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Last data update: 2014.03.03

R: Sum of Powered Score (SPU) tests and adaptive SPU (aSPU) test...

aSPU	R Documentation

Sum of Powered Score (SPU) tests and adaptive SPU (aSPU) test for single trait - SNP set association.

Description

It gives p-values of the SPU tests and aSPU test.

Usage

aSPU(Y, X, cov = NULL, resample = c("perm", "sim", "boot"),
  model = c("gaussian", "binomial"), pow = c(1:8, Inf), n.perm = 1000)

Arguments

`Y`	Response or phenotype data. It can be a disease indicator; =0 for controls, =1 for cases. Or it can be a quantitative trait. A vector with length n (number of observations).
`X`	Genotype or other data; each row for a subject, and each column for an SNP (or a predictor). The value of each SNP is the # of the copies for an allele. A matrix with dimension n by k (n : number of observation, k : number of SNPs (or predictors) ).
`cov`	Covariates. A matrix with dimension n by p (n :number of observation, p : number of covariates).
`resample`	Use "perm" for residual permutations, "sim" for simulations from the null distribution, and "boot" for parametric bootstrap.
`model`	Use "gaussian" for a quantitative trait, and use "binomial" for a binary trait.
`pow`	power 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 (in the order of the specified pow) and finally for the aSPU test. pvs : p-values for the SPU and aSPU tests.

Author(s)

Il-Youp Kwak, Junghi Kim, Yiwei Zhang 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

Junghi Kim, Jeffrey R Wozniak, Bryon A Mueller, Xiaotong Shen and Wei Pan (2014) Comparison of statistical tests for group differences in brain functional networks, NeuroImage, 1;101:681-694

Examples


data(exdat)

## example analysis using aSPU test on exdat data.
out <- aSPU(exdat$Y, exdat$X, cov = NULL, resample = "boot",
           model = "binomial", pow = c(1:8, Inf), n.perm = 1000)

out$Ts
# This is a vector of Test Statistics for SPU and aSPU tests.
# SPU1 to SPUInf corresponds with the option pow=c(1:8, Inf)
# They are SPU test statistics.
# The last element aSPU is minimum of them, aSPU statistic.

out$pvs
# This is a vector of p-values for SPU and aSPU tests.
# SPU1 to SPUInf corresponds with the option pow=c(1:8, Inf)
# They are p-values for corresponding SPU tests.
# The last element is p-value of aSPU test.