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Tsuo et al., 2024 - Google Patents

All of Us diversity and scale improve polygenic prediction contextually with greatest improvements for under-represented populations

Tsuo et al., 2024

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Document ID
12307433626827548018
Author
Tsuo K
Shi Z
Ge T
Mandla R
Hou K
Ding Y
Pasaniuc B
Wang Y
Martin A
Publication year
Publication venue
bioRxiv

External Links

Snippet

Recent studies have demonstrated that polygenic risk scores (PRS) trained on multi- ancestry data can improve prediction accuracy in groups historically underrepresented in genomic studies, but the availability of linked health and genetic data from large-scale …
Continue reading at pmc.ncbi.nlm.nih.gov (HTML) (other versions)

Classifications

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    • G06F19/18—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for functional genomics or proteomics, e.g. genotype-phenotype associations, linkage disequilibrium, population genetics, binding site identification, mutagenesis, genotyping or genome annotation, protein-protein interactions or protein-nucleic acid interactions
    • G—PHYSICS
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