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

从时间序列单细胞RNA测序数据中推断刺激诱导的单细胞基因表达轨迹的方案

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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).

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