Molecular Evolutionary Genetics Analysis


Molecular Evolutionary Genetics Analysis is computer software for conducting statistical analysis of molecular evolution and for constructing phylogenetic trees. It includes many sophisticated methods and tools for phylogenomics and phylomedicine. It is licensed as proprietary freeware. The project for developing this software was initiated by the leadership of Masatoshi Nei in his laboratory at the Pennsylvania State University in collaboration with his graduate student Sudhir Kumar and postdoctoral fellow Koichiro Tamura. Nei wrote a monograph outlining the scope of the software and presenting new statistical methods that were included in MEGA. The entire set of computer programs was written by Kumar and Tamura. The personal computers then lacked the ability to send the monograph and software electronically, so they were delivered by postal mail. From the start, MEGA was intended to be easy-to-use and include solid statistical methods only.
MEGA version 2, which was coauthored by an additional investigator Ingrid Jakobson, was released in 2001. All the computer programs and the readme files of this version could be sent electronically due to advances in computer technology. Around this time, the leadership of the MEGA project was taken over by Kumar and Tamura. The monograph Molecular Evolutionary Genetics Analysis was often used as a textbook for new ways to study molecular evolution.
MEGA has been updated and expanded several times and currently all these versions are available from the MEGA website. The latest release, MEGA7, has been optimized for use on 64-bit computing systems. MEGA is in two version. A graphical user interface is available as a native Microsoft Windows program. A command line version, MEGA-Computing Core, is available for native cross-platform operation. The method is widely used and cited. With millions of downloads across the releases, MEGA is cited in more than 85,000 papers. The 5th version has been cited over 25,000 times in 4 years.

Release history

Features

Sequence alignment construction