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The 103,200-arm acceleration dataset in the UK Biobank revealed a landscape of human sleep phenotypes.


ABSTRACT: SignificanceHuman sleep phenotypes are diversified by genetic and environmental factors, and a quantitative classification of sleep phenotypes would lead to the advancement of biomedical mechanisms underlying human sleep diversity. To achieve that, a pipeline of data analysis, including a state-of-the-art sleep/wake classification algorithm, the uniform manifold approximation and projection (UMAP) dimension reduction method, and the density-based spatial clustering of applications with noise (DBSCAN) clustering method, was applied to the 100,000-arm acceleration dataset. This revealed 16 clusters, including seven different insomnia-like phenotypes. This kind of quantitative pipeline of sleep analysis is expected to promote data-based diagnosis of sleep disorders and psychiatric disorders that tend to be complicated by sleep disorders.

SUBMITTER: Katori M 

PROVIDER: S-EPMC8944865 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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The 103,200-arm acceleration dataset in the UK Biobank revealed a landscape of human sleep phenotypes.

Katori Machiko M   Shi Shoi S   Ode Koji L KL   Tomita Yasuhiro Y   Ueda Hiroki R HR  

Proceedings of the National Academy of Sciences of the United States of America 20220318 12


SignificanceHuman sleep phenotypes are diversified by genetic and environmental factors, and a quantitative classification of sleep phenotypes would lead to the advancement of biomedical mechanisms underlying human sleep diversity. To achieve that, a pipeline of data analysis, including a state-of-the-art sleep/wake classification algorithm, the uniform manifold approximation and projection (UMAP) dimension reduction method, and the density-based spatial clustering of applications with noise (DB  ...[more]

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