title: [Statistical methodologies used in genome-wide association studies].
abstract: In lieu of large samples of cases and/or controls with hundreds of markers spreading throughout the human genome, researchers started to notice the dramatic increase of genome-wide association study (GWAS) for complex disorders, in the last 5 years. This paper highlights the statistical challenges in such huge-scale genetic studies, and introduces the analytical strategies and steps for handling GWAS data. Such issues as quality control of data, population stratification, methods available to data analysis and results presentation, replication, as well as the limitations of GWAS studies and the challenges presenting for statistics, are addressed.
authors.affiliation: Department of Epidemiology and Health Statistics, School of Public Health, Nanjing Medical University, Nanjing 210029, China. fengchen@njmu.edu.cn
authors.forename: Feng
authors.initials: F
authors.lastname: Chen
authors.forename: Jian-Ling
authors.initials: JL
authors.lastname: Bai
authors.forename: Yang
authors.initials: Y
authors.lastname: Zhao
authors.forename: Peng-Cheng
authors.initials: PC
authors.lastname: Xun
mesh_terms: D001699:Biometry; D003627:Data Interpretation, Statistical; D055106:Genome-Wide Association Study; D006801:Humans