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Moscot - Multiomics Single-cell Optimal Transport

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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.

Release files for moscot 0.5.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for moscot 0.5.2
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Built distribution (wheel)

Table of built distributions (wheels) for moscot 0.5.2
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moscot-0.5.2-py3-none-any.whl Python 3 none any Details

Total release size: 631.1 kB

Release files / moscot-0.5.2.tar.gz

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