Application of the Mediator Design Pattern to Monte Carlo Simulation in Genetic Epidemiology

Genetic epidemiology relies on simulated data to support development of theory and methods. Simulated data are designed to reflect, as accurately as possible, the true phenotypic and genotypic distributions of individuals sampled from different types of relationship clusters. Common simulation methods can be classified into two groups: agent-based methods, in which individuals are simulated, one at a time, according to the rules of Mendelian inheritance and other assumptions, and structure-based methods, in which aggregates of individuals exhibiting properties of interest are simulated, with genotypic information inferred conditionally on both phenotype and structure. A previously untried software design is proposed to support both agent-based and structure-based simulation with equal facility. The mediator design pattern is applied to simulation design, and is shown to (1) reduce the complexities arising from the potentially huge number of communication channels required between autonomous agents and (2) to provide an efficient mechanism by which higher-level system objects may override default behaviors of lower-level objects.