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.

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High-dimensional single cell profiling coupled with computational modeling holds the potential to elucidate developmental sequences and define genetic programs directing cell lineages. Here we introduce an approach to the discovery and exploration of developmental pathways based on the concept of "trajectory space", in which cells are defined not by their phenotype but by their distance along nearest neighbor trajectories to every other cell in a population. We implement a tSpace algorithm, and show that multidimensional profiling of cells in trajectory space allows unsupervised reconstruction of complex developmental sequences. tSpace is robust, scalable, and implements a global approach to trajectory analysis that attempts to preserve both local and distant relationships in developmental pathways. Applied to high dimensional flow and mass cytometry data, the method faithfully reconstructs known branching pathways of thymic T cell development, and reveals patterns of tonsillar B cell development and of B cell migration. Applied to single cell transcriptomic data, the method unfolds the complex developmental sequences and genetic programs leading from intestinal stem cells to specialized epithelial phenotypes. Profiling of complex populations in high-dimensional trajectory space should prove useful for hypothesis generation in developing cell systems.