High-dimensional single cell profiling coupled with computational modeling is emerging as a powerful tool to elucidate developmental programs directing cell lineages. We introduce tSpace, an algorithm based on the concept of “trajectory space”, in which cells are defined by their distance along nearest neighbor pathways to every other cell in a population. Graphical mapping of cells in trajectory space allows unsupervised reconstruction and exploration of complex developmental sequences. Applied to flow and mass cytometry data, the method faithfully reconstructs thymic T cell development and reveals development and trafficking regulation of tonsillar B cells. Applied to the single cell transcriptome of mouse intestine and C. elegans, the method recapitulates development from intestinal stem cells to specialized epithelial phenotypes more faithfully than existing algorithms and orders C. elegans cells concordantly to the associated embryonic time. tSpace profiling of complex populations is well suited for hypothesis generation in developing cell systems.

高维单细胞分析与计算模型相结合正在成为阐明指导细胞谱系发育程序的强大工具。我们引入了 tSpace，这是一种基于“轨迹空间”概念的算法，其中细胞由它们沿着最近邻路径到群体中每个其他细胞的距离来定义。轨迹空间中细胞的图形映射允许对复杂的发育序列进行无监督重建和探索。应用于流式和质谱细胞术数据，该方法忠实地重建了胸腺 T 细胞的发育，并揭示了扁桃体 B 细胞的发育和运输调节。应用于小鼠肠道和秀丽隐杆线虫的单细胞转录组, 该方法比现有算法更忠实地概括了从肠道干细胞到专门上皮表型的发育，并根据相关的胚胎时间对线虫细胞进行排序。复杂群体的 tSpace 分析非常适合在开发细胞系统中生成假设。