Kostiou Vasiliki, Zhang Huairen, Hall Michael W J, Jones Philip H, Hall Benjamin A
Department of Medical Physics and Biomedical Engineering, UCL, Gower Street, London WC1E 6BT, UK.
MRC Cancer Unit, University of Cambridge, Hutchison-MRC Research Centre, Box 197, Cambridge Biomedical Campus, Cambridge CB2 0XZ, UK.
R Soc Open Sci. 2021 May 5;8(5):202231. doi: 10.1098/rsos.202231.
A single population of progenitor cells maintains many epithelial tissues. Transgenic mouse cell tracking has frequently been used to study the growth dynamics of competing clones in these tissues. A mathematical model (the 'single-progenitor model') has been argued to reproduce the observed progenitor dynamics accurately. This requires three parameters to describe the growth dynamics observed in transgenic mouse cell tracking-a division rate, a stratification rate and the probability of dividing symmetrically. Deriving these parameters is a time intensive and complex process. We compare the alternative strategies for analysing this source of experimental data, identifying an approximate Bayesian computation-based approach as the best in terms of efficiency and appropriate error estimation. We support our findings by explicitly modelling biological variation and consider the impact of different sampling regimes. All tested solutions are made available to allow new datasets to be analysed following our workflows. Based on our findings, we make recommendations for future experimental design.
一群祖细胞维持着许多上皮组织。转基因小鼠细胞追踪经常被用于研究这些组织中竞争克隆的生长动态。有人认为一个数学模型（“单祖细胞模型”）能够准确再现观察到的祖细胞动态。这需要三个参数来描述在转基因小鼠细胞追踪中观察到的生长动态——分裂率、分层率和对称分裂的概率。推导这些参数是一个耗时且复杂的过程。我们比较了分析此类实验数据的不同策略，确定基于近似贝叶斯计算的方法在效率和适当的误差估计方面是最佳的。我们通过明确模拟生物变异来支持我们的发现，并考虑不同采样方案的影响。所有经过测试的解决方案均可获取，以便按照我们的工作流程分析新的数据集。基于我们的发现，我们对未来的实验设计提出建议。
