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Pattern-recognition techniques with haplotype analysis in pharmacogenomics.

Eugene Lin·Yuchi Hwang·Kung-Hao Liang·Ellson Y Chen
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Abstract

Single nucleotide polymorphisms (SNPs) can be used in clinical association studies to determine the contribution of genes to drug efficacy. However, it would be extremely inefficient to test all the 10 million common SNPs for an association study. Here we review haplotype analysis and pattern-recognition techniques to systematically select candidate SNPs for candidate-gene association studies in pharmacogenomics. First, we survey linkage disequilibrium methods to identify tag SNPs and explore the use of haplotypes as genetic markers that are correlated and associated with drug efficacy. Secondly, we investigate pattern-recognition algorithms and statistical analyses to assess drug efficacy based on SNPs and other factors. Finally, we study pattern-recognition approaches to evaluate the epistasis among genes and SNPs. These techniques may provide tools for clinical association studies and help find genes/SNPs involved in responses to therapeutic drugs or adverse drug reactions.

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AnimalsGenetic MarkersHaplotypesHumansLinkage DisequilibriumPattern Recognition, AutomatedPharmacogeneticsPolymorphism, Single NucleotideJournal ArticleResearch Support, Non-U.S. Gov'tReview

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Eugene Lin, Yuchi Hwang, Kung-Hao Liang, Ellson Y Chen. 2007. Pattern-recognition techniques with haplotype analysis in pharmacogenomics.. https://doi.org/10.2217/14622416.8.1.75

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