GoShifter is a recent method of Trynka et al. [6] (see also their previous published work [5]). Goshifter is conservative in its identification of enrichment, comparing to a null obtained by local shifting rather than a genome-wide null, and it only uses statistically significant SNPs. It had properly calibrated type 1 error in all four situations we simulated. Of these four situations, stratified LD score regression had higher power than GoShifter in the more polygenic scenarios, and the two methods performed comparably in the less polygenic scenarios, in which there were more significant SNPs.
