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magenpy

Modeling and Analysis of (Statistical) Genetics data in python

https://github.com/shz9/magenpy

Science Score: 31.0%

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    Found CITATION.cff file
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    Low similarity (10.4%) to scientific vocabulary

Keywords

genotype gwas ldsc linkage-disequilibrium phenotype prs simulation
Last synced: 6 months ago · JSON representation ·

Repository

Modeling and Analysis of (Statistical) Genetics data in python

Basic Info
Statistics
  • Stars: 16
  • Watchers: 1
  • Forks: 5
  • Open Issues: 5
  • Releases: 8
Topics
genotype gwas ldsc linkage-disequilibrium phenotype prs simulation
Created over 5 years ago · Last pushed 8 months ago
Metadata Files
Readme Changelog License Citation

README.md

magenpy: Modeling and Analysis of (Statistical) Genetics data in python

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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 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

Owner

  • Name: Shadi
  • Login: shz9
  • Kind: user

PhD Student at McGill University

Citation (CITATION.md) 

If you use `magenpy` in your research, please cite the following paper(s):

> Zabad, S., Gravel, S., & Li, Y. (2023). **Fast and accurate Bayesian polygenic risk modeling with variational inference.** 
The American Journal of Human Genetics, 110(5), 741–761. https://doi.org/10.1016/j.ajhg.2023.03.009

## BibTeX records

```bibtex
@article{ZABAD2023741,
    title = {Fast and accurate Bayesian polygenic risk modeling with variational inference},
    journal = {The American Journal of Human Genetics},
    volume = {110},
    number = {5},
    pages = {741-761},
    year = {2023},
    issn = {0002-9297},
    doi = {https://doi.org/10.1016/j.ajhg.2023.03.009},
    url = {https://www.sciencedirect.com/science/article/pii/S0002929723000939},
    author = {Shadi Zabad and Simon Gravel and Yue Li}
}
```

GitHub Events

Total
  • Create event: 3
  • Issues event: 2
  • Release event: 3
  • Issue comment event: 2
  • Push event: 18
  • Fork event: 1
Last Year
  • Create event: 3
  • Issues event: 2
  • Release event: 3
  • Issue comment event: 2
  • Push event: 18
  • Fork event: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 14
  • Total pull requests: 2
  • Average time to close issues: about 1 year
  • Average time to close pull requests: 4 months
  • Total issue authors: 3
  • Total pull request authors: 2
  • Average comments per issue: 1.07
  • Average comments per pull request: 0.0
  • Merged pull requests: 1
  • Bot issues: 0
  • Bot pull requests: 1
Past Year
  • Issues: 2
  • Pull requests: 0
  • Average time to close issues: 3 months
  • Average time to close pull requests: N/A
  • Issue authors: 2
  • Pull request authors: 0
  • Average comments per issue: 2.0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • shz9 (12)
  • biostatShao (1)
  • nlapier2 (1)
Pull Request Authors
  • dependabot[bot] (1)
  • dorukcakmakci (1)
Top Labels
Issue Labels
enhancement (6) good first issue (1)
Pull Request Labels
dependencies (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 525 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 1
  • Total versions: 18
  • Total maintainers: 1
pypi.org: magenpy

Modeling and Analysis of Statistical Genetics data in python

  • Versions: 18
  • Dependent Packages: 1
  • Dependent Repositories: 1
  • Downloads: 525 Last month
Rankings
Dependent packages count: 10.0%
Forks count: 14.2%
Stargazers count: 15.6%
Average: 17.4%
Dependent repos count: 21.7%
Downloads: 25.4%
Maintainers (1)
shz9
Last synced: 6 months ago

Dependencies

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pyproject.toml pypi
requirements-docs.txt pypi
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  • mkdocs-material *
  • mkdocs-material-extensions *
  • mkdocstrings-python *
requirements-optional.txt pypi
  • matplotlib *
  • seaborn *
  • statsmodels *
requirements-test.txt pypi
  • pytest * test
requirements.txt pypi
  • dask <=2024.1.0
  • numpy *
  • pandas *
  • pandas-plink *
  • psutil *
  • scipy *
  • tqdm *
  • zarr *
setup.py pypi