title: Utilizing HapMap and tagging SNPs.
abstract: Advancements in our understanding of variation in the human genome and rapid improvements in high-throughput genotyping technology have made it feasible to study most of the human genetic diversity that is due to common variations in relation to observable phenotypes. Over the past few years, public SNP databases have matured and empirical genome-wide SNP data, such as that generated by the International HapMap Project, have shown the utility and efficiency of selecting and testing informative markers ("tag SNPs") that exploit redundancies among nearby polymorphisms due to linkage disequilibrium (LD). In this chapter, we will demonstrate how to use the HapMap resource and the Haploview program to process and analyze genetic data from HapMap, to evaluate LD relations between SNPs, and to select tagging SNPs to be examined in disease association studies.
authors.affiliation: Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
authors.forename: Christopher A
authors.initials: CA
authors.lastname: Haiman
authors.forename: Daniel O
authors.initials: DO
authors.lastname: Stram
mesh_terms: D000465:Algorithms; D002898:Chromosomes, Human, Pair 8; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D015894:Genome, Human; D006239:Haplotypes; D006801:Humans; D015810:Linkage Disequilibrium; D020641:Polymorphism, Single Nucleotide; D016324:Sequence Tagged Sites