title: Overview of Statistical Methods for Genome-Wide Association Studies (GWAS).
abstract: This chapter provides an overview of statistical methods for genome-wide association studies (GWAS) in animals, plants, and humans. The simplest form of GWAS, a marker-by-marker analysis, is illustrated with a simple example. The problem of selecting a significance threshold that accounts for the large amount of multiple testing that occurs in GWAS is discussed. Population structure causes false positive associations in GWAS if not accounted for, and methods to deal with this are presented. Methodology for more complex models for GWAS, including haplotype-based approaches, accounting for identical by descent versus identical by state, and fitting all markers simultaneously are described and illustrated with examples.
authors.affiliation: Biosciences Research Division, Department of Primary Industries, Bundoora, VIC, Australia.
authors.forename: Ben
authors.initials: B
authors.lastname: Hayes
mesh_terms: D000465:Algorithms; D000818:Animals; D005819:Genetic Markers; D055106:Genome-Wide Association Study / Q000706:statistics & numerical data*; D006239:Haplotypes; D006801:Humans; D015810:Linkage Disequilibrium; D056186:Metagenomics; D015233:Models, Statistical; D010944:Plants / Q000235:genetics; D020641:Polymorphism, Single Nucleotide; D012107:Research Design
chemical_list: D005819:Genetic Markers