title: Analysis of Genome-Wide Association Data.
abstract: The last decade has seen substantial advances in the understanding of the genetics of complex traits and disease. This has been largely driven by genome-wide association studies (GWAS), which have identified thousands of genetic loci associated with these traits and disease. This chapter provides a guide on how to perform GWAS on both binary (case-control) and quantitative traits. As poor data quality, through both genotyping failures and unobserved population structure, is a major cause of false-positive genetic associations, there is a particular focus on the crucial steps required to prepare the SNP data prior to analysis. This is followed by the methods used to perform the actual GWAS and visualization of the results.
authors.affiliation: Centre for Neurogenetics and Statistical Genomics, Queensland Brain Institute, The University of Queensland, St Lucia, QLD, 4072, Australia. a.mcrae@uq.edu.au.
authors.forename: Allan F
authors.initials: AF
authors.lastname: McRae
mesh_terms: D000818:Animals; D055106:Genome-Wide Association Study / Q000379:methods*; D005838:Genotype; D006801:Humans; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D040641:Quantitative Trait Loci / Q000235:genetics; D012984:Software
keywords: Case–control; Genome-wide association; Imputation; Population stratification; Quantitative trait; SNP cleaning