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An R package "VariABEL" for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity

BACKGROUND: Hundreds of new loci have been discovered by genome-wide association studies of human traits. These studies mostly focused on associations between single locus and a trait. Interactions between genes and between genes and environmental factors are of interest as they can improve our unde...

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Autores principales: Struchalin, Maksim V, Amin, Najaf, Eilers, Paul HC, van Duijn, Cornelia M, Aulchenko, Yurii S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398297/
https://www.ncbi.nlm.nih.gov/pubmed/22272569
http://dx.doi.org/10.1186/1471-2156-13-4
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author Struchalin, Maksim V
Amin, Najaf
Eilers, Paul HC
van Duijn, Cornelia M
Aulchenko, Yurii S
author_facet Struchalin, Maksim V
Amin, Najaf
Eilers, Paul HC
van Duijn, Cornelia M
Aulchenko, Yurii S
author_sort Struchalin, Maksim V
collection PubMed
description BACKGROUND: Hundreds of new loci have been discovered by genome-wide association studies of human traits. These studies mostly focused on associations between single locus and a trait. Interactions between genes and between genes and environmental factors are of interest as they can improve our understanding of the genetic background underlying complex traits. Genome-wide testing of complex genetic models is a computationally demanding task. Moreover, testing of such models leads to multiple comparison problems that reduce the probability of new findings. Assuming that the genetic model underlying a complex trait can include hundreds of genes and environmental factors, testing of these models in genome-wide association studies represent substantial difficulties. We and Pare with colleagues (2010) developed a method allowing to overcome such difficulties. The method is based on the fact that loci which are involved in interactions can show genotypic variance heterogeneity of a trait. Genome-wide testing of such heterogeneity can be a fast scanning approach which can point to the interacting genetic variants. RESULTS: In this work we present a new method, SVLM, allowing for variance heterogeneity analysis of imputed genetic variation. Type I error and power of this test are investigated and contracted with these of the Levene's test. We also present an R package, VariABEL, implementing existing and newly developed tests. CONCLUSIONS: Variance heterogeneity analysis is a promising method for detection of potentially interacting loci. New method and software package developed in this work will facilitate such analysis in genome-wide context.
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spelling pubmed-33982972012-07-18 An R package "VariABEL" for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity Struchalin, Maksim V Amin, Najaf Eilers, Paul HC van Duijn, Cornelia M Aulchenko, Yurii S BMC Genet Methodology Article BACKGROUND: Hundreds of new loci have been discovered by genome-wide association studies of human traits. These studies mostly focused on associations between single locus and a trait. Interactions between genes and between genes and environmental factors are of interest as they can improve our understanding of the genetic background underlying complex traits. Genome-wide testing of complex genetic models is a computationally demanding task. Moreover, testing of such models leads to multiple comparison problems that reduce the probability of new findings. Assuming that the genetic model underlying a complex trait can include hundreds of genes and environmental factors, testing of these models in genome-wide association studies represent substantial difficulties. We and Pare with colleagues (2010) developed a method allowing to overcome such difficulties. The method is based on the fact that loci which are involved in interactions can show genotypic variance heterogeneity of a trait. Genome-wide testing of such heterogeneity can be a fast scanning approach which can point to the interacting genetic variants. RESULTS: In this work we present a new method, SVLM, allowing for variance heterogeneity analysis of imputed genetic variation. Type I error and power of this test are investigated and contracted with these of the Levene's test. We also present an R package, VariABEL, implementing existing and newly developed tests. CONCLUSIONS: Variance heterogeneity analysis is a promising method for detection of potentially interacting loci. New method and software package developed in this work will facilitate such analysis in genome-wide context. BioMed Central 2012-01-24 /pmc/articles/PMC3398297/ /pubmed/22272569 http://dx.doi.org/10.1186/1471-2156-13-4 Text en Copyright ©2012 Struchalin et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Struchalin, Maksim V
Amin, Najaf
Eilers, Paul HC
van Duijn, Cornelia M
Aulchenko, Yurii S
An R package "VariABEL" for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity
title An R package "VariABEL" for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity
title_full An R package "VariABEL" for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity
title_fullStr An R package "VariABEL" for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity
title_full_unstemmed An R package "VariABEL" for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity
title_short An R package "VariABEL" for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity
title_sort r package "variabel" for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3398297/
https://www.ncbi.nlm.nih.gov/pubmed/22272569
http://dx.doi.org/10.1186/1471-2156-13-4
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