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Reaching the End-Game for GWAS: Machine Learning Approaches for the Prioritization of Complex Disease Loci
2020
Frontiers in Genetics
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 size and improved design have augmented the power of GWAS to detect effects, differentiation of causal variants or genes from other highly correlated genes associated by LD remains the real challenge.
doi:10.3389/fgene.2020.00350
pmid:32351543
pmcid:PMC7174742
fatcat:7h47rgpunvaa5grbz43aswwzey