Calculating niche trajectories with ONTraC

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.

ONTraC generate niche cluster an assignment matrix as an intermediate result. It is possible for users to utilise the niche cluster information as spatial domains or other downstreaming analysis. The following section outlines the process for running ONTraC on stereo-seq data and visualising which niche cluster each cell belongs to.

Preparation

• Install required packages and ONTraC

Please see the Installation section for installation guidelines.

Running ONTraC

ONTraC --meta-input data/stereo_seq_brain/original_data.csv --NN-dir output/stereo_seq_NN --GNN-dir output/stereo_seq_GNN --NT-dir output/stereo_seq_NT --device cuda -s 42 --lr 0.03 --hidden-feats 4 -k 6 --modularity-loss-weight 0.3 --regularization-loss-weight 0.1 --purity-loss-weight 300 --beta 0.03 2>&1 | tee log/stereo_seq.log

The input dataset and output files could be downloaded from Zenodo