CellRank for directed single-cell fate mapping.

ABSTRACT: Computational trajectory inference enables the reconstruction of cell state dynamics from single-cell RNA sequencing experiments. However, trajectory inference requires that the direction of a biological process is known, largely limiting its application to differentiating systems in normal development. Here, we present CellRank ( https://cellrank.org ) for single-cell fate mapping in diverse scenarios, including regeneration, reprogramming and disease, for which direction is unknown. Our approach combines the robustness of trajectory inference with directional information from RNA velocity, taking into account the gradual and stochastic nature of cellular fate decisions, as well as uncertainty in velocity vectors. On pancreas development data, CellRank automatically detects initial, inter

SUBMITTER: Lange M 

PROVIDER: S-EPMC8828480 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature