wakefield_pp_quant {RapidoPGS}

Compute posterior probabilities using Wakefield's approximate Bayes Factors for quantitative traits

Description

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.

Usage

wakefield_pp_quant(beta, se, sdY, sd.prior = 0.15, pi_i = 1e-04)

Arguments

beta

a vector of effect sizes (\beta) from a quantitative trait GWAS

se

vector of standard errors of effect sizes (\beta)

sdY

a scalar of the standard deviation given vectors of variance of coefficients, MAF and sample size. Can be calculated using sdY.est

sd.prior

a scalar representing our prior expectation of \beta (DEFAULT 0.15).

pi_i

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.

Details

This function was adapted from wakefield_pp in cupcake package (github.com/ollyburren/cupcake/)

Value

a vector of posterior probabilities.

Author(s)

Guillermo Reales, Chris Wallace