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README 678b09e63c academic/megax: Added (Molecular Evolutionary Genetics Analysis). 6 years ago
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README

MEGA: Molecular Evolutionary Genetics Analysis

Sophisticated and user-friendly software suite for analyzing DNA and
protein sequence data from species and populations. MEGA can be used
with either a graphical user interface, useful for visual exploration
of data and results or a command-line interface (useful for batch or
scripted execution).

MEGA X
MEGA X is the GUI graphical user interface of MEGA and can be run in
one of two modes. The first mode is the "Analyze mode" in which all
GUI tools in MEGA are enabled and visual results explorers are
available for tasks such as editing sequence alignments and viewing
phylogenies. This is the mode that most MEGA users are familiar with.
The second mode is the Prototype mode which is used solely for
generating MEGA Analysis Options (.mao) files that specify analysis
settings when using MEGA from a command shell (megacc). In the MEGA
main form, click the Prototype button and then specify the type of
input data that will be used for analysis.

MEGA CC
The command-line version of MEGA is 'megacc', that implements its core
analysis functions and is useful for iterative and automated execution.
The megacc command requires several options, including the path to a
.mao file and paths to input data file(s) to be analyzed. For example:

$ megacc -a myMaoFile.mao -d mySequenceAlignment.fas -o myOutput

Note 1.
Upon start, MEGA X will create an examples folder with the same name
in your user's home. This is a good place to start if you are not
familiar with MEGA.

Note 2.
This SlackBuild just repackages the binaries for Debian, provided from
upstream. The RedHat packages, currently, do not have 32bit version.

Note 3. IMPORTANT!
SlackBuilds.org thanks Prof. Kumar for permission to use the direct
download URL. MEGA is not free software. Your use is subject to the
licence agreement at:

http://www.megasoftware.net/show_eua

Citing:
MEGA7: Molecular Evolutionary Genetics Analysis version 7.0 for bigger
datasets (Kumar, Stecher, and Tamura 2015).