scViewer: An Interactive Single-Cell Gene Expression Visualization Tool
Single-cell RNA sequencing (scRNA-seq) is an attractive technology for researchers to gain valuable insights into the cellular processes and cell type diversity present in all tissues. The data generated by the scRNA-seq experiment are high-dimensional and complex in nature. Several tools are now av...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-05-01
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| Series: | Cells |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4409/12/11/1489 |
| _version_ | 1797597770148741120 |
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| author | Abhijeet R. Patil Gaurav Kumar Huanyu Zhou Liling Warren |
| author_facet | Abhijeet R. Patil Gaurav Kumar Huanyu Zhou Liling Warren |
| author_sort | Abhijeet R. Patil |
| collection | DOAJ |
| description | Single-cell RNA sequencing (scRNA-seq) is an attractive technology for researchers to gain valuable insights into the cellular processes and cell type diversity present in all tissues. The data generated by the scRNA-seq experiment are high-dimensional and complex in nature. Several tools are now available to analyze the raw scRNA-seq data from public databases; however, simple and easy-to-explore single-cell gene expression visualization tools focusing on differential expression and co-expression are lacking. Here, we present scViewer, an interactive graphical user interface (GUI) R/Shiny application designed to facilitate the visualization of scRNA-seq gene expression data. With the processed Seurat RDS object as input, scViewer utilizes several statistical approaches to provide detailed information on the loaded scRNA-seq experiment and generates publication-ready plots. The major functionalities of scViewer include exploring cell-type-specific gene expression, co-expression analysis of two genes, and differential expression analysis with different biological conditions considering both cell-level and subject-level variations using negative binomial mixed modeling. We utilized a publicly available dataset (brain cells from a study of Alzheimer’s disease to demonstrate the utility of our tool. scViewer can be downloaded from GitHub as a Shiny app with local installation. Overall, scViewer is a user-friendly application that will allow researchers to visualize and interpret the scRNA-seq data efficiently for multi-condition comparison by performing gene-level differential expression and co-expression analysis on the fly. Considering the functionalities of this Shiny app, scViewer can be a great resource for collaboration between bioinformaticians and wet lab scientists for faster data visualizations. |
| first_indexed | 2024-03-11T03:09:11Z |
| format | Article |
| id | doaj.art-0471c370d492442ca209c405e4ee4541 |
| institution | Directory Open Access Journal |
| issn | 2073-4409 |
| language | English |
| last_indexed | 2024-03-11T03:09:11Z |
| publishDate | 2023-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Cells |
| spelling | doaj.art-0471c370d492442ca209c405e4ee45412023-11-18T07:40:47ZengMDPI AGCells2073-44092023-05-011211148910.3390/cells12111489scViewer: An Interactive Single-Cell Gene Expression Visualization ToolAbhijeet R. Patil0Gaurav Kumar1Huanyu Zhou2Liling Warren3Global Statistical and Data Sciences, Teva Pharmaceuticals, West Chester, PA 19380, USAGlobal Statistical and Data Sciences, Teva Pharmaceuticals, West Chester, PA 19380, USAGlobal Statistical and Data Sciences, Teva Pharmaceuticals, West Chester, PA 19380, USAGlobal Statistical and Data Sciences, Teva Pharmaceuticals, West Chester, PA 19380, USASingle-cell RNA sequencing (scRNA-seq) is an attractive technology for researchers to gain valuable insights into the cellular processes and cell type diversity present in all tissues. The data generated by the scRNA-seq experiment are high-dimensional and complex in nature. Several tools are now available to analyze the raw scRNA-seq data from public databases; however, simple and easy-to-explore single-cell gene expression visualization tools focusing on differential expression and co-expression are lacking. Here, we present scViewer, an interactive graphical user interface (GUI) R/Shiny application designed to facilitate the visualization of scRNA-seq gene expression data. With the processed Seurat RDS object as input, scViewer utilizes several statistical approaches to provide detailed information on the loaded scRNA-seq experiment and generates publication-ready plots. The major functionalities of scViewer include exploring cell-type-specific gene expression, co-expression analysis of two genes, and differential expression analysis with different biological conditions considering both cell-level and subject-level variations using negative binomial mixed modeling. We utilized a publicly available dataset (brain cells from a study of Alzheimer’s disease to demonstrate the utility of our tool. scViewer can be downloaded from GitHub as a Shiny app with local installation. Overall, scViewer is a user-friendly application that will allow researchers to visualize and interpret the scRNA-seq data efficiently for multi-condition comparison by performing gene-level differential expression and co-expression analysis on the fly. Considering the functionalities of this Shiny app, scViewer can be a great resource for collaboration between bioinformaticians and wet lab scientists for faster data visualizations.https://www.mdpi.com/2073-4409/12/11/1489single-cell RNA sequencingscRNA-seqR Shinybioinformaticsgene expressionco-expression |
| spellingShingle | Abhijeet R. Patil Gaurav Kumar Huanyu Zhou Liling Warren scViewer: An Interactive Single-Cell Gene Expression Visualization Tool Cells single-cell RNA sequencing scRNA-seq R Shiny bioinformatics gene expression co-expression |
| title | scViewer: An Interactive Single-Cell Gene Expression Visualization Tool |
| title_full | scViewer: An Interactive Single-Cell Gene Expression Visualization Tool |
| title_fullStr | scViewer: An Interactive Single-Cell Gene Expression Visualization Tool |
| title_full_unstemmed | scViewer: An Interactive Single-Cell Gene Expression Visualization Tool |
| title_short | scViewer: An Interactive Single-Cell Gene Expression Visualization Tool |
| title_sort | scviewer an interactive single cell gene expression visualization tool |
| topic | single-cell RNA sequencing scRNA-seq R Shiny bioinformatics gene expression co-expression |
| url | https://www.mdpi.com/2073-4409/12/11/1489 |
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