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Moscot - Multiomics Single-cell Optimal Transport

docs/_static/img/light_mode_concept_revised.png docs/_static/img/dark_mode_concept_revised.png

moscot is a framework for Optimal Transport (OT) applications in single-cell genomics. It scales to large datasets and can be used for a variety of applications across different modalities.

moscot's key applications

  • Trajectory inference (incorporating spatial and lineage information).
  • Mapping cells to their spatial organisation.
  • Aligning spatial transcriptomics slides.
  • Translating modalities.
  • prototyping of new OT models in single-cell genomics.
  • ... and more, check out the documentation for more information.

moscot is powered by OTT which is a JAX-based Optimal Transport toolkit that supports just-in-time compilation, GPU acceleration, automatic differentiation and linear memory complexity for OT problems.

Installation

Install moscot by running:

pip install moscot

In order to install moscot from in editable mode, run:

git clone https://github.com/theislab/moscot
cd moscot
pip install -e .

For further instructions how to install jax, please refer to https://github.com/google/jax.

Citing moscot

If you find a model useful for your research, please consider citing the Klein et al., 2025 manuscript as well as the publication introducing the model, which can be found in the corresponding documentation.