Gutenberg Open Science: GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data

Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-7302

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DC Field	Value	Language
dc.contributor.author	Marini, Federico	-
dc.contributor.author	Ludt, Annekathrin	-
dc.contributor.author	Linke, Jan	-
dc.contributor.author	Strauch, Konstantin	-
dc.date.accessioned	2022-07-05T07:57:25Z	-
dc.date.available	2022-07-05T07:57:25Z	-
dc.date.issued	2021	-
dc.identifier.uri	https://openscience.ub.uni-mainz.de/handle/20.500.12030/7316	-
dc.description.abstract	BACKGROUND The interpretation of results from transcriptome profiling experiments via RNA sequencing (RNA-seq) can be a complex task, where the essential information is distributed among different tabular and list formats—normalized expression values, results from differential expression analysis, and results from functional enrichment analyses. A number of tools and databases are widely used for the purpose of identification of relevant functional patterns, yet often their contextualization within the data and results at hand is not straightforward, especially if these analytic components are not combined together efficiently. RESULTS We developed the GeneTonic software package, which serves as a comprehensive toolkit for streamlining the interpretation of functional enrichment analyses, by fully leveraging the information of expression values in a differential expression context. GeneTonic is implemented in R and Shiny, leveraging packages that enable HTML-based interactive visualizations for executing drilldown tasks seamlessly, viewing the data at a level of increased detail. GeneTonic is integrated with the core classes of existing Bioconductor workflows, and can accept the output of many widely used tools for pathway analysis, making this approach applicable to a wide range of use cases. Users can effectively navigate interlinked components (otherwise available as flat text or spreadsheet tables), bookmark features of interest during the exploration sessions, and obtain at the end a tailored HTML report, thus combining the benefits of both interactivity and reproducibility. CONCLUSION GeneTonic is distributed as an R package in the Bioconductor project (https://bioconductor.org/packages/GeneTonic/) under the MIT license. Offering both bird’s-eye views of the components of transcriptome data analysis and the detailed inspection of single genes, individual signatures, and their relationships, GeneTonic aims at simplifying the process of interpretation of complex and compelling RNA-seq datasets for many researchers with different expertise profiles.	en_GB
dc.language.iso	eng	de
dc.rights	CC BY	*
dc.rights.uri	https://creativecommons.org/licenses/by/4.0/	*
dc.subject.ddc	610 Medizin	de_DE
dc.subject.ddc	610 Medical sciences	en_GB
dc.title	GeneTonic: an R/Bioconductor package for streamlining the interpretation of RNA-seq data	en_GB
dc.type	Zeitschriftenaufsatz	de
dc.identifier.doi	http://doi.org/10.25358/openscience-7302	-
jgu.type.dinitype	article	en_GB
jgu.type.version	Published version	de
jgu.type.resource	Text	de
jgu.organisation.department	FB 04 Medizin	de
jgu.organisation.number	2700	-
jgu.organisation.name	Johannes Gutenberg-Universität Mainz	-
jgu.rights.accessrights	openAccess	-
jgu.journal.title	BMC bioinformatics	de
jgu.journal.volume	22	de
jgu.pages.alternative	610	de
jgu.publisher.year	2021	-
jgu.publisher.name	BioMed Central	de
jgu.publisher.place	London	de
jgu.publisher.issn	1471-2105	de
jgu.organisation.place	Mainz	-
jgu.subject.ddccode	610	de
jgu.publisher.doi	10.1186/s12859-021-04461-5	de
jgu.organisation.ror	https://ror.org/023b0x485	-
Appears in collections:	JGU-Publikationen

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