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scX: A user-friendly tool for scRNA-seq exploration
Single-cell RNA sequencing (scRNAseq) has revolutionized our ability to explore biological systems by enabling the study of gene expression at the individual cell level. However, handling and analyzing this data often require specialized expertise. In this contribution, we present scX, an R package...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cornell University
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635291/ https://www.ncbi.nlm.nih.gov/pubmed/37961742 |
Sumario: | Single-cell RNA sequencing (scRNAseq) has revolutionized our ability to explore biological systems by enabling the study of gene expression at the individual cell level. However, handling and analyzing this data often require specialized expertise. In this contribution, we present scX, an R package built on top of the Shiny framework, designed to simplify the analysis, exploration, and visualization of single-cell experiments. scX offers straightforward access to essential scRNAseq analyses, encompassing marker identification, gene expression profiling, and differential gene expression analysis. Implemented as a local web application with an intuitive graphical interface, scX allows users to create customized, publication-ready plots. Additionally, it seamlessly integrates with popular single-cell Seurat and SingleCellExperiment R objects, facilitating the rapid processing and visualization of diverse datasets. In summary, scX serves as a valuable tool for effortless exploration and sharing of single-cell data, alleviating some of the complexities associated with scRNAseq analysis. |
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