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

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 s...

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Autores principales: Riggs, Kaleigh, Chen, Huann‐Sheng, Rotunno, Melissa, Li, Bing, Simonds, Naoko I., Mechanic, Leah E., Peng, Bo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7984380/
https://www.ncbi.nlm.nih.gov/pubmed/33063887
http://dx.doi.org/10.1002/gepi.22362
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author Riggs, Kaleigh
Chen, Huann‐Sheng
Rotunno, Melissa
Li, Bing
Simonds, Naoko I.
Mechanic, Leah E.
Peng, Bo
author_facet Riggs, Kaleigh
Chen, Huann‐Sheng
Rotunno, Melissa
Li, Bing
Simonds, Naoko I.
Mechanic, Leah E.
Peng, Bo
author_sort Riggs, Kaleigh
collection PubMed
description 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.
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spelling pubmed-79843802021-03-25 On the application, reporting, and sharing of in silico simulations for genetic studies Riggs, Kaleigh Chen, Huann‐Sheng Rotunno, Melissa Li, Bing Simonds, Naoko I. Mechanic, Leah E. Peng, Bo Genet Epidemiol Review Article 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. John Wiley and Sons Inc. 2020-10-16 2021-03 /pmc/articles/PMC7984380/ /pubmed/33063887 http://dx.doi.org/10.1002/gepi.22362 Text en © 2020 The Authors. Genetic Epidemiology published by Wiley Periodicals LLC. This article has been contributed to by US Government employees and their work is in the public domain in the USA. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Review Article
Riggs, Kaleigh
Chen, Huann‐Sheng
Rotunno, Melissa
Li, Bing
Simonds, Naoko I.
Mechanic, Leah E.
Peng, Bo
On the application, reporting, and sharing of in silico simulations for genetic studies
title On the application, reporting, and sharing of in silico simulations for genetic studies
title_full On the application, reporting, and sharing of in silico simulations for genetic studies
title_fullStr On the application, reporting, and sharing of in silico simulations for genetic studies
title_full_unstemmed On the application, reporting, and sharing of in silico simulations for genetic studies
title_short On the application, reporting, and sharing of in silico simulations for genetic studies
title_sort on the application, reporting, and sharing of in silico simulations for genetic studies
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7984380/
https://www.ncbi.nlm.nih.gov/pubmed/33063887
http://dx.doi.org/10.1002/gepi.22362
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