Guidelines for Genome-Scale Analysis of Biological Rhythms.

Détails

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Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_559D1C2C8AB7
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Guidelines for Genome-Scale Analysis of Biological Rhythms.
Périodique
Journal of Biological Rhythms
Auteur(s)
Hughes M.E., Abruzzi K.C., Allada R., Anafi R., Arpat A.B., Asher G., Baldi P., de Bekker C., Bell-Pedersen D., Blau J., Brown S., Ceriani M.F., Chen Z., Chiu J.C., Cox J., Crowell A.M., DeBruyne J.P., Dijk D.J., DiTacchio L., Doyle F.J., Duffield G.E., Dunlap J.C., Eckel-Mahan K., Esser K.A., FitzGerald G.A., Forger D.B., Francey L.J., Fu Y.H., Gachon F., Gatfield D., de Goede P., Golden S.S., Green C., Harer J., Harmer S., Haspel J., Hastings M.H., Herzel H., Herzog E.D., Hoffmann C., Hong C., Hughey J.J., Hurley J.M., de la Iglesia H.O., Johnson C., Kay S.A., Koike N., Kornacker K., Kramer A., Lamia K., Leise T., Lewis S.A., Li J., Li X., Liu A.C., Loros J.J., Martino T.A., Menet J.S., Merrow M., Millar A.J., Mockler T., Naef F., Nagoshi E., Nitabach M.N., Olmedo M., Nusinow D.A., Ptáček L.J., Rand D., Reddy A.B., Robles M.S., Roenneberg T., Rosbash M., Ruben M.D., Rund SSC, Sancar A., Sassone-Corsi P., Sehgal A., Sherrill-Mix S., Skene D.J., Storch K.F., Takahashi J.S., Ueda H.R., Wang H., Weitz C., Westermark P.O., Wijnen H., Xu Y., Wu G., Yoo S.H., Young M., Zhang E.E., Zielinski T., Hogenesch J.B.
ISSN
1552-4531 (Electronic)
ISSN-L
0748-7304
Statut éditorial
Publié
Date de publication
2017
Peer-reviewed
Oui
Volume
32
Numéro
5
Pages
380-393
Langue
anglais
Résumé
Genome 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.

Mots-clé
ChIP-seq, RNA-seq, biostatistics, circadian rhythms, computational biology, diurnal rhythms, functional genomics, guidelines, metabolomics, proteomics, systems biology
Pubmed
Web of science
Open Access
Oui
Création de la notice
05/11/2017 23:18
Dernière modification de la notice
20/08/2019 15:10
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