CombTEs: combining predictions from the search for transposable elements

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dc.contributor.authorFischer, Carlos Norberto [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.date.accessioned2023-07-29T16:05:23Z
dc.date.available2023-07-29T16:05:23Z
dc.date.issued2022-01-01
dc.description.abstractSeveral tools, using different approaches, are available nowadays to identify transposable elements (TEs) in a query sequence. Normally, a same set of TEs can be predicted by many of these tools. However, for other TEs, only a few tools are able to predict them due to their particular characteristics. In both cases, combining predictions produced by two or more tools can be an interesting approach to increasing the number of correct results and, at the same time, to further improve the confidence about the predicted TEs. Taking this into account, this work presents an auxiliary tool, CombTEs, that combines predictions produced by other programs and pipelines used to identify TEs in a genome sequence. The basic idea is that, after running only once the tools of interest, the same sets of initial predictions are used in several combining processes, each one considering different values for the parameters used by CombTEs (for example, filters and distance between predictions), in a very fast way, making the annotation step easier and more reliable.en
dc.description.affiliationDepartment of Statistics Applied Maths and Computer Science UNESP – São Paulo State University, SP
dc.description.affiliationUnespDepartment of Statistics Applied Maths and Computer Science UNESP – São Paulo State University, SP
dc.format.extent496-504
dc.identifierhttp://dx.doi.org/10.1504/IJBRA.2022.128238
dc.identifier.citationInternational Journal of Bioinformatics Research and Applications, v. 18, n. 5, p. 496-504, 2022.
dc.identifier.doi10.1504/IJBRA.2022.128238
dc.identifier.issn1744-5493
dc.identifier.issn1744-5485
dc.identifier.scopus2-s2.0-85147819652
dc.identifier.urihttp://hdl.handle.net/11449/249646
dc.language.isoeng
dc.relation.ispartofInternational Journal of Bioinformatics Research and Applications
dc.sourceScopus
dc.subjectbioinformatics tools
dc.subjectcombining predictions
dc.subjectLTR retrotransposons
dc.subjectpHMMs
dc.subjectprediction combination
dc.subjectprofile hidden Markov models
dc.subjectsimilarity method
dc.subjecttransposable element classification
dc.subjecttransposable element searches
dc.subjecttransposable elements
dc.titleCombTEs: combining predictions from the search for transposable elementsen
dc.typeArtigo

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