We simulated summary statistics for 18,212,157 genotyped and imputed MAF≥0.001 autosomal SNPs with INFO score≥0.6 (including short indels, excluding three long-range LD regions; see below), using N=337,491 unrelated British-ancestry individuals from UK Biobank release 3. In most simulations we computed an effect variance βi for every SNP i with annotations ai using the baseline-LF (version 2.2.UKB) model, var[βi|ai]=∑cτcaic, where c are annotations and τc estimates are taken from a fixed-effects meta-analysis of 16 well-powered genetically uncorrelated (|rg|<0.2) UK Biobank traits, scaled such that ∑ivar[βi|ai] is the same across all traits (Supplementary Table 3). In some simulations we generated values of var[βi|ai] under alternative functional architectures to evaluate the robustness of PolyFun to modeling misspecification (Supplementary Note). Each SNP was set to be causal with probability proportional to var[βi|ai], such that the average causal probability was equal to the desired proportion of causal SNPs. We provide technical details about the simulations in the Supplementary Note.
