Bioinformatics Advance Access originally published online on April 5, 2009
Bioinformatics 2009 25(10):1329-1330; doi:10.1093/bioinformatics/btp084
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
TEclass—a tool for automated classification of unknown eukaryotic transposable elements
1Katholieke Universiteit Leuven, Department of Biology, Laboratory of Aquatic Ecology and Evolutionary Biology, Ch. Deberiotstraat 32, 3000 Leuven, Belgium and 2University of Münster, Faculty of Medicine, Institute of Bioinformatics, Von-Esmarch-Str. 54, D-48149 Münster, Germany
*To whom correspondence should be addressed.
| Abstract |
|---|
Motivation: The large number of sequenced genomes required the development of software that reconstructs the consensus sequences of transposons and other repetitive elements. However, the available tools usually focus on the accurate identification of raw repeats and provide no information about the taxonomic position of the reconstructed consensi. TEclass is a tool to classify unknown transposable elements into their four main functional categories, which reflect their mode of transposition: DNA transposons, long terminal repeats (LTRs), long interspersed nuclear elements (LINEs) and short interspersed nuclear elements (SINEs). TEclass uses machine learning support vector machine (SVM) for classification based on oligomer frequencies. It achieves 90–97% accuracy in the classification of novel DNA and LTR repeats, and 75% for LINEs and SINEs.
Availability: http://www.compgen.uni-muenster.de/teclass, stand alone program upon request.
Contact: abrusan{at}uni-muenster.de
Associate Editor: Alex Bateman
Received on December 1, 2008; revised on January 13, 2009; accepted on February 9, 2009
This article has been cited by other articles:
![]() |
S. Steinbiss, U. Willhoeft, G. Gremme, and S. Kurtz Fine-grained annotation and classification of de novo predicted LTR retrotransposons Nucleic Acids Res., September 28, 2009; (2009) gkp759v1. [Abstract] [Full Text] [PDF] |
||||
