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MatGAT: An application that generates similarity/identity matrices using protein or DNA sequences

BioMed Central
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  • Methodology Article
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Abstract ral ss BioMed CentBMC Bioinformatics Open AcceMethodology article MatGAT: An application that generates similarity/identity matrices using protein or DNA sequences James J Campanella*, Ledion Bitincka and John Smalley Address: Montclair State University, Department of Biology and Molecular Biology, 1 Normal Avenue, Montclair, New Jersey 07043 USA Email: James J Campanella* - [email protected]; Ledion Bitincka - [email protected]; John Smalley - [email protected] * Corresponding author nucleic acidproteinsequencealignmentpairwise analysissimilarity matrix Abstract Background: The rapid increase in the amount of protein and DNA sequence information available has become almost overwhelming to researchers. So much information is now accessible that high-quality, functional gene analysis and categorization has become a major goal for many laboratories. To aid in this categorization, there is a need for non-commercial software that is able to both align sequences and also calculate pairwise levels of similarity/identity. Results: We have developed MatGAT (Matrix Global Alignment Tool), a simple, easy to use computer application that generates similarity/identity matrices for DNA or protein sequences without needing pre-alignment of the data. Conclusions: The advantages of this program over other software are that it is open-source freeware, can analyze a large number of sequences simultaneously, can visualize both sequence alignment and similarity/identity values concurrently, employs global alignment in calculations, and has been formatted to run under both the Unix and the Microsoft Windows Operating Systems. We are presently completing the Macintosh-based version of the program. Introduction The application of phylogenetics in the examination of a genome has been dubbed "phylogenomics" [1–3]. The analytic process of phylogenomics is taking on more importance as additional DNA and protein sequences from a multitude o

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