LiMA: Robust inference of molecular mediation from summary statistics

LiMA and its random-effect variant I-LiMA infer molecular mediation in a Mendelian randomization framework using summary statistics. Jointly modeling direct and mediated effects while accounting for measurement error, they reduce weak-instrument bias and false positives in simulations. Applications to real data reveal metabolites and proteins mediating obesity-related cardiometabolic risk.