title: Selecting single-nucleotide polymorphisms for association studies with SNPbrowser software.
abstract: The design of genetic association studies using single-nucleotide polymorphisms (SNPs) requires the selection of subsets of the variants providing high statistical power at a reasonable cost. SNPs must be selected to maximize the probability that a causative mutation is in linkage disequilibrium (LD) with at least one marker genotyped in the study. The HapMap Project performed a genome-wide survey of genetic variation with over 3 million SNPs typed in four populations, providing a rich resource to inform the design of association studies. A number of strategies have been proposed for the selection of SNPs based on observed LD, including construction of metric LD maps and the selection of haplotype-tagging SNPs. Power calculations are important at the study design stage to ensure successful results. Integrating these methods and annotations can be challenging: the algorithms required to implement these methods are complex to deploy, and all the necessary data and annotations are deposited in disparate databases. Here, we review the typical workflows for the selection of markers for association studies utilizing the SNPbrowser software, a freely available, stand-alone application that incorporates the HapMap database together with gene and SNP annotations. Selected SNPs are screened for their conversion potential to genotyping platforms, expediting the set up of genetic studies with an increased probability of success.
authors.affiliation: Applied Biosystems, Foster City, CA, USA.
authors.forename: Francisco M
authors.initials: FM
authors.lastname: De La Vega
mesh_terms: D016022:Case-Control Studies; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D005838:Genotype; D006801:Humans; D015810:Linkage Disequilibrium / Q000235:genetics; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D012984:Software
chemical_list: D005819:Genetic Markers