Multimodal weakly supervised learning to identify disease-specific changes in single-cell atlases

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  • License: BSD 3-Clause License
  • Author: Anastasia Litinetskaya
  • Maintainer: Anastasia Litinetskaya
  • Requires: Python >=3.12
  • Provides-Extra: dev , doc , test , tutorials
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Project description

Multigrate: multiomic data integration for single-cell genomics

Tests Documentation

Getting started

Please refer to the documentation. In particular, the

and the tutorials:

See the paired integration tutorial for advice on which distributions and losses to use for which modalities.

Installation

You need to have Python 3.12 or newer installed on your system.

Quick start

To install the latest release of multigrate from PyPI:

pip install multigrate

Or install the latest development version:

pip install git+https://github.com/theislab/multigrate.git@main

Development setup

For development, we recommend using uv for fast dependency management:

# Clone the repository
git clone https://github.com/theislab/multigrate.git
cd multigrate

# Install in development mode with all optional dependencies
uv sync --all-groups

Release notes

See the changelog.

Contact

If you found a bug, please use the issue tracker.

Citation

Anastasia Litinetskaya, Maiia Schulman, Fabiola Curion, Artur Szalata, Alireza Omidi, Mohammad Lotfollahi, and Fabian Theis. 2022. "Integration and querying of multimodal single-cell data with PoE-VAE." bioRxiv. https://doi.org/10.1101/2022.03.16.484643.

Reproducibility

Code and notebooks to reproduce the results from the paper are available at https://github.com/theislab/multigrate_reproducibility.

Project details

Verified details

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  • License: BSD 3-Clause License
  • Author: Anastasia Litinetskaya
  • Maintainer: Anastasia Litinetskaya
  • Requires: Python >=3.12
  • Provides-Extra: dev , doc , test , tutorials
Classifiers

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