Single-cell RNA sequencing (scRNA-seq) has transformed our ability to explore
biological systems. Nevertheless, proficient expertise is essential for
handling and interpreting the data. In this paper, we present scX, an R package
built on the Shiny framework that streamlines the analysis, exploration, and
visualization of single-cell experiments. With an interactive graphic
interface, implemented as a web application, scX provides easy access to key
scRNAseq analyses, including marker identification, gene expression profiling,
and differential gene expression analysis. Additionally, scX seamlessly
integrates with commonly used single-cell Seurat and SingleCellExperiment R
objects, resulting in efficient processing and visualization of varied
datasets. Overall, scX serves as a valuable and user-friendly tool for
effortless exploration and sharing of single-cell data, simplifying some of the
complexities inherent in scRNAseq analysis.Comment: 10 pages, 2 figures. Source code can be downloaded from
https://github.com/chernolabs/scX. User manual available at
https://chernolabs.github.io/scX/. Docker image available from dockerhub as
chernolabs/sc