The LDPred computational algorithm was used to generate seven candidate GPSs for each disease.13 This Bayesian approach calculates a posterior mean effect size for each variant based on a prior and subsequent shrinkage based on the extent to which this variant is correlated with similarly associated variants in the reference population. The underlying Gaussian distribution additionally considers the fraction of causal (e.g. non-zero effect sizes) markers via a tuning parameter, ρ. Because ρ is unknown for any given disease, a range of ρ, the fraction of causal variants, was used – 1, 0.3, 0.1, 0.03, 0.01, 0.003, 0.001.
