Gene trajectory inference for single-cell data by optimal transport metrics.

ABSTRACT: Single-cell RNA sequencing has been widely used to investigate cell state transitions and gene dynamics of biological processes. Current strategies to infer the sequential dynamics of genes in a process typically rely on constructing cell pseudotime through cell trajectory inference. However, the presence of concurrent gene processes in the same group of cells and technical noise can obscure the true progression of the processes studied. To address this challenge, we present GeneTrajectory, an approach that identifies trajectories of genes rather than trajectories of cells. Specifically, optimal transport distances are calculated between gene distributions across the cell-cell graph to extract gene programs and define their gene pseudotemporal order. Here we demonstrate that GeneTrajectory

SUBMITTER: Qu R 

PROVIDER: S-EPMC11452571 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature