Metadata-Version: 2.4
Name: mmg-sc
Version: 0.1.0
Summary: Meta Marker Generator (MMG) for multimodal and cross-species single-cell data integration
Project-URL: Homepage, https://github.com/sunyk740/MMG
Project-URL: Bug Reports, https://github.com/sunyk740/MMG/issues
Project-URL: Repository, https://github.com/sunyk740/MMG.git
Author-email: Yongkang Sun <sunyk2023@ion.ac.cn>
License: MIT
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: <3.12,>=3.8
Requires-Dist: matplotlib==3.7.5
Requires-Dist: numpy==1.22.4
Requires-Dist: pandas==2.0.3
Requires-Dist: pot==0.9.4
Requires-Dist: scanpy==1.9.3
Requires-Dist: scikit-learn==1.3.2
Requires-Dist: scipy==1.10.1
Requires-Dist: seaborn==0.13.2
Requires-Dist: torch==2.0.1
Description-Content-Type: text/markdown

# MMG
**MMG (Meta Marker Generator)** is an interpretable linear framework for cross-modal and cross-species single-cell data integration.

## 📖 Overview

MMG learns concise, linearly weighted gene combinations called **"meta-markers"** through a denoising autoencoder with adversarial domain adaptation. Unlike black-box deep learning approaches, MMG produces interpretable gene weight vectors that capture essential cellular identity information while remaining robust to technical artifacts.

## 📦 Installation

```bash
pip install mmg-sc
