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Simulation-based inference of differentiation trajectories from RNA velocity fields.

ABSTRACT: We report Cytopath, a method for trajectory inference that takes advantage of transcriptional activity information from the RNA velocity of single cells to perform trajectory inference. Cytopath performs this task by defining a Markov chain model, simulating an ensemble of possible differentiation trajectories, and constructing a consensus trajectory. We show that Cytopath can recapitulate the topological and molecular characteristics of the differentiation process under study. In our analysis, we include differentiation trajectories with varying bifurcated, circular, convergent, and mixed topologies studied in single-snapshot as well as time-series single-cell RNA sequencing experiments. We demonstrate the capability to reconstruct differentiation trajectories, assess the association of RNA velocity-based pseudotime with actually elapsed process time, and identify drawbacks in current state-of-the art trajectory inference approaches.

SUBMITTER: Gupta R

PROVIDER: S-EPMC9795361 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Simulation-based inference of differentiation trajectories from RNA velocity fields.

Gupta Revant R Cerletti Dario D Gut Gilles G Oxenius Annette A Claassen Manfred M

Cell reports methods 20221219 12

We report Cytopath, a method for trajectory inference that takes advantage of transcriptional activity information from the RNA velocity of single cells to perform trajectory inference. Cytopath performs this task by defining a Markov chain model, simulating an ensemble of possible differentiation trajectories, and constructing a consensus trajectory. We show that Cytopath can recapitulate the topological and molecular characteristics of the differentiation process under study. In our analysis, ...[more]

PMID: 36590685

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