Mega12: Molecular Evolutionary Genetic Analysis version 12 for adaptive and green computing

Sudhir Kumar, Glen Stecher, Michael Suleski, Maxwell Sanderford, Sudip Sharma, Koichiro Tamura

Research output: Contribution to journalArticlepeer-review

Abstract

We introduce the 12th version of the Molecular Evolutionary Genetics Analysis (MEGA) software. This latest version brings many significant improvements by reducing the computational time needed for selecting optimal substitution models and conducting bootstrap tests on phylogenies using maximum likelihood (ML) methods. These improvements are achieved by implementing heuristics that minimize likely unnecessary computations. Analyses of empirical and simulated datasets show substantial time savings by using these heuristics without compromising the accuracy of results. MEGA12 also implements an evolutionary sparse learning approach to identify fragile clades and associated sequences in evolutionary trees inferred through phylogenomic analyses. In addition, this version includes fine-grained parallelization for ML analyses, support for high-resolution monitors, and an enhanced Tree Explorer. MEGA12 can be downloaded from https://www.megasoftware.net.

Original languageEnglish
Article numbermsae263
JournalMolecular Biology and Evolution
Volume41
Issue number12
DOIs
StatePublished - Dec 1 2024

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