refer to this method as PolyLoc. The analysis of new samples in step 2 of PolyLoc prevents winner’s curse; although PolyFun + SuSiE is robust to winner’s curse, PolyLoc would be susceptible to winner’s curse if it reused the data analyzed by PolyFun + SuSiE. We note that M50% relies on an empirical ranking and is thus larger than the size of the smallest set of SNPs causally explaining 50% of common SNP heritability, denoted as M50%*(M50%≥M50%*). We performed extensive simulations to confirm that PolyLoc produced robust upper bounds of M50%* (Supplementary Note, Supplementary Tables 29–30). Further details of PolyLoc are provided in the Methods section; we have released open source software implementing PolyLoc.
