RepBox: a toolbox for the identification of repetitive elements.
Bioinformatics pipeline
Detection software
Genomics
Transposable elements
Journal
BMC bioinformatics
ISSN: 1471-2105
Titre abrégé: BMC Bioinformatics
Pays: England
ID NLM: 100965194
Informations de publication
Date de publication:
22 Aug 2023
22 Aug 2023
Historique:
received:
05
08
2021
accepted:
18
07
2023
medline:
24
8
2023
pubmed:
23
8
2023
entrez:
23
8
2023
Statut:
epublish
Résumé
Transposable elements (TEs) are short, mobile DNA elements that are known to play important roles in the genomes of many eukaryotic species. The identification and categorization of these elements is a critical task for many genomic studies, and the continued increase in the number of de novo assembled genomes demands new tools to improve the efficiency of this process. For this reason, we developed RepBox, a suite of Python scripts that combine several pre-existing family-specific TE detection methods into a single user-friendly pipeline. Based on comparisons of RepBox with the standard TE detection software RepeatModeler, we find that RepBox consistently classifies more elements and is also able to identify a more diverse array of TE families than the existing methods in plant genomes. The performance of RepBox on two different plant genomes indicates that our toolbox represents a significant improvement over existing TE detection methods, and should facilitate future TE annotation efforts in additional species.
Sections du résumé
BACKGROUND
BACKGROUND
Transposable elements (TEs) are short, mobile DNA elements that are known to play important roles in the genomes of many eukaryotic species. The identification and categorization of these elements is a critical task for many genomic studies, and the continued increase in the number of de novo assembled genomes demands new tools to improve the efficiency of this process. For this reason, we developed RepBox, a suite of Python scripts that combine several pre-existing family-specific TE detection methods into a single user-friendly pipeline.
RESULTS
RESULTS
Based on comparisons of RepBox with the standard TE detection software RepeatModeler, we find that RepBox consistently classifies more elements and is also able to identify a more diverse array of TE families than the existing methods in plant genomes.
CONCLUSIONS
CONCLUSIONS
The performance of RepBox on two different plant genomes indicates that our toolbox represents a significant improvement over existing TE detection methods, and should facilitate future TE annotation efforts in additional species.
Identifiants
pubmed: 37608271
doi: 10.1186/s12859-023-05419-5
pii: 10.1186/s12859-023-05419-5
pmc: PMC10463291
doi:
Substances chimiques
DNA Transposable Elements
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
317Subventions
Organisme : U.S. Department of Education
ID : P200A150266
Informations de copyright
© 2023. BioMed Central Ltd., part of Springer Nature.
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