Protocol for the imputation of stimulus-induced single-cell gene expression trajectories from time-series scRNA-seq data
Summary: 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 scR...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
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| Series: | STAR Protocols |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666166725002175 |
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| Summary: | Summary: 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 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. |
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| ISSN: | 2666-1667 |