Learning association rules for pharmacogenomic studies

Abstract

The better understanding of variants of the genomes may improve the knowledge on the causes of the individuals’ different responses to drugs. The Affymetrix DMET (Drug Metabolizing Enzymes and Transporters) microarray platform offers the possibility to determine the gene variants of a patient and correlate them with drug-dependent adverse events. The analysis of DMET data is a growing research area. Existing approaches span from the use of simple statistical tests to more complex strategies based, for instance, on learning association rules. To support the analysis, we developed GenotypeAnalytics, a RESTFul-based software service able to automatically extract association rules from DMET datasets. GenotypeAnalytics is based on an optimised algorithm for learning rules that can outperform general purpose platforms.