Drug developers' principal interest in pharmacogenetics is to learn which genes are relevant to variation in response to their drugs. Pharmacogeneticists must overcome several inferential challenges to meet this need. False positive results can be avoided through experiment replication. Using the human genome as the ultimate measure of intrinsic differences between individuals, it can be demonstrated that results are not artifacts of population structure. Association analysis based upon estimated haplotypes is more powerful than single-marker methods to minimize the hazard of false negative results. This article summarizes the current state-of-the-art in pharmacogenetic inference and identifies areas for further method development work to enable identification of the genes underlying the efficacy or safety of a particular drug.
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