Metadata-Version: 2.3
Name: maxgcp
Version: 0.1.1
Summary: Optimized phenotype definitions boost GWAS power
Project-URL: Repository, https://github.com/tatonetti-lab/maxgcp
Author-email: zietzm <michael.zietz@gmail.com>
License-File: LICENSE
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Requires-Python: >=3.10
Requires-Dist: numpy>=1.26.4
Requires-Dist: pandas>=2.2.2
Description-Content-Type: text/markdown

# Maximum genetic component phenotyping

[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
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`maxgcp` is a Python package that implements maximum genetic component phenotyping (MaxGCP), a method that optimizes a linear phenotype definition to maximize its heritability and genetic correlation with a trait of interest.
In short, this method results in a phenotype definition that is, close to the genetic component of the trait of interest, on the individual level.
This phenotype definition can be used in various applications, including enhancement of statistical power in genome-wide association studies (GWAS).
`maxgcp` requires only estimates of genetic and phenotypic covariances, which can be obtained from GWAS summary statistics.
