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.
@article{arxiv.2311.00012,
title = {scX: A user-friendly tool for scRNA-seq exploration},
author = {Tomás Vega Waichman and M. Luz Vercesi and Ariel A. Berardino and Maximiliano S. Beckel and Damiana Giacomini and Natalí B. Rasetto and Magalí Herrero and Daniela J. Di Bella and Paola Arlotta and Alejandro F. Schinder and Ariel Chernomoretz},
journal= {arXiv preprint arXiv:2311.00012},
year = {2024}
}
Comments
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/scx