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sRNAtoolbox: Dockerized Analysis of Small RNA Sequencing Data in Model and Non-model Species.
Gómez-Martín, Cristina; Aparicio-Puerta, Ernesto; Hackenberg, Michael.
Afiliação
  • Gómez-Martín C; Department of Pathology, Cancer Center Amsterdam, Amsterdam UMC, VU University, Amsterdam, The Netherlands.
  • Aparicio-Puerta E; Chair for Clinical Bioinformatics, Saarland University, Saarbrücken, Germany.
  • Hackenberg M; Genetics Department, Universidad de Granada, Granada, Spain. hackenberg@go.ugr.es.
Methods Mol Biol ; 2630: 179-213, 2023.
Article em En | MEDLINE | ID: mdl-36689184
ABSTRACT
The current versions of the microRNA databases MiRgeneDB, miRBase, and PmiREN contain annotations for a total of 358 different species. Public repositories, however, host small RNA sequencing data for over 800 species. This discrepancy implies that microRNA research is also very active in species that neither have an available high-quality genome assembly nor annotations for microRNAs or other types of noncoding genes. These cases are particularly challenging to analyze because reference sequences need to be collected from different sources and processed and formatted appropriately so that the dedicated small RNA analysis tools can make use of them. In this protocol we describe how small RNA sequencing data can be easily analyzed by means of a dockerized version of the well-established sRNAtoolbox/sRNAbench small RNA tools. We outline the analysis of two publicly available datasets to demonstrate basic aspects like the preparation of the local database, expression profiling, or differential expression analysis as well as more advanced features such as quantification of exogenous RNA content and data analysis in non-model species.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / MicroRNAs Idioma: En Revista: Methods Mol Biol Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / MicroRNAs Idioma: En Revista: Methods Mol Biol Ano de publicação: 2023 Tipo de documento: Article