JTK_CYCLE: an efficient non-parametric algorithm for detecting rhythmic components in genome-scale datasets

By Michael Hughes, John B. Hogenesch, Karl Kornacker. Journal of Biological Rhythms, 2010

1,037 citations recorded by the source corpus.

Circadian rhythms are oscillations of physiology, behavior, and metabolism that have period lengths near 24 hours. In several model organisms and humans, circadian clock genes have been characterized and found to be transcription factors. Because of this, researchers have used microarrays to characterize global regulation of gene expression and algorithmic approaches to detect cycling. This article presents a new algorithm, JTK_CYCLE, designed to efficiently identify and characterize cycling variables in large data sets. Compared with COSOPT and the Fisher’s G test, two commonly used methods for detecting cycling transcripts, JTK_CYCLE distinguishes between rhythmic and nonrhythmic transcripts more reliably and efficiently. JTK_CYCLE’s increased resistance to outliers results in considerably greater sensitivity and specificity. Moreover, JTK_CYCLE accurately measures the period, phase, and amplitude of cycling transcripts, facilitating downstream analyses. Finally, JTK_CYCLE is several orders of magnitude faster than COSOPT, making it ideal for large-scale data sets. JTK_CYCLE was used to analyze legacy data sets including NIH3T3 cells, which have comparatively low amplitude oscillations. JTK_CYCLE’s improved power led to the identification of a novel cluster of RNA-interacting genes whose abundance is under clear circadian regulation. These data suggest that JTK_CYCLE is an ideal tool for identifying and characterizing oscillations in genome-scale data sets.

Subfields: Aging, Endocrine and Autonomic Systems, Physiology

View Paper: https://www.semanticscholar.org/paper/ae44a50149ebe90e0e364fef47fbf9c0b6e63eea

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Citations in the corpus

Time-restricted feeding is a preventative and therapeutic intervention against diverse nutritional challenges (2014, background): “24 hr rhythmic metabolites (Hughes et al., 2010) (period [20–28 hr], adjusted p < 0.”
CircaDB: a database of mammalian circadian gene expression profiles (2012, methodology): “Data from each study were re-analysed using three circadian rhythm detection algorithms: JTK_CYCLE, Lombe Scargle, de Lichtenberg (23,27,28).”
Reprogramming of the Circadian Clock by Nutritional Challenge (2013, positive): “For analysis of rhythmic metabolites and transcripts, the non-parametric test, JTK_CYCLE, was used incorporating a window of 20–28 hours for the determination of circadian periodicity as described in (EckelMahan et al., 2012; Hughes et al., 2010) (Tables S2 and S3).”
MetaCycle: an integrated R package to evaluate periodicity in large scale data (2016, background): “Using the same input file, MetaCycle::meta2d implements ARSER (ARS), JTK_CYCLE (JTK), and Lomb-Scargle (LS; Glynn, et al., 2006), from dramatically different disciplines, computer science, statistics, and physics, respectively.”
Diet and Feeding Pattern Affect the Diurnal Dynamics of the Gut Microbiome (2014, neutral): “In order to determine whether a particular phylogenetic group was cyclical, we used JTK analysis, a nonparametric test that detects cycling elements (Hughes et al., 2010).”
Transkingdom control of microbiota diurnal oscillations promotes metabolic homeostasis. (2014, methodology): “For the analysis of rhythmic oscillations and their amplitudes, the nonparametric test JTK_cycle was used (Hughes et al., 2010), incorporating a window of 18–24 hr for the determination of circadian periodicity.”
A circadian gene expression atlas in mammals: Implications for biology and medicine (2014, methodology): “The JTK_CYCLE (11) package for R was used, with”