GSA power simulation with unstructured signal configurations over different sparsity settings. Ryan Sun Shirley Hui Gary D. Bader Xihong Lin Peter Kraft 10.1371/journal.pgen.1007530.g002 https://plos.figshare.com/articles/figure/GSA_power_simulation_with_unstructured_signal_configurations_over_different_sparsity_settings_/7853168 <p>Simulated power with random sets of ten genes selected from 10,000 total genes. Causal SNPs are chosen at random from all SNPs in the set. The subfigures correspond to (A) 2, (B) 5, (C) 8, (D) 9, (E) 12, and (F) 15 signals. We perform 100 simulations at each parameter setting and test at <i>α</i> = 0.01. GBJ offers robust performance through very sparse, moderately sparse, and dense settings, while other tests show decreased power in certain scenarios.</p> 2019-03-15 17:39:49 GSA Single Nucleotide Polymorphisms breast cancer pathway analysis SNP Generalized Berk-Jones statistic set-based testing settings Genome-Wide Association Studies GBJ step-down inference technique FGFR breast cancer GWAS gene summary statistics