Oscope identifies oscillatory genes in unsynchronized single-cell RNA-seq experiments

Leng, Ning; Chu, Li‐Fang; Barry, Christopher; Li, Yuan; Choi, Jae Boong; Li, Xiaomao; Jiang, Peng; Stewart, Ron; Thomson, James A.; Kendziorski, Christina

doi:10.1038/nmeth.3549

Cited by 175 publications

(227 citation statements)

References 20 publications

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“…As a result, circadian variation could be a confounding factor in many analyses of genome-wide gene expression. In the future, it may be possible to detect, correct for, and learn from unannotated circadian variation in publicly available data, perhaps using methods developed primarily for the cell cycle (Buettner et al, 2015; Leng et al, 2015). …”

Section: Discussionmentioning

confidence: 99%

Differential Phasing between Circadian Clocks in the Brain and Peripheral Organs in Humans

Hughey

Butte

2016

J Biol Rhythms

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The daily timing of mammalian physiology is coordinated by circadian clocks throughout the body. Although measurements of clock gene expression indicate that these clocks in mice are normally in phase with each other, the situation in humans remains unclear. We used publicly available data from five studies, comprising over 1000 samples, to compare the phasing of circadian gene expression in human brain and human blood. Surprisingly, after controlling for age, clock gene expression in brain was phase-delayed by ~8.5 h relative to that of blood. We then examined clock gene expression in two additional human organs and in organs from nine other mammalian species, as well as in the suprachiasmatic nucleus (SCN). In most tissues outside the SCN, the expression of clock gene orthologs showed a phase difference of ~12 h between diurnal and nocturnal species. The exception to this pattern was human brain, whose phasing resembled that of the SCN. Our results highlight the value of a multi-tissue, multi-species meta-analysis, and have implications for our understanding of the human circadian system.

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Section: Discussionmentioning

confidence: 99%

Differential Phasing between Circadian Clocks in the Brain and Peripheral Organs in Humans

Hughey

Butte

2016

J Biol Rhythms

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“…All cell culture and scRNA-seq experiments were conducted as described previously [30, 48]. Briefly, undifferentiated H1 and H9 hESCs were routinely maintained at the undifferentiated state in E8 medium on Matrigel (BD Bioscience) coated tissue culture plates with daily medium feeding [49].…”

Section: Methodsmentioning

confidence: 99%

“…Some cells were removed due to cell death or doublet cell capture, indicated by a post cell capture image analysis as well as a very low percentage of mapped reads. For more details on read mapping and quality control, see [30, 48]. DESeq normalization [53] was carried out using the MedianNorm function in the EBSeq R package [54] to obtain library sizes.…”

Section: Methodsmentioning

confidence: 99%

A statistical approach for identifying differential distributions in single-cell RNA-seq experiments

et al. 2016

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The ability to quantify cellular heterogeneity is a major advantage of single-cell technologies. However, statistical methods often treat cellular heterogeneity as a nuisance. We present a novel method to characterize differences in expression in the presence of distinct expression states within and among biological conditions. We demonstrate that this framework can detect differential expression patterns under a wide range of settings. Compared to existing approaches, this method has higher power to detect subtle differences in gene expression distributions that are more complex than a mean shift, and can characterize those differences. The freely available R package scDD implements the approach.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-1077-y) contains supplementary material, which is available to authorized users.

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“…Within the framework of linear regression, the Chow test can be used for two conditions and a model selection approach can be used for three or more conditions (Chow 1960;Atger et al 2015). Finally, we note that, with some exceptions (Leng et al 2015;Hughey et al 2016), the problem has been tackled gene by gene. Multivariate approaches that leverage rhythmic or mean signals across multiple genes may provide additional insights toward the regulation of gene modules across conditions.…”

Section: Statistical Methods For the Identification Of Periodic Gene mentioning

confidence: 99%

Systems Chronobiology: Global Analysis of Gene Regulation in a 24-Hour Periodic World

Yeung

Naef

2016

Cold Spring Harb Perspect Biol

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Mammals have evolved an internal timing system, the circadian clock, which synchronizes physiology and behavior to the daily light and dark cycles of the Earth. The master clock, located in the suprachiasmatic nucleus (SCN) of the brain, takes fluctuating light input from the retina and synchronizes other tissues to the same internal rhythm. The molecular clocks that drive these circadian rhythms are ticking in nearly all cells in the body. Efforts in systems chronobiology are now being directed at understanding, on a comprehensive scale, how the circadian clock controls different layers of gene regulation to provide robust timing cues at the cellular and tissue level. In this review, we introduce some basic concepts underlying periodicity of gene regulation, and then highlight recent genome-wide investigations on the propagation of rhythms across multiple regulatory layers in mammals, all the way from chromatin conformation to protein accumulation.

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Oscope identifies oscillatory genes in unsynchronized single-cell RNA-seq experiments

Cited by 175 publications

References 20 publications

Differential Phasing between Circadian Clocks in the Brain and Peripheral Organs in Humans

Differential Phasing between Circadian Clocks in the Brain and Peripheral Organs in Humans

A statistical approach for identifying differential distributions in single-cell RNA-seq experiments

Systems Chronobiology: Global Analysis of Gene Regulation in a 24-Hour Periodic World

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