We have focussed on the most common GWA design, namely of a single-stage study, and the simplest disease model. The flexibility of the simulation approach allows many other practical aspects of study design to be incorporated into power calculations. These include more complex disease models, two-stage strategies (the starting point for our work was a comparison of power for one- and two-stage designs in the context of the WTCCC study [5]), genotyping errors, QC filters, misidentification of cases as controls and simple types of population structure. The HAPGEN software also provides a useful tool for the development and comparison of more sophisticated multi-marker approaches to detecting disease association (e.g. imputation [14]). We therefore believe that simulations are an essential tool in the design of association studies by allowing a focus on study power and an assessment of the affect on power of following a given study design. We hope that this method will continue to find use and can be extended to new catalogs of genetic variation such as the 1000 Genomes Project http://www.1000genomes.org/.
