Peng Bo, Chen Huann-Sheng, Mechanic Leah E, Racine Ben, Clarke John, Gillanders Elizabeth, Feuer Eric J
Department of Bioinformatics and Computational Biology, The University of Texas, MD Anderson Cancer Center, Houston, Texas, United States of America.
Genet Epidemiol. 2015 Jan;39(1):2-10. doi: 10.1002/gepi.21876. Epub 2014 Dec 13.
Computer simulations have played an indispensable role in the development and applications of statistical models and methods for genetic studies across multiple disciplines. The need to simulate complex evolutionary scenarios and pseudo-datasets for various studies has fueled the development of dozens of computer programs with varying reliability, performance, and application areas. To help researchers compare and choose the most appropriate simulators for their studies, we have created the genetic simulation resources (GSR) website, which allows authors of simulation software to register their applications and describe them with more than 160 defined attributes. This article summarizes the properties of 93 simulators currently registered at GSR and provides an overview of the development and applications of genetic simulators. Unlike other review articles that address technical issues or compare simulators for particular application areas, we focus on software development, maintenance, and features of simulators, often from a historical perspective. Publications that cite these simulators are used to summarize both the applications of genetic simulations and the utilization of simulators.
计算机模拟在多学科遗传研究的统计模型和方法的开发与应用中发挥了不可或缺的作用。为各种研究模拟复杂进化场景和伪数据集的需求推动了数十种计算机程序的开发，这些程序具有不同的可靠性、性能和应用领域。为帮助研究人员比较并选择最适合其研究的模拟器，我们创建了遗传模拟资源（GSR）网站，该网站允许模拟软件的作者注册其应用程序并用160多个定义的属性对其进行描述。本文总结了目前在GSR上注册的93个模拟器的特性，并概述了遗传模拟器的开发与应用。与其他论述技术问题或比较特定应用领域模拟器的综述文章不同，我们通常从历史角度关注模拟器的软件开发、维护和特性。引用这些模拟器的出版物用于总结遗传模拟的应用以及模拟器的使用情况。
