A Lightweight & Versatile Visualization Tool for Spatial-Omics Data.
Spatial-Live is a lightweight and versatile visualization tool specifically developed for single cell spatial-omics data analysis, including spatial transcriptiomics and more. Its 3D integration of multiple layers within a single space makes it highly suitable for visualizing multi-types spatial data. Leveraging the rendering capabilities of GPU-powered backend, Spatial-Live efficiently processes large datasets, offering interactivity, responsiveness, and a wide range of visualization effects through the stacking of multiple layers. As the saying goes, a picture is worth a thousand words. We firmly believe that effective data visualization plays a pivotal role in data exploration and interpretation, serving as a key component in gaining insights from complex datasets. Spatial-Live represents a valuable tool for achieving these objectives.
The development of Spatial-Live relied on several outstanding third-party libraries, such as deckgl, vue3, and react framework, alongside numerous other open-source libraries that may not all be listed here. I am immensely grateful for the contributions of these libraries and the invaluable work they have provided.
Please visit our documentation for installation, tutorials, examples and more.
First, please go to github website to download the Spatial-Live:
$ git clone https://github.com/yezhenqing/spatial-liveThere are two ways to start Spatial-Live for different users:
- regular user
You may need to install docker on your computer already, then you can run the below command:
$ cd spatial-live
$ docker compose -f docker-compose.yml up -d- development user
If you are a development user, I will assume you already installed node/npm on your computer:
$ cd spatial-live
$ npm install
$ npm run devAfter the docker instance or node server started, the Spatial-Live will be ready for exploration. You can open your browser to visit the url link: http://localhost:8225/
If you use Spatial-Live in your work, please cite the publication (preprint now) as below:
Spatial-Live: A lightweight and versatile tool for single cell spatial-omics data visualization
Zhenqing Ye, Zhao Lai, Siyuan Zheng, Yidong Chen
bioRxiv 2023 Sep 24. doi: 10.1101/2023.09.24.559173.
This repository is under MIT License.