SNP by SNP by environment interaction network of alcoholism

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SNP by SNP by environment interaction network of alcoholism

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Title: SNP by SNP by environment interaction network of alcoholism
Author: Zollanvari, Amin; Alterovitz, Gil

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Citation: Zollanvari, Amin, and Gil Alterovitz. 2017. “SNP by SNP by environment interaction network of alcoholism.” BMC Systems Biology 11 (Suppl 3): 19. doi:10.1186/s12918-017-0403-7. http://dx.doi.org/10.1186/s12918-017-0403-7.
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Abstract: Background: Alcoholism has a strong genetic component. Twin studies have demonstrated the heritability of a large proportion of phenotypic variance of alcoholism ranging from 50–80%. The search for genetic variants associated with this complex behavior has epitomized sequence-based studies for nearly a decade. The limited success of genome-wide association studies (GWAS), possibly precipitated by the polygenic nature of complex traits and behaviors, however, has demonstrated the need for novel, multivariate models capable of quantitatively capturing interactions between a host of genetic variants and their association with non-genetic factors. In this regard, capturing the network of SNP by SNP or SNP by environment interactions has recently gained much interest. Results: Here, we assessed 3,776 individuals to construct a network capable of detecting and quantifying the interactions within and between plausible genetic and environmental factors of alcoholism. In this regard, we propose the use of first-order dependence tree of maximum weight as a potential statistical learning technique to delineate the pattern of dependencies underpinning such a complex trait. Using a predictive based analysis, we further rank the genes, demographic factors, biological pathways, and the interactions represented by our SNP \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \times $$\end{document}×SNP\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ \times $$\end{document}×E network. The proposed framework is quite general and can be potentially applied to the study of other complex traits. Electronic supplementary material The online version of this article (doi:10.1186/s12918-017-0403-7) contains supplementary material, which is available to authorized users.
Published Version: doi:10.1186/s12918-017-0403-7
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5374593/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:32071895
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