CardamomOT

A gene regulatory network inference method adapted to time-course scRNA-seq datasets.

The algorithm consists of calibrating the parameters of a mechanistic model of gene expression. The calibrated model can then be simulated to reproduce the dataset used for inference. The simulation part is based on the Harissa package.

Key Features

  • Mechanistic inference of gene regulatory networks from scRNA-seq data

  • Supports time-course and trajectory data

  • Integration with mechanistic simulation models

  • Network visualization and analysis tools

References

  1. Ventre E, et al. (2021).

  2. Ventre E, et al. (2023).

  3. Maugé Y. and Ventre E. (2026). CardamomOT: a mechanistic optimal transport-based framework for gene regulatory network inference, trajectory reconstruction and generative modeling. doi: 10.64898/2026.03.31.715390

Author

Elias Ventre Yann Mauge

License

MIT License

Submodules