ArticleBMC bioinformatics2012
Simulating gene-gene and gene-environment interactions in complex diseases: Gene-Environment iNteraction Simulator 2.
Article in BMC bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Pathway-induced allelic spectra of diseases in the presence of strong genetic effects.Human genetics · 2018Article
- The importance of gene-environment interactions in human obesity.Clinical science (London, England : 1979) · 2016Review
- A Global Health Diagnostic for Personalized Medicine in Resource-Constrained World Settings: A Simple PCR-RFLP Method for Genotyping CYP2B6 g.15582C>T and Science and Policy Relevance for Optimal Use of Antiretroviral Drug Efavirenz.Omics : a journal of integrative biology · 2015Article
- A method to associate all possible combinations of genetic and environmental factors using GxE landscape plot.Bioinformation · 2015Article
- Genetic data simulators and their applications: an overview.Genetic epidemiology · 2015Article
- A C++ template library for efficient forward-time population genetic simulation of large populations.Genetics · 2014Article
- A whole-genome simulator capable of modeling high-order epistasis for complex disease.Genetic epidemiology · 2013Article
- Systems Modeling at Multiple Levels of Regulation: Linking Systems and Genetic Networks to Spatially Explicit Plant Populations.Plants (Basel, Switzerland) · 2013Review
- Using mouse models of autism spectrum disorders to study the neurotoxicology of gene-environment interactions.Neurotoxicology and teratologyReview
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe analysis of complex diseases is an important problem in human genetics. Because multifactoriality is expected to play a pivotal role, many studies are currently focused on collecting information on the genetic and environmental factors that potentially influence these diseases. However, there is still a lack of efficient and thoroughly tested statistical models that can be used to identify implicated features and their interactions. Simulations using large biologically realistic data sets with known gene-gene and gene-environment interactions that influence the risk of a complex disease are a convenient and useful way to assess the performance of statistical methods.
resultsThe Gene-Environment iNteraction Simulator 2 (GENS2) simulates interactions among two genetic and one environmental factor and also allows for epistatic interactions. GENS2 is based on data with realistic patterns of linkage disequilibrium, and imposes no limitations either on the number of individuals to be simulated or on number of non-predisposing genetic/environmental factors to be considered. The GENS2 tool is able to simulate gene-environment and gene-gene interactions. To make the Simulator more intuitive, the input parameters are expressed as standard epidemiological quantities. GENS2 is written in Python language and takes advantage of operators and modules provided by the simuPOP simulation environment. It can be used through a graphical or a command-line interface and is freely available from http://sourceforge.net/projects/gensim. The software is released under the GNU General Public License version 3.0.
conclusionsData produced by GENS2 can be used as a benchmark for evaluating statistical tools designed for the identification of gene-gene and gene-environment interactions.
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