dc.contributor.author | Zollanvari, Amin | en_US |
dc.contributor.author | Alterovitz, Gil | en_US |
dc.date.accessioned | 2017-04-06T03:18:06Z | |
dc.date.issued | 2017 | en_US |
dc.identifier.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. | en |
dc.identifier.issn | | en |
dc.identifier.uri | http://nrs.harvard.edu/urn-3:HUL.InstRepos:32071895 | |
dc.description.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. | en |
dc.language.iso | en_US | en |
dc.publisher | BioMed Central | en |
dc.relation.isversionof | doi:10.1186/s12918-017-0403-7 | en |
dc.relation.hasversion | http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5374593/pdf/ | en |
dash.license | LAA | en_US |
dc.subject | GWAS | en |
dc.subject | Alcoholism | en |
dc.subject | SNP | en |
dc.subject | Environment | en |
dc.subject | Interaction | en |
dc.subject | Network | en |
dc.title | SNP by SNP by environment interaction network of alcoholism | en |
dc.type | Journal Article | en_US |
dc.description.version | Version of Record | en |
dc.relation.journal | BMC Systems Biology | en |
dash.depositing.author | Alterovitz, Gil | en_US |
dc.date.available | 2017-04-06T03:18:06Z | |
dc.identifier.doi | 10.1186/s12918-017-0403-7 | * |
dash.contributor.affiliated | Alterovitz, Gil | |