Simultaneous profiling of single-cell gene expression and lineage history holds enormous potential for studying cellular decision-making. Recent computational approaches combine both modalities into cellular trajectories; however, they cannot make use of all available lineage information in destructive time-series experiments. Here, we present moslin, a Gromov-Wasserstein-based model to couple cellular profiles across time points based on lineage and gene expression information. We validate our approach in simulations and demonstrate on Caenorhabditis elegans embryonic development how moslin predicts fate probabilities and putative decision driver genes. Finally, we use moslin to delineate lineage relationships among transiently activated fibroblast states during zebrafish heart regeneration.

中文翻译：

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使用 moslin 跨时间点绘制谱系追踪细胞


同时分析单细胞基因表达和谱系历史对于研究细胞决策具有巨大潜力。最近的计算方法将这两种模式结合到细胞轨迹中;但是，它们无法在破坏性时间序列实验中使用所有可用的世系信息。在这里，我们介绍了 moslin，这是一种基于 Gromov-Wasserstein 的模型，用于根据谱系和基因表达信息耦合跨时间点的细胞谱。我们在模拟中验证了我们的方法，并在秀丽隐杆线虫胚胎发育上展示了 moslin 如何预测命运概率和推定的决策驱动基因。最后，我们使用 moslin 来描绘斑马鱼心脏再生过程中瞬时激活的成纤维细胞状态之间的谱系关系。