Finally, we have performed power calculations assuming fixed sample sizes rather than fixed costs. As we have shown (Table 6), the inclusion of public control genotype data can dramatically decrease the cost of genotyping in addition to increasing statistical power. With this in mind, the increase in power between approaches that include public control data compared to those that do not is even greater than what we have presented in situations where the sample size of study subjects is limited by costs and not sample availability. Optimizing power with respect to cost for each study design would require an iterative application of the methods we have described. We have R software code that is available for investigators who would like to calculate power and make the comparisons for their own studies.
