ISCVAM - Interactive Single Cell Visual Analytics
Full-stack web application for visualizing single-cell RNA-seq data with React/Node.js and R Shiny
Overview
Developed a full-stack web application to enable interactive visualization and exploration of single-cell RNA-seq data stored in HDF5 format.
Live Demo
🔗 Interactive Single Cell Visual Analytics for Multiomics (ISCVAM)
Key Features
- React/Node.js Frontend: Built a responsive, interactive web application for data visualization
- R Shiny Integration: Deployed a complementary R Shiny app to enable public data exploration
- HDF5 Data Support: Efficiently handles large-scale single-cell datasets stored in HDF5 format
- Multi-omics Visualization: Supports visualization of various single-cell data modalities
Technologies Used
- Frontend: React.js, JavaScript
- Backend: Node.js
- Data Apps: R Shiny
- Data Format: HDF5
- Deployment: University of Utah CHPC
Impact
This tool enables researchers to interactively explore and analyze complex single-cell datasets, facilitating discoveries in cancer research and immunotherapy.