Estimate trait standard deviation given vectors of variance of coefficients, MAF and sample size

sdY.est(vbeta, maf, n)

Arguments

vbeta

vector of variance of coefficients

maf

vector of MAF (same length as vbeta)

n

sample size

Value

estimated standard deviation of Y

Details

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)

Author

Chris Wallace