Confidence interval for corrected coverage estimate using Z-scores and MAFs

Obtain confidence interval for corrected coverage estimate using Z-scores and mafs

corrcov_CI(z, f, N0, N1, Sigma, thr, W = 0.2, nrep = 1000, CI = 0.95,
  pp0min = 0.001)

Arguments

z	Marginal Z-scores
f	Minor allele frequencies
N0	Number of controls
N1	Number of cases
Sigma	SNP correlation matrix
thr	Minimum threshold for fine-mapping experiment
W	Prior for the standard deviation of the effect size parameter, beta (default 0.2)
nrep	The number of simulated posterior probability systems to consider for the corrected coverage estimate (nrep = 1000 default)
CI	The size of the confidence interval (as a decimal)
pp0min	Only average over SNPs with pp0 > pp0min

Value

CI for corrected coverage estimate

Examples

# \donttest{

 # this is a long running example
set.seed(1)
nsnps = 100
N0 = 5000
N1 = 5000
z_scores <- rnorm(nsnps, 0, 3) # simulate a vector of Z-scores

## generate example LD matrix
library(mvtnorm)
nsamples = 1000

simx <- function(nsnps, nsamples, S, maf=0.1) {
    mu <- rep(0,nsnps)
    rawvars <- rmvnorm(n=nsamples, mean=mu, sigma=S)
    pvars <- pnorm(rawvars)
    x <- qbinom(1-pvars, 1, maf)
}

S <- (1 - (abs(outer(1:nsnps,1:nsnps,`-`))/nsnps))^4
X <- simx(nsnps,nsamples,S)
LD <- cor2(X)
maf <- colMeans(X)

corrcov_CI(z = z_scores, f = maf, N0, N1, Sigma = LD, thr = 0.95)
#>      2.5%     97.5% 
#> 0.9945937 0.9999510 
# }