MSATS: Multi-trait SNP-set association test using GWAS summary data

In baolinwu/MSKAT: Various multi-trait variant-set association test methods

Description

Efficient multi-trait SNP-set association tests: variance components test (MQT), burden type test (MBT), adaptive test (MAT)

Usage

MSATS(Z, Sig, R, rho = c((0:5/10)^2, 0.5, 1))

Arguments

Z	M by K matrix of summary Z-statistics for M variants across K traits
Sig	estimated trait correlation matrix (K by K)
R	variant LD correlation matrix (M by M)
rho	weight assigned to the MBT

Value

p.value

test p-values for MAT, MQT, MBT

pval

vector of all p-values

rho.est

the optimal rho weight

References

Guo,B. and Wu,B. (2018) Powerful and efficient SNP-set association tests across multiple phenotypes using GWAS summary data. Bioinformatics, bty811.

Examples

K = 4; M = 20
R = cor(matrix(rnorm(500*M),500,M)*sqrt(0.8)+rnorm(500)*sqrt(0.2))
Y = matrix(rnorm(100*K), 100,K)*sqrt(0.8)+rnorm(100)*sqrt(0.2)
Y[,1] = -Y[,1]; Sig = cor(Y)
Z = matrix(rnorm(K*M),M,K)
js = sample(1:M, size=round(M*0.4))
Z[js,] = Z[js,] + 1.5
MSATS(Z,Sig,R)
Z = matrix(rnorm(K*M),M,K)
ij = cbind(sample(1:M, size=20, rep=TRUE), sample(1:K, size=20, rep=TRUE))
Z[ij] = Z[ij] + rnorm(20)*1.5
MSATS(Z,Sig,R)

baolinwu/MSKAT documentation built on May 28, 2019, 6:37 p.m.