NEWS1.md

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

MSKAT

• An R package implementing various statistical methods for testing multi-trait variant-set association

SNP-set association tests across multiple phenotypes using GWAS summary data

• Multi-trait SNP-set Association Tests using GWAS Summary data (MSATS)
• Efficient and powerful MSATS tests: variance components test (MQT), burden type test (MBT), adaptive test (MAT)
  • All test p-values are efficiently and analytically computed: extremely scalable without the need of Monte Carlo sampling.
  • The MAT has robust performance and can truly combine the strength of both MQT and MBT.
• Reference
  • Guo,B. and Wu,B. (2018) Powerful and efficient SNP-set association tests across multiple phenotypes using GWAS summary data. tech rep.
• Sample R codes

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.