BackgroundA goal of human genetics is to discover genetic factors that influence individuals' susceptibility to common diseases. Most common diseases are thought to result from the joint failure of two or more interacting components instead of single component failures. This greatly complicates both the task of selecting informative genetic variants and the task of modeling interactions between them. We and others have previously developed algorithms to detect and model the relationships between these genetic factors and disease. Previously these methods have been evaluated with datasets simulated according to pre-defined genetic models.
Himmelstein, Daniel S; Greene, Casey S; and Moore, Jason H, "Evolving Hard Problems: Generating Human Genetics Datasets with a Complex Etiology" (2011). Open Dartmouth: Peer-reviewed articles by Dartmouth faculty. 550.