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A brief history and popularity of methods and tools used to estimate micro‐evolutionary forces

Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that...

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Autores principales: Kidner, Jonathan, Theodorou, Panagiotis, Engler, Jan O., Taubert, Martin, Husemann, Martin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8525119/
https://www.ncbi.nlm.nih.gov/pubmed/34707813
http://dx.doi.org/10.1002/ece3.8076
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author Kidner, Jonathan
Theodorou, Panagiotis
Engler, Jan O.
Taubert, Martin
Husemann, Martin
author_facet Kidner, Jonathan
Theodorou, Panagiotis
Engler, Jan O.
Taubert, Martin
Husemann, Martin
author_sort Kidner, Jonathan
collection PubMed
description Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome‐wide estimates of the four major micro‐evolutionary forces—mutation, gene flow, genetic drift, and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and high‐throughput sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro‐evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility.
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spelling pubmed-85251192021-10-26 A brief history and popularity of methods and tools used to estimate micro‐evolutionary forces Kidner, Jonathan Theodorou, Panagiotis Engler, Jan O. Taubert, Martin Husemann, Martin Ecol Evol Reviews Population genetics is a field of research that predates the current generations of sequencing technology. Those approaches, that were established before massively parallel sequencing methods, have been adapted to these new marker systems (in some cases involving the development of new methods) that allow genome‐wide estimates of the four major micro‐evolutionary forces—mutation, gene flow, genetic drift, and selection. Nevertheless, classic population genetic markers are still commonly used and a plethora of analysis methods and programs is available for these and high‐throughput sequencing (HTS) data. These methods employ various and diverse theoretical and statistical frameworks, to varying degrees of success, to estimate similar evolutionary parameters making it difficult to get a concise overview across the available approaches. Presently, reviews on this topic generally focus on a particular class of methods to estimate one or two evolutionary parameters. Here, we provide a brief history of methods and a comprehensive list of available programs for estimating micro‐evolutionary forces. We furthermore analyzed their usage within the research community based on popularity (citation bias) and discuss the implications of this bias for the software community. We found that a few programs received the majority of citations, with program success being independent of both the parameters estimated and the computing platform. The only deviation from a model of exponential growth in the number of citations was found for the presence of a graphical user interface (GUI). Interestingly, no relationship was found for the impact factor of the journals, when the tools were published, suggesting accessibility might be more important than visibility. John Wiley and Sons Inc. 2021-09-16 /pmc/articles/PMC8525119/ /pubmed/34707813 http://dx.doi.org/10.1002/ece3.8076 Text en © 2021 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Reviews
Kidner, Jonathan
Theodorou, Panagiotis
Engler, Jan O.
Taubert, Martin
Husemann, Martin
A brief history and popularity of methods and tools used to estimate micro‐evolutionary forces
title A brief history and popularity of methods and tools used to estimate micro‐evolutionary forces
title_full A brief history and popularity of methods and tools used to estimate micro‐evolutionary forces
title_fullStr A brief history and popularity of methods and tools used to estimate micro‐evolutionary forces
title_full_unstemmed A brief history and popularity of methods and tools used to estimate micro‐evolutionary forces
title_short A brief history and popularity of methods and tools used to estimate micro‐evolutionary forces
title_sort brief history and popularity of methods and tools used to estimate micro‐evolutionary forces
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8525119/
https://www.ncbi.nlm.nih.gov/pubmed/34707813
http://dx.doi.org/10.1002/ece3.8076
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