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MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms - PubMed

  • ️Mon Jan 01 2018

MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms

Sudhir Kumar et al. Mol Biol Evol. 2018.

Abstract

The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.

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Figures

<sc>Fig</sc>. 1.
Fig. 1.

The

Mega

X main form has a modernized look-and-feel, but it maintains the familiar structure of the previous versions of

Mega

. (A) The top toolbar organizes the large number of analyses available in

Mega

X into logical groups accessed via drop down menus. (B) The bottom toolbar provides access to utility functions such as the help system, example input data files and application preferences. (C) Icons on the main form provide convenient access to input data and results explorer windows. Mega X can now be used in two modes: one for data analysis (ANALYZE mode) and another for prototyping (PROTOTYPE mode).

<sc>Fig</sc>. 2.
Fig. 2.

The redesigned GUI elements in

Mega

X include explorer windows such as the (A) Sequence Data Explorer, (B) Timetree Wizard, and (C) Tree Explorer. These use the native widget set of the target operating system. (D) Options dialogs and (E) Caption Expert were developed using HTML and JavaScript and are displayed via

Mega’

s integrated web browser that is built on the Chromium Embedded Framework. (F) The redesigned “Analysis Preferences” dialog box for selecting options for data analysis, including (G) the number of threads to employ and (H) a “Save Settings” button for generating an “.mao” file for use with MEGA-CC for high throughput analysis.

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References

    1. Kumar S, Stecher G, Peterson D, Tamura K.. 2012. MEGA-CC: computing core of molecular evolutionary genetics analysis program for automated and iterative data analysis. Bioinformatics 28(20):2685–2686. - PMC - PubMed
    1. Kumar S, Stecher G, Tamura K.. 2016. MEGA7: molecular evolutionary genetics analysis version 7.0 for bigger datasets. Mol Biol Evol. 33(7):1870–1874. - PMC - PubMed
    1. Kumar S, Tamura K, Jakobsen IB, Nei M.. 2001. MEGA2: molecular evolutionary genetics analysis software. Bioinformatics 17(12):1244–1245. - PubMed
    1. Kumar S, Tamura K, Nei M.. 1994. MEGA: molecular Evolutionary Genetics Analysis software for microcomputers. Comput Appl Biosci 10(2):189–191. - PubMed
    1. Lazarus Team. Lazarus Homepage. Available from: https://www.lazarus-ide.org/.

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