RESAT: Robust heterogeneous-effects meta-analysis of variant-set...

In baolinwu/MetaSAT: Meta-analysis of variant-set association tests

Description

Conduct meta-analysis of variant-set association test of m variants assuming heterogeous effects across K studies. HE VT: ∑_k U_k^TU_k; RHE BT: ∑_k(η_k^TU_k)^2; RAT: adaptively combine HE VT and RHE BT.

Usage

RESAT(Us, Vs, eta = NULL, rho = (0:10/10)^2)

Arguments

Us	matrix of variant test statistics (m by K)
Vs	array of covariance matrix for test statistics (m,m by K)
eta	coefficient matrix for variants (m by K). Default to equal weights.
rho	weights assigned to the RHE BT

Value

p.value

p-values for RAT, HE VT, RHE BT

pval

vector of p-values for each rho

rho.est

optimal rho value leading to the minimum p-value

References

Wu,B. and Zhao,H. (2018) Efficient and powerful meta-analysis of variant-set association tests using MetaSAT.

Examples

K = 3; m=10
Vs = array(0, dim=c(m,m,K)); Us = matrix(0, m,K)
for(k in 1:K){
  ak = matrix(rnorm(100*m),100,m)*sqrt(0.8)+rnorm(100)*sqrt(0.2)
  Vs[,,k] = cor(ak)
  Rh = chol(Vs[,,k])
  Us[,k] = colSums(Rh*rnorm(m))
}
RESAT(Us,Vs)
U1 = Us + rnorm(m*K,1,1.25)
RESAT(U1,R=Vs)

baolinwu/MetaSAT documentation built on May 13, 2019, 5:22 p.m.