est_mu_bhat: Estimate the true effect at the causal variant using...

In corrcoverage: Correcting the Coverage of Credible Sets from Bayesian Genetic Fine Mapping

Description

Estimate the true effect at the causal variant using estimated effect sizes and their standard errors

Usage

est_mu_bhat(bhat, V, N0, N1, p1 = 1e-04, W = 0.2)

Arguments

bhat	Vector of estimated effect sizes
V	Prior variance for estimated effect sizes
N0	Number of controls
N1	Number of cases
p1	Prior probability a SNP is associated with the trait, default 1e-4
W	Prior for the standard deviation of the effect size parameter, beta

Value

Estimate of the true effect at the causal variant

Author(s)

Anna Hutchinson

Examples

nsnps <- 100
N0 <- 5000 # number of controls
N1 <- 5000 # number of cases

maf <- runif(nsnps, 0.05, 0.3)

varbeta <- Var.data.cc(f = maf, N = N0 + N1, s = N1/(N0+N1))

bhats = rnorm(nsnps,0,0.2) # log(OR)

est_mu_bhat(bhat = bhats, V = varbeta, N0 = N0, N1 = N1)

corrcoverage documentation built on Dec. 7, 2019, 1:07 a.m.