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MEGA11: Molecular Evolutionary Genetics Analysis Version 11

The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families u...

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Autores principales: Tamura, Koichiro, Stecher, Glen, Kumar, Sudhir
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233496/
https://www.ncbi.nlm.nih.gov/pubmed/33892491
http://dx.doi.org/10.1093/molbev/msab120
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author Tamura, Koichiro
Stecher, Glen
Kumar, Sudhir
author_facet Tamura, Koichiro
Stecher, Glen
Kumar, Sudhir
author_sort Tamura, Koichiro
collection PubMed
description The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor, and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net.
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spelling pubmed-82334962021-06-28 MEGA11: Molecular Evolutionary Genetics Analysis Version 11 Tamura, Koichiro Stecher, Glen Kumar, Sudhir Mol Biol Evol Resources The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor, and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net. Oxford University Press 2021-04-23 /pmc/articles/PMC8233496/ /pubmed/33892491 http://dx.doi.org/10.1093/molbev/msab120 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Resources
Tamura, Koichiro
Stecher, Glen
Kumar, Sudhir
MEGA11: Molecular Evolutionary Genetics Analysis Version 11
title MEGA11: Molecular Evolutionary Genetics Analysis Version 11
title_full MEGA11: Molecular Evolutionary Genetics Analysis Version 11
title_fullStr MEGA11: Molecular Evolutionary Genetics Analysis Version 11
title_full_unstemmed MEGA11: Molecular Evolutionary Genetics Analysis Version 11
title_short MEGA11: Molecular Evolutionary Genetics Analysis Version 11
title_sort mega11: molecular evolutionary genetics analysis version 11
topic Resources
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8233496/
https://www.ncbi.nlm.nih.gov/pubmed/33892491
http://dx.doi.org/10.1093/molbev/msab120
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