From f3853d35f636d07f944e435732ee22e690d2a5dd Mon Sep 17 00:00:00 2001 From: zietzm Date: Tue, 30 Apr 2024 13:44:51 -0500 Subject: [PATCH] chore: add usage/install to readme --- README.md | 47 +++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 47 insertions(+) diff --git a/README.md b/README.md index af487bc..631aa73 100644 --- a/README.md +++ b/README.md @@ -1,9 +1,56 @@ # 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) +[![image](https://img.shields.io/pypi/v/maxgcp)](https://pypi.python.org/pypi/maxgcp) +[![image](https://img.shields.io/pypi/l/maxgcp)](https://pypi.python.org/pypi/maxgcp) +[![image](https://img.shields.io/pypi/pyversions/maxgcp)](https://pypi.python.org/pypi/maxgcp) [![Actions status](https://img.shields.io/github/actions/workflow/status/tatonetti-lab/maxgcp/test.yml?branch=main&label=actions)](https://github.com/tatonetti-lab/maxgcp/actions) +Maximum genetic component phenotyping. Optimized phenotype definitions boost GWAS power. + `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. + +## Usage + +```python +import maxgcp +import numpy as np + +# Genetic covariances between target and feature phenotypes +genetic_cov_vec = np.array([0.5, 0.75, 0.25]) +phenotypic_cov_mat = np.array([ + [0.5, 0.25, 0.1], + [0.25, 0.3, 0.05], + [0.1, 0.05, 0.6], +]) + +# Compute the MaxGCP phenotype (defined by these weights) +w = maxgcp.fit_coheritability(genetic_cov_vec, phenotypic_cov_mat) + +# Evaluate MaxGCP at the individual level +feature_phenotypes = np.array([ + [1, 0, 0], + [0, 0, 1], + [1, 1, 1], + [0, 0, 0], +]) +maxgcp_phenotypes = feature_phenotypes @ w + +# Show the results +>>> maxgcp_phenotypes +array([-0.34242555, 0.18438299, 1.87895044, 0. ]) +``` + +MaxGCP fits a phenotype (y) to a target (z) to maximize coheritability between y and z. +This package can also fit a maximally heritable phenotype `maxgcp.fit_heritability` or a maximally genetically correlated phenotype (`maxgcp.fit_genetic_correlation`. + +## Installation + +```bash +pip install maxgcp +``` + +`maxgcp` depends on NumPy, SciPy, and pandas.