transmorph 0.1.1

Optimal transport-based tools for data integration.

Transmorph is a python package dedicated to data integration, with a particular focus on single-cell applications. Dataset integration describes the problem of tying several datasets together, across different samples or modalities. Our priority is scalability, as we aim to integrate datasets of tens of thousands data points in under a minute. We use an efficient optimal transport-based approach to do so, supported by a variety of computational tricks.

Documentation

https://transmorph.readthedocs.io/en/latest/

Installation

Two main options exist to install transmorph, from source of from PyPi. PyPi version should be more stable, but may not contain latest features. Using a python environment is highly recommended (for instance pipenv) in order to better handle dependency versioning.

Dependencies (automatically installed via $pip)

• cython
• numba
• numpy
• scipy
• scikit-learn
• osqp (quadratic program solver)
• POT (optimal transport in python)

Install from source (latest version)

git clone https://github.com/Risitop/transmorph
pip install ./transmorph

Install from PyPi (recommended, latest stable version)

pip install transmorph

Contributors

• Aziz Fouché, (Institut Curie Paris, ENS Paris-Saclay)
• Andrei Zinovyev, (Institut Curie Paris, INSERM, Mines ParisTech)
• Special thanks to Nicolas Captier (Institut Curie Paris) and Maxime Roméas (LIX, École polytechnique, INRIA, Institut Polytechnique de Paris) for the insightful discussions and proofreading.

References

• Weighted optimal transport integration: https://www.biorxiv.org/content/10.1101/2021.05.12.443561v1
• Package: preprint to come