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