Scientific Reports · 2016 · 74 citations · 39 references
Life SciencesBioinformaticsGeneticsComparative GenomicsGene ExpressionGenomicsGenome SequencingTransposable ElementsGenome Organization EvolutionGenome-wide CharacterizationLempel-ziv CodingLempel-ziv CompressionMobile Genetic Element AnalysisMolecular Identification Of MitesRepetitive Dna ElementsTransposition Mechanisms
Miniature inverted repeat transposable elements (MITEs) are prevalent in eukaryotic genomes, including plants and animals. Classified as a type of non-autonomous DNA transposable elements, they play important roles in genome organization and evolution. Comprehensive and accurate genome-wide detection of MITEs in various eukaryotic genomes can improve our understanding of their origins, transposition processes, regulatory mechanisms, and biological relevance with regard to gene structures, expression, and regulation. In this paper, we present a new MATLAB-based program called detectMITE that employs a novel numeric calculation algorithm to replace conventional string matching algorithms in MITE detection, adopts the Lempel-Ziv complexity algorithm to filter out MITE candidates with low complexity, and utilizes the powerful clustering program CD-HIT to cluster similar MITEs into MITE families. Using the rice genome as test data, we found that detectMITE can more accurately, comprehensively, and efficiently detect MITEs on a genome-wide scale than other popular MITE detection tools. Through comparison with the potential MITEs annotated in Repbase, the widely used eukaryotic repeat database, detectMITE has been shown to find known and novel MITEs with a complete structure and full-length copies in the genome. detectMITE is an open source tool (https://sourceforge.net/projects/detectmite).
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Basic local alignment search tool
Stephen F. Altschul, Warren Gish, Webb Miller et al. · Journal of Molecular Biology · 1990 · 94.5K citations
Initial sequencing and analysis of the human genome
Eric S. Lander, Lauren Linton, Bruce W. Birren et al. · Nature · 2001 · 24.6K citations · Full text
CD-HIT: accelerated for clustering the next-generation sequencing data
LiMin Fu, Beifang Niu, Zhengwei Zhu et al. · Bioinformatics · 2012 · 11.8K citations · Full text
Life Sciences, Bioinformatics, High-performance Computing +12