Association rule mining is a knowledge discovery technique which informs researchers about relationships between variables in data. These relationships can be focused to a specific set of response variables. We propose an augmented version of this method to discover groups of genotypes which relate to specific outcomes. We derive the methodology to find these candidate groups of genotypes and illustrate how the method works on data regarding neuroinvasive complications of West Nile virus and through simulation.