PolyFun uses version 2.2.UKB of the baseline-LF model, which differs from the original baseline-LF model25 by including MAF≥0.001 SNPs and several new annotations, and omitting annotations that could not be easily extended to account for MAF<0.005 SNPs (Supplementary Table 1). Briefly, we use 187 overlapping functional annotations, including 10 common MAF bins (MAF≥0.05); 10 low-frequency MAF bins (0.05>MAF≥0.001); 6 LD-related annotations for common SNPs (levels of LD, predicted allele age, recombination rate, nucleotide diversity, background selection statistic, CpG content); 5 LD-related annotations for low-frequency SNPs; 40 binary functional annotations for common SNPs; 7 continuous functional annotations for common SNPs; 40 binary functional annotations for low-frequency SNPs; 3 continuous functional annotations for low-frequency SNPs; and 66 annotations constructed via windows around other annotations17. We did not include a base annotation that includes all SNPs, because such an annotation is linearly dependent on all the MAF bins when S-LDSC uses the same set of SNPs to compute LD-scores and to estimate annotation coefficients.
