ONTraC (Ordered Niche Trajectory Construction)
Authors/Creators
Description
ONTraC (Ordered Niche Trajectory Construction) is a niche-centered, machine learning method for constructing spatially continuous trajectories. ONTraC differs from existing tools in that it treats a niche, rather than an individual cell, as the basic unit for spatial trajectory analysis. In this context, we define niche as a multicellular, spatially localized region where different cell types may coexist and interact with each other. ONTraC seamlessly integrates cell-type composition and spatial information by using the graph neural network modeling framework. Its output, which is called the niche trajectory, can be viewed as a one dimensional representation of the tissue microenvironment continuum. By disentangling cell-level and niche- level properties, niche trajectory analysis provides a coherent framework to study coordinated responses from all the cells in association with continuous tissue microenvironment variations.
Files
Files
(102.0 kB)
| Name | Size | Download all |
|---|---|---|
|
md5:237d300238d3c837954e841bd3d6f73e
|
55.8 kB | Download |
|
md5:4d07f00c2f07878b146b65a527848648
|
46.2 kB | Download |
Additional details
Related works
- Is supplement to
- 10.1101/2024.04.23.590827 (DOI)
Software
- Repository URL
- https://github.com/gyuanlab/ONTraC
- Programming language
- Python
- Development Status
- Active