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