TrajectoryNet 0.2.4

Installation

TrajectoryNet is available in pypi. Install by running the following

pip install TrajectoryNet

This code was tested with python 3.7 and 3.8.

Example

Basic Usage

Run with

python -m TrajectoryNet.main --dataset SCURVE

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 -m TrajectoryNet.main --dataset [PATH_TO_NPZ_FILE] --embedding_name [EMBEDDING_NAME]
python -m TrajectoryNet.eval --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.

References

[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}
}