Title: Kinetic foundation of the zero-inflated negative binomial model for single-cell RNA sequencing data Show Chinese title

Title: 零膨胀负二项分布模型的运动学基础用于单细胞RNA测序数据

Abstract: Single-cell RNA sequencing data have complex features such as dropout events, over-dispersion, and high-magnitude outliers, resulting in complicated probability distributions of mRNA abundances that are statistically characterized in terms of a zero-inflated negative binomial (ZINB) model. Here we provide a mesoscopic kinetic foundation of the widely used ZINB model based on the biochemical reaction kinetics underlying transcription. Using multiscale modeling and simplification techniques, we show that the ZINB distribution of mRNA abundance and the phenomenon of transcriptional bursting naturally emerge from a three-state stochastic transcription model. We further reveal a nontrivial quantitative relation between dropout events and transcriptional bursting, which provides novel insights into how and to what extent the burst size and burst frequency could reduce the dropout rate. Three different biophysical origins of over-dispersion are also clarified at the single-cell level. Show Chinese abstract

Abstract: 单细胞RNA测序数据具有复杂的特征，如缺失事件、过度离散和高幅度异常值，导致mRNA丰度的概率分布复杂，这些分布在统计上通过零膨胀负二项（ZINB）模型进行表征。 在这里，我们基于转录的生化反应动力学，提供了广泛使用的ZINB模型的介观动力学基础。 使用多尺度建模和简化技术，我们表明mRNA丰度的ZINB分布和转录爆发现象自然地来自于一个三状态随机转录模型。 我们进一步揭示了缺失事件与转录爆发之间的非平凡定量关系，这为爆发大小和爆发频率如何以及在多大程度上减少缺失率提供了新的见解。 三种不同的过度离散的生物物理起源也在单细胞水平上得到了澄清。