On the application, reporting, and sharing of in silico simulations for genetic studies

Abstract

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.

Keywords: Genetic simulations; data sets; reproducibility.