models that can be interpreted in terms of interactions. However, these probabilities depend on both the risk of disease given G and E (and their interactions) and the correlations among these factors, so do not represent a pure interactome122 model. Alternatively, a known network can be used as either a prior covariance matrix for main effects or as prior covariates for interactions in a hierarchical model (Box 4). Although potentially exciting, such methods have yet to be applied on a GWA scale.
