FCCC LOGO Faculty Publications
Tamura K , Stecher G , Kumar S
MEGA11: Molecular Evolutionary Genetics Analysis version 11
Mol Biol Evol. 2021 Jun 25;38(7) :3022-3027
PMID: 33892491    PMCID: PMC8233496    URL: https://www.ncbi.nlm.nih.gov/pubmed/33892491
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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, which will be 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. We have now added 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 (GUI) has been made more responsive and interactive for very big datasets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled GUI and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net.
1537-1719 Tamura, Koichiro Stecher, Glen Kumar, Sudhir R01 GM126567/GM/NIGMS NIH HHS/United States R35 GM139540/GM/NIGMS NIH HHS/United States Journal Article United States Mol Biol Evol. 2021 Apr 23:msab120. doi: 10.1093/molbev/msab120.