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LtrDetector: A tool-suite for detecting long terminal repeat retrotransposons de-novo.
Valencia, Joseph D; Girgis, Hani Z.
Afiliação
  • Valencia JD; The Bioinformatics Toolsmith Laboratory, Tandy School of Computer Science, University of Tulsa, 800 South Tucker Drive, Tulsa, 74104, OK, USA.
  • Girgis HZ; The Bioinformatics Toolsmith Laboratory, Tandy School of Computer Science, University of Tulsa, 800 South Tucker Drive, Tulsa, 74104, OK, USA. hani-girgis@utulsa.edu.
BMC Genomics ; 20(1): 450, 2019 Jun 03.
Article em En | MEDLINE | ID: mdl-31159720
BACKGROUND: Long terminal repeat retrotransposons are the most abundant transposons in plants. They play important roles in alternative splicing, recombination, gene regulation, and defense mechanisms. Large-scale sequencing projects for plant genomes are currently underway. Software tools are important for annotating long terminal repeat retrotransposons in these newly available genomes. However, the available tools are not very sensitive to known elements and perform inconsistently on different genomes. Some are hard to install or obsolete. They may struggle to process large plant genomes. None can be executed in parallel out of the box and very few have features to support visual review of new elements. To overcome these limitations, we developed LtrDetector, which uses techniques inspired by signal-processing. RESULTS: We compared LtrDetector to LTR_Finder and LTRharvest, the two most successful predecessor tools, on six plant genomes. For each organism, we constructed a ground truth data set based on queries from a consensus sequence database. According to this evaluation, LtrDetector was the most sensitive tool, achieving 16-23% improvement in sensitivity over LTRharvest and 21% improvement over LTR_Finder. All three tools had low false positive rates, with LtrDetector achieving 98.2% precision, in between its two competitors. Overall, LtrDetector provides the best compromise between high sensitivity and low false positive rate while requiring moderate time and utilizing memory available on personal computers. CONCLUSIONS: LtrDetector uses a novel methodology revolving around k-mer distributions, which allows it to produce high-quality results using relatively lightweight procedures. It is easy to install and use. It is not species specific, performing well using its default parameters on genomes of varying size and repeat content. It is automatically configured for parallel execution and runs efficiently on an ordinary personal computer. It includes a k-mer scores visualization tool to facilitate manual review of the identified elements. These features make LtrDetector an attractive tool for future annotation projects involving long terminal repeat retrotransposons.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Plantas / Software / Retroelementos / Genoma de Planta / Sequências Repetidas Terminais / Genômica / Drosophila Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Plantas / Software / Retroelementos / Genoma de Planta / Sequências Repetidas Terminais / Genômica / Drosophila Tipo de estudo: Prognostic_studies Limite: Animals Idioma: En Ano de publicação: 2019 Tipo de documento: Article