Gruppo Interdipartimentale di Bioinformatica e Biologia Computazionale, Università di Napoli "Federico II" - Università di Salerno, Italy.
BMC Bioinformatics. 2012 Jun 14;13:132. doi: 10.1186/1471-2105-13-132.
The 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.
The 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.
Data produced by GENS2 can be used as a benchmark for evaluating statistical tools designed for the identification of gene-gene and gene-environment interactions.
复杂疾病的分析是人类遗传学中的一个重要问题。由于多因素性预计将发挥关键作用,目前许多研究都集中在收集可能影响这些疾病的遗传和环境因素的信息上。然而,仍然缺乏高效且经过充分测试的统计模型,可以用于识别相关特征及其相互作用。使用具有已知影响复杂疾病风险的基因-基因和基因-环境相互作用的大型生物学上合理的数据集进行模拟是评估统计方法性能的一种便捷且有用的方法。
基因-环境相互作用模拟器 2(GENS2)模拟两个遗传因素和一个环境因素之间的相互作用,并且还允许存在上位性相互作用。GENS2 基于具有现实连锁不平衡模式的数据,并且对要模拟的个体数量或要考虑的非易患遗传/环境因素数量没有任何限制。GENS2 工具能够模拟基因-环境和基因-基因相互作用。为了使模拟器更直观,输入参数表示为标准流行病学量。GENS2 是用 Python 语言编写的,利用了 simuPOP 模拟环境提供的运算符和模块。它可以通过图形界面或命令行界面使用,并可从 http://sourceforge.net/projects/gensim 免费获得。该软件根据 GNU 通用公共许可证版本 3.0 发布。
GENS2 生成的数据可用于评估旨在识别基因-基因和基因-环境相互作用的统计工具。