SGS: An Integrative Browser for Collaborative Visualization of Single-cell and Spatial Multimodal Data

🎉 SGS, a user-friendly ⚡, collaborative ⚡ and versatile ⚡ browser for visualizing single-cell and spatial multiomics data, including scRNA, spatial transcriptomics, scATAC, scMethylC, sc-eQTL etc. With advanced features for comparative visualization, multi-panel coordiniate view, abundant visualization functions and collaborative exploration, SGS empowers researchers to unlocking the novel insights from scMulti-omics data 🎉.

🚀 Document

Instructions, documentation, and tutorials can be found at: SGS Website

⚙️ Installation

Make Sure Docker is installed on your server SGS primarily utilizes Docker and Flutter technologies to achieve graphical one-click installation. SGS supports the following three deployment methods:

🎈🎈🎈 Quick Start

Once you have downloaded the SGS software, you can install SGS through a graphical interface for data visualization.

Please note that SGS installation relies on Docker, so make sure Docker is configured!

👋 (Recommended）Graphical installation tutorial

Manual installation (Optional）

If you want to customize the container configuration items, please refer to the manual installation tutorial: Manual installation

💻 File Format and Conversion

• SGS supports various data formats including Anndata, Mudata, and genome-mapped files (GFF, VCF, BED, Bigwig, HiC, Biginteract, Longrange, methylC, Gwas,).
• The SgsAnnData R package enables seamless data format conversion with analysis tools like Seurat, ArchR, Signac, and Giotto.
• SgsAnnData can be access by the following links: SgsAnnData gtihub

🌱 Reporting Issues

If you found an issue, please report it along with any relevant details to reproduce it. Thanks.

😊 Contact

• Yi Wang ([email protected])
• Fang Lu ([email protected])
• Yongjiang Luo ([email protected])
• Tingting Xia ([email protected])
• Jiahe Sun ([email protected])

🌹 Citiation

Xia, T., Sun, J., Lu, F., Luo, Y., Mao, Y., Xu, L., & Wang, Y. (2024). Empowering Integrative and Collaborative Exploration of Single-Cell and Spatial Multimodal Data with SGS. bioRxiv, (), 2024.07.19.604227. Accessed July 23, 2024. https://doi.org/10.1101/2024.07.19.604227.

👉 License

SGS Copyright (c) 2024 Wang lab. All rights reserved. This software is distributed under the MIT License (MIT).