Extended Data Fig. 7: minPIP-inf performance.
From: Improving fine-mapping by modeling infinitesimal effects
a. Replication failure rates of minPIP and minPIP-inf in real data and in ideal simulations. Numerical results available in Supplementary Table 4. Error bars represent one SD of the corresponding binomial distribution Binom(n, p), where n is the total number of high-PIP variants at sample size N = 100 K, and p is the RFR. Bar plot data is presented as RFR + /- SD. b. Functional enrichment of top N (N = 500, 1000, 1500, and 3000) highest PIP variants from SuSiE-inf, FINEMAP-inf and minPIP-inf. Error bars represent one SD of the corresponding binomial distribution Binom(n,p), where n is the total number of variants in each set and p is the corresponding proportion of annotated variants). Numerical results available in Supplementary Table 16. c-d. PRS accuracy, in terms of delta R2, when applying SuSiE-inf sparse component of the posterior effect sizes vs. minPIP-inf sparse component of the posterior effects sizes as weights; similarly, for FINEMAP-inf and minPIP-inf. PRS were computed for 2 out-of-sample cohorts and 7 traits. For descriptions of PRS weights, see Methods. Numerical results available in Supplementary Table 11-12.
