scX: A user-friendly tool for scRNA-seq exploration
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arXiv
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| Autori principali: | , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| author | Waichman, Tomás Vega Vercesi, M. Luz Berardino, Ariel A. Beckel, Maximiliano S. Giacomini, Damiana Rasetto, Natalí B. Herrero, Magalí Di Bella, Daniela J. Arlotta, Paola Schinder, Alejandro F. Chernomoretz, Ariel |
| author_facet | Waichman, Tomás Vega Vercesi, M. Luz Berardino, Ariel A. Beckel, Maximiliano S. Giacomini, Damiana Rasetto, Natalí B. Herrero, Magalí Di Bella, Daniela J. Arlotta, Paola Schinder, Alejandro F. Chernomoretz, Ariel |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2311_00012 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | scX: A user-friendly tool for scRNA-seq exploration Waichman, Tomás Vega Vercesi, M. Luz Berardino, Ariel A. Beckel, Maximiliano S. Giacomini, Damiana Rasetto, Natalí B. Herrero, Magalí Di Bella, Daniela J. Arlotta, Paola Schinder, Alejandro F. Chernomoretz, Ariel Genomics 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. |
| title | scX: A user-friendly tool for scRNA-seq exploration |
| topic | Genomics |
| url | https://arxiv.org/abs/2311.00012 |