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.

ONTraC website

Software GitHub repository

Reproducible code for ONTraC V1 (Genome Biology) paper

Zenodo dataset repository for ONTraC V1 (Genome Biology) paper

Reproducible code for ONTraC V2 (Small Methods) paper

ONTraC V1 (Genome Biology) paper link

ONTraC V2 (Small Methods) paper link