Reaching the End-Game for GWAS: Machine Learning Approaches for the Prioritization of Complex Disease Loci

Reaching the End-Game for GWAS: Machine Learning Approaches for the Prioritization of Complex Disease Loci

Genome-wide association studies (GWAS) have revealed thousands of genetic loci that underpin the complex biology of many human traits. However, the strength of GWAS – the ability to detect genetic association by linkage disequilibrium (LD) – is also its limitation. Whilst the ever-increasing study s...

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Bibliographic Details
Main Authors: Hannah L. Nicholls, Christopher R. John, David S. Watson, Patricia B. Munroe, Michael R. Barnes, Claudia P. Cabrera
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-04-01
Series:Frontiers in Genetics
Subjects:
machine learning
artificial intelligence
genome-wide association study
genomics
candidate gene
clinical translation
Online Access:https://www.frontiersin.org/article/10.3389/fgene.2020.00350/full

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