Set-based association tests, combining a set of single-nucleotide polymorphisms into a unified test, have become important approaches to identify weak-effect or low-frequency risk loci of complex diseases. However, there is no comprehensive and user-friendly tool to estimate power of set-based tests for study design. We developed a simulation tool to estimate statistical power of multiple representative set-based tests (SPS). SPS has a graphic interface to facilitate parameter settings and result visualization. Advanced functions include loading real genotypes to define genetic architecture, set-based meta-analysis for risk loci with or without heterogeneity, and parallel simulations. In proof-of-principle examples, SPS took no more than 3 sec on average to estimate the power in a conventional setting. The SPS has been integrated into a user-friendly software tool (KGG) as an independent functional module and it is freely available at http://statgenpro.psychiatry.hku.hk/limx/kgg/.
Keywords: complex disease; meta-analysis; power; set-based association test; simulation.
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