Estimate trait standard deviation given vectors of variance of coefficients, MAF and sample size
sdY.est(vbeta, maf, n)vector of variance of coefficients
vector of MAF (same length as vbeta)
sample size
estimated standard deviation of Y
Estimate is based on var(beta-hat) = var(Y) / (n * var(X)) var(X) = 2* maf*(1-maf) so we can estimate var(Y) by regressing n*var(X) against 1/var(beta) This function is verbatim from its namesake in coloc package (github.com/chr1swallace/coloc/), by Chris Wallace