multimil 0.3.1

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

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

Getting started

Please refer to the documentation. In particular, the

• API documentation

and the tutorials:

• 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:

1. Install the latest release of multimil from PyPI:

pip install multimil

2. 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 theislab/multimil_reproducibility.