Simulating variance heterogeneity in quantitative genome wide association studies.

Abstract:

BACKGROUND:Analyzing 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. RESULTS:A 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. CONCLUSIONS:We 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.

journal_name

BMC Bioinformatics

journal_title

BMC bioinformatics

authors

Al Kawam A,Alshawaqfeh M,Cai JJ,Serpedin E,Datta A

doi

10.1186/s12859-018-2061-1

subject

Has Abstract

pub_date

2018-03-21 00:00:00

pages

72

issue

Suppl 3

issn

1471-2105

pii

10.1186/s12859-018-2061-1

journal_volume

19

pub_type

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