We applied SuSiE and PolyFun + SuSiE to fine-map 49 traits in the UK Biobank, using the same data and the same parameter settings described in the Fine-mapping simulations section. We performed basic QC on each trait as described in our previous publications30,31. Specifically, we removed outliers outside the reasonable range for each quantitative trait, and applied quantile normalizing within sex strata after correcting for covariates for non-binary traits with non-normal distributions. We computed summary statistics with BOLT-LMM v2.3.331 adjusting for sex, age and age squared, assessment center, genotyping platform, and the top 20 principal components (computed as described in ref. 31), and dilution factor for biochemical traits. As the non-infinitesimal version of BOLT-LMM does not estimate effect sizes, we computed z-scores for fine-mapping by taking the square root of the BOLT-LMM χ2 statistics and multiplying them by the sign of the effect estimate from the infinitesimal version of BOLT-LMM.
