Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, USA.
Division of Biology and Biological Engineering & Department of Computing and Mathematical Sciences, California Institute of Technology, Pasadena, USA.
Genome Biol. 2020 Feb 18;21(1):39. doi: 10.1186/s13059-020-1945-3.
The simultaneous quantification of protein and RNA makes possible the inference of past, present, and future cell states from single experimental snapshots. To enable such temporal analysis from multimodal single-cell experiments, we introduce an extension of the RNA velocity method that leverages estimates of unprocessed transcript and protein abundances to extrapolate cell states. We apply the model to six datasets and demonstrate consistency among cell landscapes and phase portraits. The analysis software is available as the protaccel Python package.
同时定量蛋白质和 RNA 使得从单个实验快照推断过去、现在和未来的细胞状态成为可能。为了能够从多模态单细胞实验中进行这种时间分析,我们引入了 RNA 速度方法的扩展,该方法利用未处理的转录本和蛋白质丰度的估计值来推断细胞状态。我们将该模型应用于六个数据集,并证明了细胞图谱和相图之间的一致性。分析软件作为 protaccel Python 包提供。