流式细胞术的分支过程模型和细胞同步性实验中的出芽指数测量
A branching process model for flow cytometry and budding index measurements in cell synchrony experiments
摘要：
我们提出了一个灵活的分支过程模型，用于研究重要的细胞过程的同步/时间序列实验中的细胞群体动力学。它的提法是建设性的，其基础是对人口中独特的群体随着时间的推移而产生和演变的核算，使其能够以封闭的形式编写。该模型可以将效应归因于群体的子集，提供了使用历史上应用于这些群体的模型所不具备的灵活性。它提供了一个工具，在计算机同步的人口，并可用于去卷积人口水平的实验测量，如时间表达谱。它还允许直接比较从多个实验进行的测定测量。该模型可以适合发芽指数或DNA含量测量，或两者兼而有之，并且很容易适应新形式的数据。使用DNA含量数据的能力使得该模型适用于几乎任何生物。我们描述了该模型，并说明其实用性和灵活性，在酵母酿酒酵母细胞周期进程的研究。
英文摘要：
We present a flexible branching process model for cell population dynamics in synchrony/time-series experiments used to study important cellular processes. Its formulation is constructive, based on an accounting of the unique cohorts in the population as they arise and evolve over time, allowing it to be written in closed form. The model can attribute effects to subsets of the population, providing flexibility not available using the models historically applied to these populations. It provides a tool for in silico synchronization of the population and can be used to deconvolve population-level experimental measurements, such as temporal expression profiles. It also allows for the direct comparison of assay measurements made from multiple experiments. The model can be fit either to budding index or DNA content measurements, or both, and is easily adaptable to new forms of data. The ability to use DNA content data makes the model applicable to almost any organism. We describe the model and illustrate its utility and flexibility in a study of cell cycle progression in the yeast Saccharomyces cerevisiae.
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