Abstract
BackgroundAnalyzing Variance heterogeneity in genome wide association studies (vGWAS) is an emerging approach for detecting genetic loci involved in gene-gene and gene-environment interactions. vGWAS analysis detects variability in phenotype values across genotypes, as opposed to typical GWAS analysis, which detects variations in the mean phenotype value.ResultsA handful of vGWAS analysis methods have been recently introduced in the literature. However, very little work has been done for evaluating these methods. To enable the development of better vGWAS analysis methods, this work presents the first quantitative vGWAS simulation procedure. To that end, we describe the mathematical framework and algorithm for generating quantitative vGWAS phenotype data from genotype profiles. Our simulation model accounts for both haploid and diploid genotypes under different modes of dominance. Our model is also able to simulate any number of genetic loci causing mean and variance heterogeneity.ConclusionsWe demonstrate the utility of our simulation procedure through generating a variety of genetic loci types to evaluate common GWAS and vGWAS analysis methods. The results of this evaluation highlight the challenges current tools face in detecting GWAS and vGWAS loci.
Highlights
Analyzing Variance heterogeneity in genome wide association studies is an emerging approach for detecting genetic loci involved in gene-gene and gene-environment interactions. vGWAS analysis detects variability in phenotype values across genotypes, as opposed to typical Genome-wide association studies (GWAS) analysis, which detects variations in the mean phenotype value
Detecting vGWAS loci enables researchers to identify and study genetic loci involved in these interactions. vGWAS analysis aim to detect genetic loci that
We describe the implementation of our vGWAS simulation algorithm and demonstrate it’s utility in the “Results and discussion” section before presenting our conclusions in the last section
Summary
A handful of vGWAS analysis methods have been recently introduced in the literature. Very little work has been done for evaluating these methods. To enable the development of better vGWAS analysis methods, this work presents the first quantitative vGWAS simulation procedure. We describe the mathematical framework and algorithm for generating quantitative vGWAS phenotype data from genotype profiles. Our simulation model accounts for both haploid and diploid genotypes under different modes of dominance. Our model is able to simulate any number of genetic loci causing mean and variance heterogeneity
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