cycleX: multi-dimensional pseudotime reveals cell cycle and differentiation relationship of dendritic cell progenitors

Abstract Advances in single-cell RNA-sequencing have helped reveal the previously underappreciated level of cellular heterogeneity present during cellular differentiation. A static snapshot of single-cell transcriptomes provides a good representation of the various stages of differentiation as differentiation is rarely synchronized between cells. Data from numerous single-cell analyses has suggested that cellular differentiation and development can be conceptualized as continuous processes. Consequently, computational algorithms have been developed to infer pseudotimes and re-ordered cells along developmental trajectories. However, existing pseudotime inference methods generate one-dimensional pseudotime in an unsupervised manner, which is inadequate to elucidate the effects of individual biological processes such as cell cycle and differentiation and the links between them. Here we present a method called cycleX which infers multi-dimensional pseudotimes to reveal putative relationship between cell cycle and differentiation during dendritic cell development. cycleX can be also applied to generate multi-dimensional pseudotime for the relationship among cell cycle, differentiation, trafficking, activation, metabolism and etc.