PolyFun + SuSiE identified 3,025 PIP>0.95 fine-mapped SNP-trait pairs, a >32% improvement vs. SuSiE; 9,684 PIP>0.5 SNP-trait pairs, a >59% improvement vs. SuSiE; and 225,153 PIP>0.05 SNP-trait pairs, a >84% improvement vs. SuSiE (Supplementary Table 9). The number of PIP>0.95 SNPs per trait ranged from 0 (number of children) to 407 (height) (Figure 2a, Supplementary Table 9). The 3,025 PIP>0.95 SNP-trait pairs spanned 2,225 unique SNPs, including 532 low-frequency SNPs (0.005<MAF<0.05) and 185 rare SNPs (0.001<MAF<0.005) (Supplementary Table 10). Only 39% of the 2,225 PIP>0.95 SNPs were also lead GWAS SNPs (defined as MAF>0.001 SNPs with P<5×10−8 and no MAF>0.001 SNP with a smaller p-value within 1Mb) (Supplementary Table 10), demonstrating the importance of using fine-mapped SNPs rather than lead GWAS SNPs for downstream analysis. 31% of the PIP>0.95 SNPs resided in coding regions and 22% were non-synonymous (broadly consistent with previous fine-mapping studies8,12) (Supplementary Table 10). When restricting the analysis to 16 genetically uncorrelated traits (|rg|<0.2; Methods and Supplementary Tables 11–12) we identified 1,626 PIP>0.95 SNP-trait pairs spanning 1,496 unique SNPs, with a median distance of 9kb between a
