aSPU_perm {GLMaSPU} | R Documentation |
Resample based Sum of Powered Score (SPU) tests and adaptive SPU (aSPU) test.
Description
aSPU_perm
returns p-values of the SPU tests and aSPU test.
Usage
aSPU_perm(Y, X, cov = NULL, resample = c("perm", "boot"),
model = c("gaussian", "binomial"), pow = c(1:6, Inf), n.perm = 1000)
Arguments
Y |
Response. It can be binary or continuous trait. A vector with length n (number of observations). |
X |
Genotype or other data; each row for a subject, and each column for a variable of interest. An n by p matrix (n: number of observations, p: number of predictors). |
cov |
Covariates. An n by q matrix (n: number of observations, q: number of covariates). |
resample |
Resample methods. "perm" for residual permutations; "boot" for parametric bootstrap. |
model |
corresponding to the Response. "gaussian" for a quantitative response; "binomial" for a binary response. |
pow |
Gamma set used in SPU test. A vector of the powers. |
n.perm |
number of permutations or bootstraps. |
Value
A list object, Ts : test statistics for the SPU tests and the aSPU test. pvs : p-values for the SPU and aSPU tests.
Author(s)
Chong Wu and Wei Pan
References
Wei Pan, Junghi Kim, Yiwei Zhang, Xiaotong Shen and Peng Wei (2014) A powerful and adaptive association test for rare variants, Genetics, 197(4), 1081-95
Examples
p = 200
n = 100
beta = c(1,3,3)
s = 0.15
signal.r = 0.08
non.zero = floor(p * s)
seed = 2
alpha = c(rep(signal.r,non.zero),rep(0,p-non.zero))
dat = generate_data(seed, n = n, p = p, beta = beta,alpha = alpha)
cov = dat$Z
X = dat$X
Y = dat$Y
aSPU_perm(Y, X, cov = cov, pow = c(1:6, Inf),resample = "perm", model = "gaussian", n.perm = 1000)
# The p-values are similar to the asymptotic based one