compute posterior probabilities using Wakefield's approximate Bayes Factors wakefield_pp computes posterior probabilities for a given SNP to be causal for a given SNP under the assumption of a single causal variant.

This function was adapted from its namesake in cupcake package (github.com/ollyburren/cupcake/) to no longer require allele frequencies.

wakefield_pp(beta, se, pi_i = 1e-04, sd.prior = 0.2)

Arguments

beta: a vector of effect sizes (\(\beta\)) from a quantitative trait GWAS
se: vector of standard errors of effect sizes (\(\beta\))
pi_i: a scalar representing the prior probability (DEFAULT \(1 \times 10^{-4}\))
sd.prior: a scalar representing our prior expectation of \(\beta\) (DEFAULT 0.2). The method assumes a normal prior on the population log relative risk centred at 0 and the DEFAULT value sets the variance of this distribution to 0.04, equivalent to a 95\ is in the range of 0.66-1.5 at any causal variant.

a vector of posterior probabilities.

Olly Burren, Chris Wallace, Guillermo Reales