aSPUd: Adaptive Sum of powered score (SPU) tests (SPU and aSPU)...

Description Usage Arguments Value References See Also Examples

Description

It gives the p-values of the SPU(1), SPU(2) and minP tests and aSPUd test based on the asymptotic distribution.

Usage

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aSPUd(Y, X, cov = NULL, model = c("gaussian", "binomial"))

Arguments

Y

phenotype data. It can be disease lables; =0 for controls, =1 for cases. or It can be any quantitative traits. Vector with length n (number of observations)

X

genotype data; each row for a subject, and each column for an SNP. The value of each element is the # of the copies for an allele. Matrix with dimension n by k (n : number of observation, k : number of genotype data)

cov

covariates. Matrix with dimension n by p (n :number of observation, p : number of covariates)

model

Use "gaussian" for quantitative trait (Default) , and Use "binomial" for binary trait.

Value

p-values for SPU(1), SPU(2), minP tests and aSPU test.

References

Gongjun Xu, Lifeng Lin, Peng Wei and Wei Pan (2016) An adaptive two-sample test for high-dimensional means, Biometrika (2016) 103 (3): 609-624.

See Also

aSPU

Examples

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data(exdat)
out <- aSPUd(exdat$Y, exdat$X, cov = NULL, model = "binomial")
out

aSPU documentation built on May 1, 2019, 7:04 p.m.