| Summary | Oscillatory gene expression is fundamental to mammalian development, but technologies to monitor expression oscillations are limited. We have developed a statistical approach called Oscope to identify and characterize the transcriptional dynamics of oscillating genes in single-cell RNA-seq data from an unsynchronized cell population. Applications to a number of data sets, include a single-cell RNA-seq data set of human embroyonic stem cells (hESCs), demonstrate advantages of the approach and also identify a potential artifact in the Fluidigm C1 platform. |
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