Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (11.0%) to scientific vocabulary
Keywords
gwas
medicine
pgs
polygenic-risk-scores
prs
variational-inference
Last synced: 6 months ago
·
JSON representation
·
Repository
Variational Inference of Polygenic Risk Scores
Basic Info
- Host: GitHub
- Owner: shz9
- License: mit
- Language: Python
- Default Branch: master
- Homepage: https://shz9.github.io/viprs/
- Size: 9.48 MB
Statistics
- Stars: 28
- Watchers: 4
- Forks: 2
- Open Issues: 0
- Releases: 4
Topics
gwas
medicine
pgs
polygenic-risk-scores
prs
variational-inference
Created over 5 years ago
· Last pushed 10 months ago
Metadata Files
Readme
Changelog
License
Citation
README.md
viprs: Variational Inference of Polygenic Risk Scores
viprs is a python package that implements variational inference techniques to estimate the posterior distribution
of variant effect sizes conditional on the GWAS summary statistics. The package is designed to be fast and accurate,
and to provide a variety of options for the user to customize the inference process.
Highlighted features:
- The coordinate ascent algorithms are written in
C/C++andcythonfor improved speed and efficiency. - The code is written in object-oriented form, allowing the user to extend and experiment with existing implementations.
- Different priors on the effect size: Spike-and-slab, Sparse mixture, etc.
- We also provide scripts for different hyperparameter tuning strategies, including: Grid search, Bayesian optimization, Bayesian model averaging.
- Easy and straightforward interfaces for computing PRS from fitted models.
- Implementation for a wide variety of evaluation metrics for both binary and continuous phenotypes.
Helpful links
Owner
- Name: Shadi
- Login: shz9
- Kind: user
- Website: https://shz9.github.io/
- Repositories: 20
- Profile: https://github.com/shz9
PhD Student at McGill University
Citation (CITATION.md)
If you use `viprs` 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: 2
- Release event: 2
- Issues event: 14
- Watch event: 7
- Issue comment event: 16
- Push event: 16
- Fork event: 1
Last Year
- Create event: 2
- Release event: 2
- Issues event: 14
- Watch event: 7
- Issue comment event: 16
- Push event: 16
- Fork event: 1
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 13
- Total pull requests: 0
- Average time to close issues: 6 months
- Average time to close pull requests: N/A
- Total issue authors: 9
- Total pull request authors: 0
- Average comments per issue: 2.23
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 6
- Pull requests: 0
- Average time to close issues: about 1 month
- Average time to close pull requests: N/A
- Issue authors: 5
- Pull request authors: 0
- Average comments per issue: 2.5
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- MuhammadMuneeb007 (3)
- biostatShao (2)
- nlapier2 (2)
- shz9 (2)
- xinyu-c9 (1)
- sanket-desai (1)
- EtienneNtumba (1)
- rkarlssonlinner (1)
- ekhar17 (1)
- HUST-341 (1)
Pull Request Authors
Top Labels
Issue Labels
enhancement (1)
bug (1)
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- pypi 295 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 8
- Total maintainers: 1
pypi.org: viprs
Variational Inference of Polygenic Risk Scores (VIPRS)
- Homepage: https://github.com/shz9/viprs
- Documentation: https://viprs.readthedocs.io/
- License: mit
-
Latest release: 0.1.3
published 10 months ago
Rankings
Dependent packages count: 6.6%
Stargazers count: 19.5%
Average: 21.8%
Forks count: 30.5%
Dependent repos count: 30.6%
Maintainers (1)
Last synced:
7 months ago
Dependencies
requirements-optional.txt
pypi
- Cython *
- scikit-optimize ==0.8.1
- seaborn *
requirements.txt
pypi
- magenpy >=0.0.5
- numpy *
- pandas *
- psutil *
- scikit-learn *
- scipy *
- statsmodels *
- tqdm *
.github/workflows/ci-docs.yml
actions
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.github/workflows/ci-linux.yml
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pyproject.toml
pypi
requirements-docs.txt
pypi
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requirements-test.txt
pypi
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setup.py
pypi