Large samples of unrelated individuals have become the design of choice for genome-wide association scans, because earlier concerns about population stratification have been largely allayed by empirical methods [19]. Estimates of the total sample size are in the order of thousands [20]. Because the majority of genes are not associated with disease, it is uneconomical to genotype the whole sample for all genes. Sequential study designs, in particular a two-stage block design, have been proposed for reducing the total cost of a genome-wide experiment, which remains the main limiting factor preventing large-scale application. In a two-stage design, all of the genes are typed in a subset of the sample, with only the genes showing a trend of association being taken forward for genotyping in the remainder. This directs resources towards true associations at an earlier stage, so that the available sample size is larger for genes with true effects.
