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Cited 2 time in webofscience Cited 2 time in scopus
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tReasure: R-based GUI package analyzing tRNA expression profiles from small RNA sequencing data

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dc.contributor.authorLee, Jin-Ok-
dc.contributor.authorChu, Jiyon-
dc.contributor.authorJang, Gyuyeon-
dc.contributor.authorLee, Minho-
dc.contributor.authorChung, Yeun-Jun-
dc.date.accessioned2023-04-27T11:40:46Z-
dc.date.available2023-04-27T11:40:46Z-
dc.date.issued2022-05-
dc.identifier.issn1471-2105-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/3174-
dc.description.abstractBackground: Recent deep sequencing technologies have proven to be valuable resources to gain Insights into the expression profiles of diverse tRNAs. However, despite these technologies, the association of tRNAs with diverse diseases has not been explored in depth because analytical tools are lacking. Results: We developed a user-friendly tool, tRNA Expression Analysis Software Utilizing R for Easy use (tReasure), to analyze differentially expressed tRNAs (DEtRNAs) from deep sequencing data of small RNAs using R packages. tReasure can quantify individual mature tRNAs, isodecoders, and isoacceptors. By adopting stringent mapping strategies, tReasure supports the precise measurement of mature tRNA read counts. The whole analysis workflow for determining DEtRNAs (uploading FASTQ files, removing adapter sequences and poor-quality reads, mapping and quantifying tRNAs, filtering out low count tRNAs, determining DEtRNAs, and visualizing statistical analysis) can be performed with the tReasure package. Conclusions: tReasure is an open-source software available for download at https://treasure.pmrc.re.kr and will be indispensable for users who have little experience with command-line software to explore the biological implication of tRNA expression.-
dc.language영어-
dc.language.isoENG-
dc.publisherBioMed Central-
dc.titletReasure: R-based GUI package analyzing tRNA expression profiles from small RNA sequencing data-
dc.typeArticle-
dc.publisher.location영국-
dc.identifier.doi10.1186/s12859-022-04691-1-
dc.identifier.scopusid2-s2.0-85129334433-
dc.identifier.wosid000789809700003-
dc.identifier.bibliographicCitationBMC Bioinformatics, v.23, no.1-
dc.citation.titleBMC Bioinformatics-
dc.citation.volume23-
dc.citation.number1-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaBiochemistry & Molecular Biology-
dc.relation.journalResearchAreaBiotechnology & Applied Microbiology-
dc.relation.journalResearchAreaMathematical & Computational Biology-
dc.relation.journalWebOfScienceCategoryBiochemical Research Methods-
dc.relation.journalWebOfScienceCategoryBiotechnology & Applied Microbiology-
dc.relation.journalWebOfScienceCategoryMathematical & Computational Biology-
dc.subject.keywordPlusBIOCONDUCTOR PACKAGE-
dc.subject.keywordPlusGENE-EXPRESSION-
dc.subject.keywordPlusQUANTIFICATION-
dc.subject.keywordAuthortRNA expression analysis-
dc.subject.keywordAuthorSmall RNA sequence-
dc.subject.keywordAuthorGUI R packages-
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