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Spatial-Live

Name

A Lightweight & Versatile Visualization Tool for Spatial-Omics Data.

Description

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.

Installation & Usage

First, please go to github website to download the Spatial-Live:

  $ git clone https://github.com/yezhenqing/spatial-live

There 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 dev

After 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/

Citation

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.

License

This repository is under MIT License.