wakefield_pp_quant computes posterior probabilities for a given SNP to be causal for a given SNP under the assumption of a single causal variant.
wakefield_pp_quant(beta, se.beta, sdY, sd.prior = 0.15, pi_i = 1e-04)a vector of effect sizes (\(\beta\)) from a quantitative trait GWAS
vector of standard errors of effect sizes (\(\beta\))
a scalar of the standard deviation given vectors of variance of coefficients, MAF and sample size. Can be calculated using sdY.est
a scalar representing our prior expectation of \(\beta\) (DEFAULT 0.15).
a scalar representing the prior probability (DEFAULT \(1 \times 10^{-4}\)) 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.
This function was adapted from wakefield_pp in cupcake package (github.com/ollyburren/cupcake/)