Welcome to ONTraC (Ordered Niche Trajectory Construction)¶
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.
Check out the installation for installation guidelines.
Check out the usage for details if you want to use ONTraC with command lines.
Check out the step-by-step tutorial for details if you want to use ONTraC within a Jupyter notebook.
Note
This project is under active development.
Interoperability¶
ONTraC has been incorporated with Giotto Suite.
Citation¶
Wang, W.*, Zheng, S.*, Shin, C. S., Chávez-Fuentes J. C. & Yuan, G. C.$. ONTraC characterizes spatially continuous variations of tissue microenvironment through niche trajectory analysi. Genome Biol, 2025.