Bayesian network analysis incorporating genetic anchors complements conventional Mendelian randomization approaches for exploratory analysis of causal relationships in complex data.

Abstract excerpt

Mendelian randomization (MR) implemented through instrumental variables analysis is an increasingly popular causal inference tool used in genetic epidemiology. But it can have limitations for evaluating simultaneous causal relationships in complex data sets that include, for example, multiple genetic predictors and multiple potential risk factors associated with the same genetic variant. Here we use real and...

Topics

• Bayes Theorem
• Genetic Pleiotropy
• Humans
• Mendelian Randomization Analysis
• Polymorphism, Single Nucleotide
• Risk Factors