Awesome
Multimodal weakly supervised learning to identify disease-specific changes in single-cell atlases
Getting started
Please refer to the documentation. In particular, the
and the tutorials:
- Paired integration and query-to-reference mapping
- Trimodal integration and query-to-reference mapping
- Classification with MIL
Installation
You need to have Python 3.10 or newer installed on your system. We recommend installing Mambaforge.
To create and activate a new environment:
mamba create --name multimil python=3.10
mamba activate multimil
Next, there are several alternative options to install multimil:
- Install the latest release of
multimil
from PyPI:
pip install multimil
- Or install the latest development version:
pip install git+https://github.com/theislab/multimil.git@main
Release notes
See the changelog.
Contact
If you found a bug, please use the issue tracker.
Citation
Multimodal Weakly Supervised Learning to Identify Disease-Specific Changes in Single-Cell Atlases
Anastasia Litinetskaya, Maiia Shulman, Soroor Hediyeh-zadeh, Amir Ali Moinfar, Fabiola Curion, Artur Szalata, Alireza Omidi, Mohammad Lotfollahi, and Fabian J. Theis. 2024. bioRxiv. https://doi.org/10.1101/2024.07.29.605625.
Reproducibility
Code and notebooks to reproduce the results from the paper are available at https://github.com/theislab/multimil_reproducibility.