Metadata-Version: 2.3
Name: cosmoDA
Version: 0.1.0
Summary: Compositional Score Matching Optimization for Differential Abundance Testing
Project-URL: Homepage, https://github.com/bio-datascience/cosmoDA
Project-URL: Issues, https://github.com/bio-datascience/cosmoDA/issues
Author-email: Johannes Ostner <johannes.ostner@online.de>
License: BSD 3-Clause License
        
        Copyright (c) 2023, johannesostner
        All rights reserved.
        
        Redistribution and use in source and binary forms, with or without
        modification, are permitted provided that the following conditions are met:
        
        1. Redistributions of source code must retain the above copyright notice, this
           list of conditions and the following disclaimer.
        
        2. Redistributions in binary form must reproduce the above copyright notice,
           this list of conditions and the following disclaimer in the documentation
           and/or other materials provided with the distribution.
        
        3. Neither the name of the copyright holder nor the names of its
           contributors may be used to endorse or promote products derived from
           this software without specific prior written permission.
        
        THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
        AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
        IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
        DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
        FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
        DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
        SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
        CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
        OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
        OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Classifier: Development Status :: 4 - Beta
Classifier: Framework :: Jupyter
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.9
Requires-Dist: anndata
Requires-Dist: gglasso
Requires-Dist: jupyter
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: rpy2
Requires-Dist: scanpy
Requires-Dist: sccoda
Requires-Dist: scikit-learn
Requires-Dist: scipy
Requires-Dist: seaborn
Requires-Dist: statsmodels
Requires-Dist: ternary
Requires-Dist: tqdm
Requires-Dist: xlrd
Description-Content-Type: text/markdown

# cosmoDA - Compositional Score Matching Optimization for Differential Abundance Testing

![cosmoDA](misc/concept_figure.png)
 
This repository contains the cosmoDA model (Ostner et al., 2024), as well as a Python interface 
to the score matching estimator for power interaction models in the genscore R package (Yu et al., 2024). 
It also contains all code needed to reproduce the analyses in the publication (TODO).

For usage info, please refer to the tutorial.

Raw and intermediate data objects can be downloaded on [zenodo](TODO). 
Simply download the `data` directory from there and unpack it in the cosmoDA directory.

## Installation

TODO

## Usage

TODO

## Repository structure

This repository is structured as follows:

- The `cosmoDA` directory contains the python code to run the cosmoDA or genscore models.
- The `src` directory contains the C code from genscore, as well as its extension from the cosmoDA model.
- The `simulation` and `applications` directories contain the simulated and real data applications from the paper, respectively.
- The `misc` directory contains code for supplementary and concept figures.
- The `figures` directory contains all generated figures.


