Skip to content

Applying iDEAL to AD dataset to identify genetic modifiers of APOE

Notifications You must be signed in to change notification settings

semper21/iDEAL_AD

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 

Repository files navigation

Imputed Deviation of Evolutionary Action Load (iDEAL) analysis of Alzheimer's disease

Project Description

Despite considerable insight from GWAS and sequencing studies, much of late-onset Alzheimer’s Disease (LOAD) heritability remains unexplained leading to uncertain risk stratification of patients and no available disease-modifying therapies. To date, the APOE gene remains the strongest genetic risk factor for LOAD. Carriers of the APOEɛ4 allele are at a greater risk, while the APOEɛ2 allele plays a protective role. However, many APOEɛ4 carriers remain disease-free and some APOEɛ2 carriers develop LOAD.

iDEAL, or imputed Deviation of Evolutionary Action Load, is a novel approach that identifies genes with differential mutational burden between the two paradoxical patient groups through a series of linear regression analyses.

Publication

Kim YW, Al-Ramahi I, Koire A, Wilson SJ, Konecki DM, Mota S, Soleimani S, Botas J, Lichtarge O. Harnessing the Paradoxical Phenotypes of APOE2 and APOE4 to Identify Genetic Modifiers in Alzheimer's Disease. Alzheimer's & Dementia. 2020

Note: The most up-to-date version of this repository is set to private.


Setup

Requirements

  • Linux or OSx
  • Anaconda
  • Python 3.6+

Download code

git clone https://github.com/semper21/iDEAL_AD.git 

Install environment

conda env create -f environment.yml

About

Applying iDEAL to AD dataset to identify genetic modifiers of APOE

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages