JointMR: A joint likelihood-based approach for causal effect estimation in overlapping Mendelian Randomization studies
Sijia Wu, Lei Hou, Zhongshang Yuan…·Hongkai Li
JointMR integrates GWAS summary databases to estimate causal effects, providing unbiased and reliable results with higher power and better Type I error control than traditional methods.