Reciprocal causation mixture model for robust Mendelian randomization analysis using genome-scale summary data

Abstract

Mendelian randomization methods are prone to produce false positive results when assumptions are violated. Here, the authors propose a statistical model that offers good power to detect causation between traits while controlling the false positive rate.