aSPU (version 1.50)

GEEaSPU: The SPU and aSPU tests for multiple traits - single SNP association in generalized estimating equations.

Description

It gives p-values of the GEESPU tests and GEEaSPU test.

Usage

GEEaSPU(
  traits,
  geno,
  Z = NULL,
  model = c("binomial", "gaussian"),
  gamma = c(1:8, Inf),
  n.sim = 1000,
  corstr = "independence"
)

Arguments

traits

trait matrix. The row for individuals and the column for traits.

geno

A matrix of genetic information.

Z

covariates.

model

Use "gaussian" for a quantitative trait, and use "binomial" for a binary trait.

gamma

power used in GEEaSPU test. A vector of the powers.

n.sim

number of simulations.

corstr

a character string specifying the correlation structure. The following are permitted: "independence", "fixed", "stat_M_dep", "non_stat_M_dep", "exchangeable", "AR-M" and "unstructured"

Value

p-values for the GEE-SPU and GEE-aSPU test.

References

Yiwei Zhang, Zhiyuan Xu, Xiaotong Shen, Wei Pan (2014) Testing for association with multiple traits in generalized estimation equations, with application to neuroimaging data. Neuroimage. 96:309-25

Examples

# NOT RUN {
traits <- matrix(rnorm(100*5, 0,1), ncol=5)
Z <- rnorm(100, 2, 0.5)
geno <- rbinom(100, 2, 0.5)
out <- GEEaSPU(traits, geno, Z = NULL, model = "gaussian", 
	  gamma = c(1:8,Inf), n.sim = 100)

# }