Metadata-Version: 2.1
Name: magenpy
Version: 0.1.0
Summary: Modeling and Analysis of Statistical Genetics data in python
Home-page: https://github.com/shz9/magenpy
Author: Shadi Zabad
Author-email: shadi.zabad@mail.mcgill.ca
Classifier: Programming Language :: Python
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering
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: Programming Language :: Python :: 3.12
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: dask
Requires-Dist: scipy
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: pandas-plink
Requires-Dist: psutil
Requires-Dist: tqdm
Requires-Dist: zarr
Provides-Extra: docs
Requires-Dist: mkdocs ; extra == 'docs'
Requires-Dist: mkdocstrings-python ; extra == 'docs'
Requires-Dist: mkdocs-material ; extra == 'docs'
Requires-Dist: mkdocs-material-extensions ; extra == 'docs'
Provides-Extra: opt
Requires-Dist: matplotlib ; extra == 'opt'
Requires-Dist: seaborn ; extra == 'opt'
Requires-Dist: statsmodels ; extra == 'opt'
Provides-Extra: test
Requires-Dist: pytest ; extra == 'test'

# `magenpy`: *M*odeling and *A*nalysis of (Statistical) *Gen*etics data in *py*thon

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`magenpy` is a Python package for modeling and analyzing statistical genetics data. 
The package provides tools for:

* Reading and processing genotype data in `plink` BED format.
* Efficient LD matrix construction and storage in [Zarr](https://zarr.readthedocs.io/en/stable/index.html) array format.
* Data structures for harmonizing various GWAS data sources.
  * Includes parsers for commonly used GWAS summary statistics formats.
* Simulating polygenic traits (continuous and binary) using complex genetic architectures.
    * Multi-cohort simulation scenarios (beta)
    * Simulations incorporating functional annotations in the genetic architecture (beta)
* Interfaces for performing association testing on simulated and real phenotypes.
* Preliminary support for processing and integrating genomic annotations with other data sources.

### Helpful links

- [Documentation](https://shz9.github.io/magenpy/)
- [Citation / BibTeX records](./CITATION.md)
- [Report issues/bugs](https://github.com/shz9/magenpy/issues)
