This repository contains scripts used to analyze proxy-cases in population-based genome-wide association studies. :warning:These scripts are beta versions and this respository is under development.
Liu et al, 2017 introduced the concept of GWAS by proxy (GWAX): performing case-control genetic association studies using unaffected first-degree relatives of cases (proxy-cases) in the (near) absence of true cases. This was motivated by large population-based biobanks, such as the UK Biobank, with a largely young and healthy population where cases for diseases such as Alzheimer's are rare, but relatives of Alzheimer's cases are present. Proxy-cases can be identified via self report of family history of disease in survey questionnaires that are frequently a part of biobank enrollment. Previous work in this area also includes the kin-cohort method (Joshi et al, 2016 and Wacholder et al, 1998).
Population-based cohorts such as the Nord-Trøndelag Health Study (HUNT) and the UK Biobank have cases and proxy-cases for many diseases of interest (e.g. type 2 diabetes or myocardial infarction). We have demonstrated the utility of these proxy-cases and developed tools for using these samples in multiple models to study the genetics of complex diseases. Please view the provided PDF for more information.
Scripts made available here are useful for:
- Identifying proxy-cases in your cohort
- proxyCaseAssign1dr.py
- proxyCaseAssignAffRel.py
- proxyModel.py
- Running statistical methods that model proxy-cases
In order to download proxyPower you should clone this repository.
git clone https:://github.com/bnwolford/proxyPower.git
cd proxyPower
- Tutorial
- Issues with proxyPower? Email bwolford@umich.edu.
This project is licensed under the terms of the MIT license.