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dc.creatorHughes, Michael E.es
dc.creatorAbruzzi, Katharine Comptones
dc.creatorAllada, Ravies
dc.creatorAnafi, Ron C.es
dc.creatorArpat, Alaaddin Bulakes
dc.creatorAsher, Gades
dc.creatorOlmedo López, Maríaes
dc.creatorGachon, Frédérices
dc.date.accessioned2020-10-27T16:14:11Z
dc.date.available2020-10-27T16:14:11Z
dc.date.issued2017
dc.identifier.citationHughes, M.E., Abruzzi, K.C., Allada, R., Anafi, R.C., Arpat, A.B., Asher, G.,...,Gachon, F. (2017). Guidelines for Genome-Scale Analysis of Biological Rhythms. Journal of Biological Rhythms, 32 (5), 380-393.
dc.identifier.issn0748-7304es
dc.identifier.issn1552-4531es
dc.identifier.urihttps://hdl.handle.net/11441/102284
dc.description.abstractGenome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding “big data” that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.es
dc.formatapplication/pdfes
dc.format.extent14 p.es
dc.language.isoenges
dc.publisherSAGEes
dc.relation.ispartofJournal of Biological Rhythms, 32 (5), 380-393.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectBiostatisticses
dc.subjectChIP-seqes
dc.subjectCircadian rhythmses
dc.subjectComputational biologyes
dc.subjectDiurnal rhythmses
dc.subjectFunctional genomicses
dc.subjectGuidelineses
dc.subjectMetabolomicses
dc.subjectProteomicses
dc.subjectRNA-seqes
dc.subjectSystems biologyes
dc.titleGuidelines for Genome-Scale Analysis of Biological Rhythmses
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/publishedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Genéticaes
dc.relation.publisherversionhttps://doi.org/10.1177%2F0748730417728663es
dc.identifier.doi10.1177%2F0748730417728663es
dc.journaltitleJournal of Biological Rhythmses
dc.publication.volumen32es
dc.publication.issue5es
dc.publication.initialPage380es
dc.publication.endPage393es

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