Computational workflow for investigating highly variable genes in single-cell RNA-seq across multiple time points and cell types

Arora J.K.Mahidol University2023-07-172023-07-172023-09-15STAR Protocols Vol.4 No.3 (2023)https://repository.li.mahidol.ac.th/handle/20.500.14594/87861Here, 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.1Biochemistry, Genetics and Molecular BiologyComputational workflow for investigating highly variable genes in single-cell RNA-seq across multiple time points and cell typesArticleSCOPUS10.1016/j.xpro.2023.1023872-s2.0-8516351979726661667