MEGA-CC: Computing core of molecular evolutionary genetics analysis program for automated and iterative data analysis

Sudhir Kumar, Glen Stecher, Daniel Peterson, Koichiro Tamura

Research output: Contribution to journalArticle

156 Scopus citations

Abstract

There is a growing need in the research community to apply the molecular evolutionary genetics analysis (MEGA) software tool for batch processing a large number of datasets and to integrate it into analysis workflows. Therefore, we now make available the computing core of the MEGA software as a stand-alone executable (MEGA-CC), along with an analysis prototyper (MEGA-Proto). MEGA-CC provides users with access to all the computational analyses available through MEGA's graphical user interface version. This includes methods for multiple sequence alignment, substitution model selection, evolutionary distance estimation, phylogeny inference, substitution rate and pattern estimation, tests of natural selection and ancestral sequence inference. Additionally, we have upgraded the source code for phylogenetic analysis using the maximum likelihood methods for parallel execution on multiple processors and cores. Here, we describe MEGA-CC and outline the steps for using MEGA-CC in tandem with MEGA-Proto for iterative and automated data analysis.

Original languageEnglish (US)
Pages (from-to)2685-2686
Number of pages2
JournalBioinformatics
Volume28
Issue number20
DOIs
StatePublished - Oct 1 2012

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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