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Induced pluripotent stem cells (iPSCs) provide a great model to study theprocess of reprogramming and differentiation of stem cells. Single-cell RNAsequencing (scRNA-seq) enables us to investigate the reprogramming process atsingle-cell level. Here, we introduce single-cell entropy (scEntropy) as amacroscopic variable to quantify the cellular transcriptome from scRNA-seq dataduring reprogramming and differentiation of iPSCs. scEntropy measures therelative order parameter of genomic transcriptions at single cell level duringthe cell fate change process, which shows increasing during differentiation,and decreasing upon reprogramming. Moreover, based on the scEntropy dynamics,we construct a phenomenological stochastic differential equation model and thecorresponding Fokker-Plank equation for cell state transitions during iPSCdifferentiation, which provide insights to infer cell fates changes and stemcell differentiation. This study is the first to introduce the novel concept ofscEntropy to the biological process of iPSC, and suggests that the scEntropycan provide a suitable quantify to describe cell fate transition indifferentiation and reprogramming of stem cells.

Using single-cell entropy to describe the dynamics of reprogramming and differentiation of induced pluripotent stem cells