Similarly, to compare the power of different methods, one can randomly sample disease associated genes (with different strengths of associations) from a GWAS dataset or generate disease outcome based on genetic models with various parameters indicating strengths of associations [12,55]. Benchmark GWAS datasets for diseases with well known biological basis, such as Crohn’s Disease (CD), would also be useful for evaluating and comparing gene set analysis methods. As an example, Ballard et al. [69] compared two gene set analysis methods based on their applications to three CD datasets.
