title: Robust joint analysis allowing for model uncertainty in two-stage genetic association studies.
abstract: BACKGROUND
  The cost efficient two-stage design is often used in genome-wide association studies (GWASs) in searching for genetic loci underlying the susceptibility for complex diseases. Replication-based analysis, which considers data from each stage separately, often suffers from loss of efficiency. Joint test that combines data from both stages has been proposed and widely used to improve efficiency. However, existing joint analyses are based on test statistics derived under an assumed genetic model, and thus might not have robust performance when the assumed genetic model is not appropriate.
  
  
  RESULTS
  In this paper, we propose joint analyses based on two robust tests, MERT and MAX3, for GWASs under a two-stage design. We developed computationally efficient procedures and formulas for significant level evaluation and power calculation. The performances of the proposed approaches are investigated through the extensive simulation studies and a real example. Numerical results show that the joint analysis based on the MAX3 test statistic has the best overall performance.
  
  
  CONCLUSIONS
  MAX3 joint analysis is the most robust procedure among the considered joint analyses, and we recommend using it in a two-stage genome-wide association study.
authors.affiliation: Department of Statistics, Yunnan University, Kunming 650091, PR China.
authors.forename: Dongdong
authors.initials: D
authors.lastname: Pan
authors.forename: Qizhai
authors.initials: Q
authors.lastname: Li
authors.forename: Ningning
authors.initials: N
authors.lastname: Jiang
authors.forename: Aiyi
authors.initials: A
authors.lastname: Liu
authors.forename: Kai
authors.initials: K
authors.lastname: Yu
mesh_terms: D019295:Computational Biology / Q000379:methods*; D005787:Gene Frequency; D055106:Genome-Wide Association Study / Q000379:methods*; D006801:Humans; D008957:Models, Genetic; D015233:Models, Statistical; D009010:Monte Carlo Method; D020641:Polymorphism, Single Nucleotide; D035501:Uncertainty