Spateo-viewer is the “Google earth” of spatial transcriptomics. Relying on a set of powerful libraries and tools in the Python ecosystem, such as Trame, PyVista, VTK, etc., it delivers a complete web application solution of creating convenient, vivid, and lightweight interface for 3D reconstruction and visualization of Spateo downstream analysis results. Currently, Spateo-viewer includes two major applications, interactive-viewer and static-viewer, which are respectively dedicated to the 3D reconstruction of spatial transcriptomics and the visualization of spatial transcriptomics analysis results.
Please download and read the corresponding Slides to learn more about Spateo-viewer.
- In the interactive-viewer, 3D serial slices of spatial transcriptomics datasets can be aligned to create 3D models. The 3D model can be also cleaned up by freely clipping and editing.
- In the static-viewer, users can not only visualize gene expression, but also easily switch between raw and different types of normalized data or data layers. Users can also visualize all cell annotation information such as cell size, cell type, tissue type, etc. All done in 3D space!
- Static-viewer allows users to not only visualize the point cloud model and mesh model of the whole embryo, but also for individual organ or tissue type at the same time. It even visualizes morphogenesis vector field model to animate how cell move in the physical 3D space.
- Spateo-viewer can not only run on the local computer, but also run freely on the remote server.
- Users can upload custom files in the web application, or access to custom files in local folders when running Spateo-Viewer as a stand alone App.(See StaticViewerUsage or InteractiveViewerUsage)
You can clone the Spateo-viewer with git and install dependencies with pip:
git clone https://github.com/aristoteleo/spateo-viewer.git
cd spateo-viewer
pip install -r requirements.txt
python stv_static_app.py --port 1234
See the StaticViewerUsage for more details.
python stv_interactive_app.py --port 1234
See the InteractiveViewerUsage for more details.
Xiaojie Qiu1$*, Daniel Y. Zhu3$, Jiajun Yao2, 4, 5, 6$, Zehua Jing2, 4,7$, Lulu Zuo8$, Mingyue Wang2, 4, 9, 10$, Kyung Hoi (Joseph) Min11, Hailin Pan2, 4, Shuai Wang2, 4, 7, Sha Liao4, Yiwei Lai4, Shijie Hao2, 4, 7, Yuancheng Ryan Lu1, Matthew Hill17, Jorge D. Martin-Rufino17, Chen Weng1, Anna Maria Riera-Escandell18, Mengnan Chen2, 4, Liang Wu4, Yong Zhang4, Xiaoyu Wei2, 4, Mei Li4, Xin Huang4, Rong Xiang2, 4, 7, Zhuoxuan Yang4, 12, Chao Liu4, Tianyi Xia4, Yingxin Liang10, Junqiang Xu4,7, Qinan Hu9, 10, Yuhui Hu9, 10, Hongmei Zhu8, Yuxiang Li4, Ao Chen4, Miguel A. Esteban4, Ying Gu2, 4,7, Douglas A. Lauffenburger3, Xun Xu2, 4, 13, Longqi Liu2, 4, 14, 15*, Jonathan S. Weissman1,19, 20*, Shiping Liu2, 4, 14, 15, 16*, Yinqi Bai2, 4* $Co-first authors; *:Corresponding authors
Spateo: multidimensional spatiotemporal modeling of single-cell spatial transcriptomics