Functions to find the corrected coverage estimate of a credible set
corrcov()
Corrected coverage estimate using Z-scores and MAFs
corrcov_bhat()
Corrected coverage estimate using estimated effect sizes and their standard errors
Functions to find a corrected credible set
corrected_cs()
Corrected credible set using Z-scores and MAFs
corrected_cs_bhat()
Corrected credible set using estimated effect sizes and their standard errors
Functions to find a confidence interval for the corrected coverage estimate
corrcov_CI()
Confidence interval for corrected coverage estimate using Z-scores and MAFs
corrcov_CI_bhat()
Confidence interval for corrected coverage estimate using estimated effect sizes and their standard errors
Functions to find a corrected coverage estimate when fixing the number of variants in the credible set
corrcov_nvar()
Corrected coverage estimate using Z-scores and MAFs (fixing nvar)
corrcov_nvar_bhat()
Corrected coverage estimate using estimated effect sizes and their standard errors (fixing nvar)
Functions to estimate the joint Z score at the causal variant
est_mu()
Estimate the true effect at the causal variant using Z-scores and MAFs
est_mu_bhat()
Estimate the true effect at the causal variant using estimated effect sizes and their standard errors
Functions to convert between p-values, Z-scores, ABFs and PPs
approx.bf.p()
Find approx. Bayes factors (ABFs)
ppfunc()
Find PPs of SNPs from Z-scores
pvals_pp()
Find PPs for SNPs and null model from P-values and MAFs
z0_pp()
Find PPs for SNPs and null model from Z-scores and MAFs
z_sim()
Simulate marginal Z-scores from joint Z-score vector
zj_pp()
Simulate posterior probabilities of causality from joint Z-score vector
Var.data.cc()
Variance of the estimated effect size for case-control data
cor2()
Correlation matrix of SNPS
credset()
Credible set of genetic variants