powered by
Estimate trait standard deviation given vectors of variance of coefficients, MAF and sample size
sdY.est(vbeta, maf, n)
estimated standard deviation of Y
vector of variance of coefficients
vector of MAF (same length as vbeta)
sample size
Chris Wallace
Estimate is based on var(beta-hat) = var(Y) / (n * var(X)) var(X) = 2maf(1-maf) so we can estimate var(Y) by regressing n*var(X) against 1/var(beta)