2) Develop strategies for the assessment and comparison of gene set analysis methods. When assessing the performance of a method, it is important to ensure the proportion of false positive findings from the test is as expected. Null gene sets can be generated by randomly simulating disease outcomes without using any genotype data [55], or by randomly sampling genes from a GWAS dataset [3,4]. Next, one can plot a histogram of the estimated P-values for these “null” gene sets. These P-values are expected to roughly follow a uniform distribution. It is desirable to have a method whose type I error is equal to or less than the significance cutoff (e.g., 0.05).
