Please use this identifier to cite or link to this item: http://doi.org/10.25358/openscience-5739
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMarini, Federico-
dc.contributor.authorLinke, Jan-
dc.contributor.authorBinder, Harald-
dc.date.accessioned2021-04-21T11:01:55Z-
dc.date.available2021-04-21T11:01:55Z-
dc.date.issued2020-
dc.identifier.urihttps://openscience.ub.uni-mainz.de/handle/20.500.12030/5748-
dc.description.abstractBACKGROUND RNA sequencing (RNA-seq) is an ever increasingly popular tool for transcriptome profiling. A key point to make the best use of the available data is to provide software tools that are easy to use but still provide flexibility and transparency in the adopted methods. Despite the availability of many packages focused on detecting differential expression, a method to streamline this type of bioinformatics analysis in a comprehensive, accessible, and reproducible way is lacking. RESULTS We developed the ideal software package, which serves as a web application for interactive and reproducible RNA-seq analysis, while producing a wealth of visualizations to facilitate data interpretation. ideal is implemented in R using the Shiny framework, and is fully integrated with the existing core structures of the Bioconductor project. Users can perform the essential steps of the differential expression analysis workflow in an assisted way, and generate a broad spectrum of publication-ready outputs, including diagnostic and summary visualizations in each module, all the way down to functional analysis. ideal also offers the possibility to seamlessly generate a full HTML report for storing and sharing results together with code for reproducibility. CONCLUSION ideal is distributed as an R package in the Bioconductor project (http://bioconductor.org/packages/ideal/), and provides a solution for performing interactive and reproducible analyses of summarized RNA-seq expression data, empowering researchers with many different profiles (life scientists, clinicians, but also experienced bioinformaticians) to make the ideal use of the data at hand.en_GB
dc.language.isoengde
dc.rightsCC BY*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subject.ddc610 Medizinde_DE
dc.subject.ddc610 Medical sciencesen_GB
dc.titleideal: an R/Bioconductor package for interactive diferential expression analysisen_GB
dc.typeZeitschriftenaufsatzde
dc.identifier.doihttp://doi.org/10.25358/openscience-5739-
jgu.type.dinitypearticleen_GB
jgu.type.versionPublished versionde
jgu.type.resourceTextde
jgu.organisation.departmentFB 04 Medizinde
jgu.organisation.number2700-
jgu.organisation.nameJohannes Gutenberg-Universität Mainz-
jgu.rights.accessrightsopenAccess-
jgu.journal.titleBMC bioinformaticsde
jgu.journal.volume21de
jgu.pages.alternative565de
jgu.publisher.year2020-
jgu.publisher.nameBioMed Centralde
jgu.publisher.placeLondonde
jgu.publisher.urihttps://doi.org/10.1186/s12859-020-03819-5de
jgu.publisher.issn1471-2105de
jgu.organisation.placeMainz-
jgu.subject.ddccode610de
jgu.publisher.doi10.1186/s12859-020-03819-5
jgu.organisation.rorhttps://ror.org/023b0x485
Appears in collections:JGU-Publikationen

Files in This Item:
  File Description SizeFormat
Thumbnail
marini_federico-ideal__an_r/bi-20210414122937882.pdf1.42 MBAdobe PDFView/Open