Evaluation of polygenic scoring methods in five biobanks reveals greater variability between biobanks than between methods and highlights benefits of ensemble learning

Abstract excerpt

<h4>Methods: </h4> to estimate polygenic scores (PGS) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived using seven methods in five biobank studies (totaling about 1.2 million participants) across 16 diseases and quantitative traits, building on a reference-standardi...

Topics

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• Biological Specimen Banks
• Diabetes Mellitus, Type 1
• Genome-Wide Association Study
• Machine Learning
• Multifactorial Inheritance
• Phenotype
• Polymorphism, Single Nucleotide
• Sample Size

Identifiers and source

Literature Corpus work

150c232d-2afc-533b-88b0-acd0a23bcd8c

DOI

10.1101/2023.11.20.23298215