Mendelian randomization analysis using mixture models for robust and efficient estimation of causal effects

Abstract

Mendelian randomization (MR) is a powerful and widely used method for causal inference leveraging genetic information. Here, the authors develop MRMix, an MR method using mixture models for more robust and efficient estimation of causal effects.