Description Usage Arguments Details Value Author(s) References See Also Examples
Function to run power/null simulations by simulating one gene and one SNP at a time. The objective of these simulations is two pronged  1) Check for the type I error control for the joint score test statistic, and 2) Compare two different null hypotheses where one's called a global null (bta=0 and PVEg =0) and other is local null (PVEg=0). Under the global null hypotheses, we fit a model where we assume that there is no main genotypic effect and groupspecific variability in the data. Under the local null, we fit a model where we assume only the absence of groupspecific variability. This is essentially a variance component score test.
1  jaguar_sim(nobs = 500, k = 5, tau = 1, eps = 1, PVEg = 0, bta = 0, maf = 0.10)

nobs 
The number of observations in each group 
k 
The total number of groups 
tau 
Variance component of the subjectspecific random effect 
eps 
Variance component of the residual error 
PVEg 
Proportion of variance explained by gamma 
bta 
Additive genotypic effect as a fixedeffect 
maf 
Minor allele frequency 
This function currently implements only balanced designs with equal number of observations in each group. For each individual, we model the potential genetic association between a target SNP and the expression level a target gene (in multiple tissues) at a single locus using the following mixed effects model (i = individual; t = tissue) 
y_{i,t}=α_t + g_i β_i + b_t g_i + u_i + ε_{i,t}
where y_{i,t} is a tdimensional vector of gene expression data for individual i, g_i is the scalar value of genotype in alleledosage format, b_t is a tdimensional tissuespecific random effect where b \sim N(0,γ), u_i is the scalar value representing individualspecific random effect where u \sim(0,τ).

A numeric vector consisting of two different pvalues, "VCScoreTest" and "JointScoreTest" with the former indicating the pvalue from the variance component score test and the latter indicating the pvalue from the joint score test. 
Chaitanya R. Acharya, Andrew S. Allen Maintainer: Chaitanya Acharya<c.acharya@duke.edu>
Chaitanya R. Acharya, Kouros Owzar, Janice M. McCarthy and Andrew S. Allen; Exploiting expression patterns across multiple tissues to map expression quantitative trait loci (Manuscript submitted)
Chaitanya R. Acharya and Andrew S. Allen; JAGUAR: An Rpackage to Implement Joint Analysis of Genotype and GroupSpecific Variability Using a Novel Score Test to Map eQTL (Manuscript submitted)
jaguar_process,jaguar_slice,jaguar_gwa,jaguar_cis,jaguar_plotqtl
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