Metadata-Version: 2.1
Name: QRankGWAS
Version: 0.0.7
Summary: Python implementation of the QRank method described in Song et al Bioninformatics 2017.
Home-page: https://github.com/daverblair/QRankGWAS
Author: David Blair
Author-email: david.blair@ucsf.edu
License: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
Requires-Dist: argparse (>=1.1)
Requires-Dist: numpy (>=1.19.0)
Requires-Dist: pandas (>=1.0.5)
Requires-Dist: statsmodels (>=0.11.1)
Requires-Dist: scipy (>=1.5.2)
Requires-Dist: scikit-learn (>=0.23.1)
Requires-Dist: bgen (==1.2.7)

# QRankGWAS
 Software implementing the QRank method described in Song el al. Bioninformatics 2017. It was adapted for use within the UK Biobank using Python. It was designed to be used as a command-line tool. Note, the R QRank version and the python implementation will not yield identical results. The python version uses Iterative Weighted Least Squares to fit the null regression models, while the R version uses the simplex method. Therefore, the two implementations can produce slightly different p-values, but they are highly consistent.

Installation:

pip install QRankGWAS

Following installation, specific details regarding the software can be found by running the following command:

python -m QRankGWAS -h