title: Optimum two-stage designs in case-control association studies using false discovery rate.
abstract: Genetic association studies using case-control designs are often done to identify loci associated with disease susceptibility. These studies are often expensive to perform, due to a large number of genetic markers. Several types of two-stage designs are proposed and used from the point of cost effectiveness. We proposed to control the false discovery rate for multiple-testing correction in two-stage designs, using optimal sample sizes and criteria for selecting markers associated with a disease in each stage to minimize the cost of genotyping. The expected power and cost of two-stage designs were compared with those of one-stage designs, under the assumptions that the genetic markers are independent and total sample size is fixed. The results showed that the proposed two-stage procedure usually reduced the cost of genotyping by 40-60%, with a power similar to that of the one-stage designs. In addition, the sample size and selection criteria, which are optimized parameters, are defined as a function of a prior probability that marker-disease association is true. So, the effects of mis-specification of a prior probability on efficiency were also considered.
authors.affiliation: Department of Biostatistics/Epidemiology and Preventive Health Sciences, Graduate School of Medicine, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan. kuchiba@epistat.m.u-tokyo.ac.jp.
authors.forename: Aya
authors.initials: A
authors.lastname: Kuchiba
authors.affiliation: Department of Clinical Bioinformatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.
authors.forename: Noriko Y
authors.initials: NY
authors.lastname: Tanaka
authors.affiliation: Department of Biostatistics/Epidemiology and Preventive Health Sciences, Graduate School of Medicine, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.
authors.forename: Yasuo
authors.initials: Y
authors.lastname: Ohashi
mesh_terms: D016022:Case-Control Studies; D003627:Data Interpretation, Statistical; D005189:False Positive Reactions; D005819:Genetic Markers; D020022:Genetic Predisposition to Disease; D005828:Genetics, Population / Q000379:methods*; D005838:Genotype; D006801:Humans; D011336:Probability; D012107:Research Design; D018401:Sample Size
chemical_list: D005819:Genetic Markers