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On the application, reporting, and sharing of in silico simulations for genetic studies
Genetic Epidemiology ( IF 1.7 ) Pub Date : 2020-10-16 , DOI: 10.1002/gepi.22362
Kaleigh Riggs 1 , Huann-Sheng Chen 2 , Melissa Rotunno 3 , Bing Li 4 , Naoko I Simonds 5 , Leah E Mechanic 3 , Bo Peng 6
Affiliation  

In silico simulations play an indispensable role in the development and application of statistical models and methods for genetic studies. Simulation tools allow for the evaluation of methods and investigation of models in a controlled manner. With the growing popularity of evolutionary models and simulation‐based statistical methods, genetic simulations have been applied to a wide variety of research disciplines such as population genetics, evolutionary genetics, genetic epidemiology, ecology, and conservation biology. In this review, we surveyed 1409 articles from five journals that publish on major application areas of genetic simulations. We identified 432 papers in which genetic simulations were used and examined the targets and applications of simulation studies and how these simulation methods and simulated data sets are reported and shared. Whereas a large proportion (30%) of the surveyed articles reported the use of genetic simulations, only 28% of these genetic simulation studies used existing simulation software, 2% used existing simulated data sets, and 19% and 12% made source code and simulated data sets publicly available, respectively. Moreover, 15% of articles provided no information on how simulation studies were performed. These findings suggest a need to encourage sharing and reuse of existing simulation software and data sets, as well as providing more information regarding the performance of simulations.

中文翻译:

用于遗传研究的计算机模拟的应用、报告和共享

计算机模拟在遗传研究统计模型和方法的开发和应用中发挥着不可或缺的作用。仿真工具允许以受控方式评估方法和研究模型。随着进化模型和基于模拟的统计方法的日益普及,遗传模拟已被广泛应用于各种研究学科,如种群遗传学、进化遗传学、遗传流行病学、生态学和保护生物学。在这篇综述中,我们调查了 5 种期刊发表的 1409 篇关于遗传模拟主要应用领域的文章。我们确定了 432 篇使用遗传模拟的论文,并检查了模拟研究的目标和应用,以及如何报告和共享这些模拟方法和模拟数据集。尽管很大比例(30%)的被调查文章报告了使用遗传模拟,但这些遗传模拟研究中只有 28% 使用现有模拟软件,2% 使用现有模拟数据集,19% 和 12% 制作源代码和分别公开可用的模拟数据集。此外,15% 的文章没有提供有关如何进行模拟研究的信息。这些发现表明需要鼓励共享和重用现有的模拟软件和数据集,并提供更多有关模拟性能的信息。19% 和 12% 分别公开了源代码和模拟数据集。此外,15% 的文章没有提供有关如何进行模拟研究的信息。这些发现表明需要鼓励共享和重用现有的模拟软件和数据集,并提供更多有关模拟性能的信息。19% 和 12% 分别公开了源代码和模拟数据集。此外,15% 的文章没有提供有关如何进行模拟研究的信息。这些发现表明需要鼓励共享和重用现有的模拟软件和数据集,并提供更多有关模拟性能的信息。
更新日期:2020-10-16
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