An R package 'VariABEL' for genome-wide searching of potentially interacting loci by testing genotypic variance heterogeneity
| Autor: | Maksim Struchalin, Cornelia M. van Duijn, Najaf Amin, Paul H. C. Eilers, Yurii S. Aulchenko |
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| Přispěvatelé: | Epidemiology |
| Jazyk: | angličtina |
| Rok vydání: | 2012 |
| Předmět: |
environmental sensitivity
lcsh:QH426-470 Genotype Context (language use) Biology gene-gene interactions (GxG) Polymorphism Single Nucleotide single-nucleotide polymorphisms (SNPs) variance heterogeneity VariABEL genome-wide association (GWA) Genetic variation Genetic model Genetics gene-environment interactions (GxE) Humans Genetics(clinical) Genetics (clinical) Genetic association Methodology Article Computational Biology Genetic Variation Variance (accounting) lcsh:Genetics Multiple comparisons problem Trait the GenABEL project Software Type I and type II errors |
| Zdroj: | BMC Genetics BMC Genetics, 13. BioMed Central Ltd. BMC Genetics, Vol 13, Iss 1, p 4 (2012) |
| ISSN: | 1471-2156 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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