2023/10/31 by Waichman, Tomás Vega, Vercesi, M. Luz, Maximiliano S. Beckel +16
Biochemistry, Genetics and Molecular Biology · #Cancer Genomics and Diagnostics #FOS: Biological sciences #Gene expression and cancer classification #Genomics (q-bio.GN) #Single-cell and spatial transcriptomics
paper · pdf · doi:10.48550/arxiv.2311.00012
openalex publication_date 2023/10/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
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.