Figure 3.

Schematic illustrating the principles of pseudotime cell ordering. (A) Cells display asynchronous activity within distinct functional states. Purifying cells with similar level of activity at distinct functional stages is difficult or impossible. (B) As cells move between functional states they undergo transcriptional re-configuration (some genes being silenced, others activated). Through machine learning techniques, the sequence of gene expression changes is determined and the trajectory that best fits the data is constructed. Based on the molecular profile of each human β-cell pseudotime analysis infers the order of gene activation events and assigns each cell a value of progress within the trajectory.