Guidelines for genome-scale analysis of biological rhythmsMore about Open Access at the Crick
Authors listMichael E Hughes Katherine C Abruzzi Ravi Allada Ron Anafi Alaaddin Bulak Arpat Gad Asher Pierre Baldi Charissa de Bekker Deborah Bell-Pedersen Justin Blau Steve Brown M Fernanda Ceriani Zheng Chen Joanna C Chiu Juergen Cox Alexander M Crowell Jason P DeBruyne Derk-Jan Dijk Luciano DiTacchio Francis J Doyle Giles E Duffield Jay C Dunlap Kristin Eckel-Mahan Karyn A Esser Garret A FitzGerald Daniel B Forger Lauren J Francey Ying-Hui Fu Frédéric Gachon David Gatfield Paul de Goede Susan S Golden Carla Green John Harer Stacey Harmer Jeff Haspel Michael H Hastings Hanspeter Herzel Erik D Herzog Christy Hoffmann Christian Hong Jacob J Hughey Jennifer M Hurley Horacio O de la Iglesia Carl Johnson Steve A Kay Nobuya Koike Karl Kornacker Achim Kramer Katja Lamia Tanya Leise Scott A Lewis Jiajia Li Xiaodong Li Andrew C Liu Jennifer J Loros Tami A Martino Jerome S Menet Martha Merrow Andrew J Millar Todd Mockler Felix Naef Emi Nagoshi Michael N Nitabach Maria Olmedo Dmitri A Nusinow Louis J Ptáček David Rand Akhilesh B Reddy Maria S Robles Till Roenneberg Michael Rosbash Marc D Ruben Samuel SC Rund Aziz Sancar Paolo Sassone-Corsi Amita Sehgal Scott Sherrill-Mix Debra J Skene Kai-Florian Storch Joseph S Takahashi Hiroki R Ueda Han Wang Charles Weitz Pål O Westermark Herman Wijnen Ying Xu Gang Wu Seung-Hee Yoo Michael Young Eric Erquan Zhang Tomasz Zielinski John B Hogenesch
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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.
Journal Journal of Biological Rhythms
Issue number 5