Work

Protocol for the imputation of stimulus-induced single-cell gene expression trajectories from time-series scRNA-seq data

Year: 2025

Type: article

Abstract: Single-cell RNA sequencing (scRNA-seq) measures cell-to-cell heterogeneous mRNA abundance but destroys the cell and precludes tracking of heterogeneous gene expression trajectories. Here, we present an approach to impute single-cell gene expression trajectories (scGETs) from time-series scRNA-seq measurements. We describe four main computational steps: dimensionality reduction, calculation of transition probability matrices, spline interpolation, and deconvolution to scGETs. Imputing scGETs can aid in studying heterogeneous stimulus responses over time, such as cancer cell responses to drugs or immune cell responses to pathogens. For complete details on the use and execution of this protocol, please refer to Sheu et al. 1

Source: STAR Protocols

DOI: 10.1016/j.xpro.2025.103811

Authors: Katherine M. Sheu, Alexander Hoffmann

Institution: University of California, Los Angeles

Language: English

Topic: Single-cell and spatial transcriptomics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $1,550

Funders: University of California, Los Angeles, National Cancer Institute, National Institute of Allergy and Infectious Diseases