Improving genetic risk prediction across diverse population by disentangling ancestry representations

Abstract excerpt

<title>Abstract</title> <p>Risk prediction models using genetic data have seen increasing traction in genomics. However, most of the polygenic risk models were developed using data from participants with similar (mostly European) ancestry. This can lead to biases in the risk predictors resulting in poor generalization when applied to minority populations and admixed individuals such as African Americans. To addre...

Topics

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• Black or African American
• Deep Learning
• European People
• Minority Groups
• Models, Statistical
• Multifactorial Inheritance
• Population Groups
• Risk

Identifiers and source

Literature Corpus work

6f2b17b4-11d4-55d5-a671-f635037234d6

DOI

10.21203/rs.3.rs-1829520/v1