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 group-specific variability in the data. Under the local null, we fit a model where we assume only the absence of group-specific 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)
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nobs |
The number of observations in each group |
k |
The total number of groups |
tau |
Variance component of the subject-specific random effect |
eps |
Variance component of the residual error |
PVEg |
Proportion of variance explained by gamma |
bta |
Additive genotypic effect as a fixed-effect |
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 t-dimensional vector of gene expression data for individual i, g_i is the scalar value of genotype in allele-dosage format, b_t is a t-dimensional tissue-specific random effect where b \sim N(0,γ), u_i is the scalar value representing individual-specific random effect where u \sim(0,τ).
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A numeric vector consisting of two different p-values, "VCScoreTest" and "JointScoreTest" with the former indicating the p-value from the variance component score test and the latter indicating the p-value 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 R-package to Implement Joint Analysis of Genotype and Group-Specific 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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