gtx (version 0.0.8)

abf.Wakefield: Calculate approximate Bayes factor (ABF) using method of Wakefield (2009).

Description

Calculates an approximation to the Bayes Factor for an alternative model where the parameter beta is a priori normal, by approximating the likelihood function with a normal distribution.

Usage

abf.Wakefield(beta, se, priorsd)

Arguments

beta

Vector of effect size estimates.

se

Vector of associated standard errors.

priorsd

Scalar specifying the standard deviation of the prior on true effect sizes.

Value

A vector of approximate Bayes factors.

Details

See “Bayes factors for genome-wide association studies: comparison with P-values” by John Wakefield, 2009, Genetic Epidemiology 33(1):79-86 at http://dx.doi.org/10.1002/gepi.20359.

Examples

data(agtstats)
agtstats$pval <- with(agtstats, pchisq((beta/se.GC)^2, df = 1, lower.tail = FALSE))
max1 <- function(bf) return(bf/max(bf, na.rm = TRUE))
agtstats$BF.normal <- with(agtstats, max1(abf.Wakefield(beta, se.GC, 0.05)))
agtstats$BF.t <- with(agtstats, max1(abf.t(beta, se.GC, 0.0208)))
with(agtstats, plot(-log10(pval), log(BF.normal)))
with(agtstats, plot(-log10(pval), log(BF.t)))