SBayesS-strat

SBayesS-strat is a two-component SBayesS model that allows the distributions of SNP effects in the focal annotation category, e.g., coding, regulatory and conserved regions, to be different from that in the rest of the genome. Compared to other methods utilising functional annotations, such as S-LDSC⁵², BayesRC⁵³ and RSS-E⁵⁴, a unique feature of the annotation-stratified SBayesS (referred to as SBayesS-strat) is that it allows the estimation of S in a specific functional annotation category. Compared to a recently published method, BLD-LDAK-Alpha⁹, that estimates the S parameter (denoted by α in their model) based on an infinitesimal model, our method accounts for a sparse genetic architecture. In addition to the estimation of per-SNP heritability, polygenicity and S for each category, we also defined per-nonzero-effect (per-NZE) heritability (hNZE2) as the total heritability explained in a category divided by the number of nonzero effects in the category, which is helpful to understand whether the heritability enrichment is due to the larger number of associated variants or the larger magnitude of effect size compared to genome average. In addition to the category-specific parameters, we estimated the global parameters S, π, hSNP2 and hNZE2 empirically conditional on the sampled value of β in each iteration of MCMC. The fold of enrichment of each parameter for each trait was then computed as Etθγt/θt over T MCMC iterations. The estimation variation of the enrichment fold was quantified by the posterior variance as described above.