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  • Kyle Ruh

Introduction to Genome Wide Association Studies (GWAS)

Updated: Jul 20, 2023


DNA, Genome Wide Association Studies, GWAS

Genome-wide association studies (GWAS) analysis is probably one of the most popular bioinformatic methods used in the scientific field. This article will cover what GWAS is, and when and how to use it.


What is GWAS?

As you may have learned from biology class, mutations may occur in the DNA during inheritance, specifically on a nucleotide. And when such inherited mutations become more and more frequent in a population, it is called a single nucleotide polymorphism (SNP). GWAS is a powerful tool to identify genomic variants like SNPs associated with a risk for a disease or a particular trait. Thanks to the rapid development in data science, researchers can now analyze SNPs in millions, if not billions of individuals.

Sometimes GWAS isn’t too helpful in finding the direct disease mechanism–but in some cases like Alzheimer’s Disease, researchers continuously found APOE4 [1] as a risk gene through GWAS–so it’s always better than nothing. Identifying risk loci can greatly accelerate development of therapeutics.


How?

Please check out more resources below to aid yourself!




Challenges

Correlation is not causation. GWAS is a statistical tool to explain possible links, but it cannot provide evidence to cause-and-effect relationships. However, it can still show plausible links between a risk gene and a disease with sufficient epidemiological studies, so it remains a popular tool that professional scientists use.


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