Tomás V Waichman, M L Vercesi, Ariel A Berardino, Maximiliano S Beckel, Damiana Giacomini, Natalí B Rasetto, Magalí Herrero, Daniela J Di Bella, Paola Arlotta, Alejandro F Schinder, Ariel Chernomoretz
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引用次数: 0
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.
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