从单细胞基因组学数据的轨迹推断,使用过程时间模型
Meichen Fang1, Gennady Gorin1,2, Lior Pachter1,3
1Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California, United States of America.
PLoS computational biology
|January 21, 2025
概括
我们介绍了Chronocell,这是一种从单细胞转录组数据推断生物过程时间的新方法. 这种方法提供了一个生物物理上有意义的替代 pseudotime,改善动态洞察细胞过程.
科学领域:
- 单细胞生物学 单细胞生物学
- 计算生物学是一种计算生物学.
- 系统生物学 系统生物学
背景情况:
- 单细胞转录学捕捉了细胞状态,但使用"伪时间"对细胞进行排序缺乏物理意义.
- 现有的方法难以处理离散的细胞群和连续的细胞状态转换.
研究的目的:
- 从单细胞数据中推断"处理时间"的原则建模方法.
- 介绍Chronocell,一个用于生物物理轨迹推断的计算工具.
- 提供一种将轨迹推断和集群结合的方法.
主要方法:
- 使用生物物理模型制定细胞状态转换.
- 推断隐性变量代表生物物理过程中的时间.
- 实现可识别参数推断的Chronocell模型.
主要成果:
- 时代细胞成功地在连续和离散细胞状态之间进行插曲.
- 对各种数据集的分析揭示了在过程时间的不同细胞分布.
- 降解率的参数估计与代谢标记数据保持一致.
结论:
- 克罗诺细胞为分析单细胞动态提供了一个生物物理上有意义的框架.
- 该方法有助于评估数据集的适用性和理解生物时间.
- 准确的过程时间推断取决于数据集质量和模型评估.
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