicine