DNA methylation levels are known to vary over time, and modelling these trajectories is crucial for our understanding of the biological relevance of these changes over time. However, due to the computational cost of fitting multilevel models across the epigenome, most trajectory modelling efforts to date have focused on a subset of CpG sites identified through epigenome-wide association studies (EWAS) at individual time-points.

中文翻译：

---

用于模拟表观遗传轨迹的纵向分析策略

众所周知，DNA 甲基化水平会随时间而变化，对这些轨迹进行建模对于我们理解这些变化随时间变化的生物学相关性至关重要。然而，由于跨表观基因组拟合多级模型的计算成本，迄今为止，大多数轨迹建模工作都集中在通过单个时间点的表观基因组关联研究 (EWAS) 确定的 CpG 位点子集上。