Arora J.K. Computational workflow for investigating highly variable genes in single-cell RNA-seq across multiple time points and cell types. STAR Protocols Vol.4 No.3 (2023). doi:10.1016/j.xpro.2023.102387 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/87861
Title
Computational workflow for investigating highly variable genes in single-cell RNA-seq across multiple time points and cell types
Here, we present a computational approach for investigating highly variable genes (HVGs) associated with biological pathways of interest, across multiple time points and cell types in single-cell RNA-sequencing (scRNA-seq) data. Using public dengue virus and COVID-19 datasets, we describe steps for using the framework to characterize the dynamic expression levels of HVGs related to common and cell-type-specific biological pathways over multiple immune cell types. For complete details on the use and execution of this protocol, please refer to Arora et al.1
