Figure 1
From: Causal graph-based analysis of genome-wide association data in rheumatoid arthritis
Graphical representation of the local pathway concept. The local pathway of the phenotype (shown with the ash blue colour) contains all its direct causes (C1, C2, C3), direct effects (E1, E2, E3), and direct causes of the direct effects (CE1). This is exactly the Markov boundary of the phenotype. Other variables (X1, X2, X3, X4, X5) do not belong to the local pathway. This definition of a local pathway ties in a theoretically rigorous manner causality with predictivity, since the Markov boundary is the smallest set of variables that contains the maximum predictive information about the phenotype that is contained in the data. Alternative definitions of the local causal pathway that exclude direct causes of the direct effects (the so-called "spouse variables", such as CE1) are also useful and specialized algorithms exist to infer them from data. In GWAS data, the two definitions coincide because of lack of spouse variables in GWAS designs.