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

Volume: 11, Pages: 350
Published: Apr 15, 2020
Abstract
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...
Paper Details
Title
Reaching the End-Game for GWAS: Machine Learning Approaches for the Prioritization of Complex Disease Loci.
Published Date
Apr 15, 2020
Volume
11
Pages
350
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.