title: Optimal multistage designs--a general framework for efficient genome-wide association studies.
abstract: Genome-wide association studies (GWAS) have become increasingly affordable but they are still costly. Therefore, cost saving 2-stage designs were proposed in the literature. The restriction to 2 stages, however, seems artificial and does not exploit the full potential of the underlying methods. We extend the 2-stage approach to the general framework of any number of stages. Based on the theory of group sequential methods, we derive optimal multistage designs. With current genotyping cost structures, our results suggest that up to 4 stages are sufficient in order to get feasible and efficient designs. Furthermore, we consider the problem of choosing the optimal number of stages depending on the costs of the statistical interim analysis at each stage and provide guidelines for planning the number of stages in practice. In particular, we found that in the majority of cases both 3-stage designs and 4-stage designs are more efficient than 2-stage designs. Although prices for marker panels are showing a continuing downward trend, we still recommend implementing and using optimal multistage designs in practice. In addition to the immediate benefit, it will be necessary to acquire know-how regarding the application of multistage designs in order to be able to adapt the general framework of multistage designs to upcoming technologies in the area of GWAS.
authors.affiliation: Institute of Medical Biometry and Epidemiology, Philipps University, Marburg, Germany.
authors.forename: Roman
authors.initials: R
authors.lastname: Pahl
authors.forename: Helmut
authors.initials: H
authors.lastname: Schäfer
authors.forename: Hans-Helge
authors.initials: HH
authors.lastname: Müller
mesh_terms: D015415:Biomarkers; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study / Q000191:economics / Q000379:methods*; D005838:Genotype; D006801:Humans; D015233:Models, Statistical; D020641:Polymorphism, Single Nucleotide; D012107:Research Design
chemical_list: D015415:Biomarkers