scX: a user-friendly tool for scRNAseq exploration
Single-cell RNA sequencing (scRNAseq) has transformed our ability to explore biological systems. Nevertheless, proficient expertise is essential for handling and interpreting the data. In this article, we present scX, an R package built on the Shiny framework that streamlines the analysis, explorati...
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Veröffentlicht in: | Bioinformatics advances 2024, Vol.4 (1), p.vbae062 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Single-cell RNA sequencing (scRNAseq) has transformed our ability to explore biological systems. Nevertheless, proficient expertise is essential for handling and interpreting the data.
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.
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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ISSN: | 2635-0041 2635-0041 |
DOI: | 10.1093/bioadv/vbae062 |