Multivariate stochastic modeling for transcriptional dynamics with cell-specific latent time using SDEvelo.

ABSTRACT: Recently, RNA velocity has driven a paradigmatic change in single-cell RNA sequencing (scRNA-seq) studies, allowing the reconstruction and prediction of directed trajectories in cell differentiation and state transitions. Most existing methods of dynamic modeling use ordinary differential equations (ODE) for individual genes without applying multivariate approaches. However, this modeling strategy inadequately captures the intrinsically stochastic nature of transcriptional dynamics governed by a cell-specific latent time across multiple genes, potentially leading to erroneous results. Here, we present SDEvelo, a generative approach to inferring RNA velocity by modeling the dynamics of unspliced and spliced RNAs via multivariate stochastic differential equations (SDE). Uniquely, SDEvelo exp

SUBMITTER: Liao X 

PROVIDER: S-EPMC11685993 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature