Statistical methods for genome-wide association studies

Genome-wide association studies (GWAS) detect common genetic variants associated with complex disorders. With their comprehensive coverage of common single nucleotide polymorphisms and comparatively low cost, GWAS are an attractive tool in the clinical and commercial genetic testing. This review introduces the pipeline of statistical methods used in GWAS analysis, from data quality control, association tests, population structure control, interaction effects and results visualization, through to post-GWAS validation methods and related issues.