scX: a user-friendly tool for scRNAseq exploration.

Bioinformatics advances
Authors
Abstract

MOTIVATION: Single-cell RNA sequencing (scRNAseq) has transformed our ability to explore biological systems. Nevertheless, proficient expertise is essential for handling and interpreting the data.RESULTS: In this article, 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.AVAILABILITY AND IMPLEMENTATION: Source code can be downloaded from https://github.com/chernolabs/scX. A docker image is available from dockerhub as chernolabs/scx.

Year of Publication
2024
Journal
Bioinformatics advances
Volume
4
Issue
1
Pages
vbae062
Date Published
12/2024
ISSN
2635-0041
DOI
10.1093/bioadv/vbae062
PubMed ID
38779177
Links