longskat_snp_test: None

In ZWang-Lab/LSKAT: SNP-set (Sequence) Kernel Association Test for longitudinal data.

Description

None

Usage

longskat_snp_test(r.model, 
    snp, 
    weights.common = c(0.5, 0.5),
    weights.rare = c(1, 25), 
    snp.impute = "mean",
    rare.cutoff = NULL, 
    run.cpp = F, 
    verbose = FALSE )

Arguments

r.model	The list object obtained from the function longskat_est_model, including the estimated parameters and residuals.
snp	Matrix with m row for individuals and n columns for the variaints(SNPs), also with the individuals' ID as the row names.
weights.common	a numeric vector of parameters of beta weights for common variants (default=c(0.5,0.5)).
weights.rare	a numeric vector of parameters of beta weights for rare variants (default=c(1,25)).
rare.cutoff	Numeric, a value of MAF cutoff for the rare SNPs. Only SNPs that have MAFs smaller than this are considered as rare SNP. The default criterion of rare SNP is calculated by the formula 1/√{2*sample}
run.cpp	Logical, indicating whether C/C++ functions are used to compute LSKAT.
verbose	Logical variable, indicating whether some debug information can be outputted.

Value

None

Examples

## data simulation for the power test
p0 <- longskat_gene_simulate( plink.format=F, power.test=T, n.gene=1);

## model estimation
r.model <- longskat_est_model( p0$phe.long, p0$phe.cov, g.maxiter=3, verbose=T);

for(i in 1:NCOL(p0$snp.mat[[1]]))
{
    ## test all SNPs in the 1st gene.
    r.lskat <- longskat_snp_test(r.model, p0$snp.mat[[1]][,i]);
    print(r.lskat);
}

ZWang-Lab/LSKAT documentation built on May 10, 2019, 1:55 a.m.