This library runs code associated with the TrajectoryNet paper.

Download code

git clone http://github.com/KrishnaswamyLab/TrajectoryNet.git

Install required packages

pip install -r requirements.txt

This code was tested with python 3.8

Run with

python main.py --dataset EB

To use a custom dataset expose the coordinates and timepoint information according to the example jupyter notebooks in the /notebooks/ folder.

TrajectoryNet requires the following:

1. An embedding matrix titled [embedding_name] (Cells x Dimensions)
2. A sample labels array titled sample_labels (Cells)
3. (Optionally) a delta embedding representing RNA velocity titled delta_[embedding_name] (Cells x Dimensions)

To run TrajectoryNet with a custom dataset use:

python main.py --dataset [PATH_TO_NPZ_FILE] --embedding_name [EMBEDDING_NAME]

See notebooks/EB-Eval.ipynb for an example on how to use TrajectoryNet on a PCA embedding to get trajectories in the gene space.

[1] Tong, A., Huang, J., Wolf, G., van Dijk, D., and Krishnaswamy, S. TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics. In International Conference on Machine Learning, 2020. [arxiv] [ICML]

If you found this library useful, please consider citing

@inproceedings{tong2020trajectorynet,
  title = {TrajectoryNet: A Dynamic Optimal Transport Network for Modeling Cellular Dynamics},
  shorttitle = {{{TrajectoryNet}}},
  booktitle = {Proceedings of the 37th International Conference on Machine Learning},
  author = {Tong, Alexander and Huang, Jessie and Wolf, Guy and {van Dijk}, David and Krishnaswamy, Smita},
  year = {2020}
}