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 🎉.
Instructions, documentation, and tutorials can be found at: SGS Website
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:
The SGS browser consists of two main components: the SGS server and SGS client. Once you have downloaded and installed the SGS client, you need to deploy the SGS server for data visualization.
Please note that SGS server deployment relies on Docker, so make sure Docker is configured!
👋 (Recommended）Graphical installation tutorial
If you want to customize the container configuration items, please refer to the manual installation tutorial: Manual installation
- 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
If you found an issue, please report it along with any relevant details to reproduce it. Thanks.
- Yi Wang (yiwang28@swu.edu.cn)
- Fang Lu (lufang0411@sina.com)
- Yongjiang Luo (lyjiang126@yeah.net)
- Tingting Xia (xtt199239@163.com)
- Jiahe Sun (sunjiahe0502@email.swu.edu.cn)
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.
SGS Copyright (c) 2024 Wang lab. All rights reserved. This software is distributed under the MIT License (MIT).