Study
Whole-genome sequencing of normal Singaporean volunteers
Study ID | Alternative Stable ID | Type |
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EGAS00001004007 | Other |
Study Description
Sleep is associated with various health outcomes. Despite their growing adoption, the potential for consumer wearables to contribute sleep metrics to sleep-related biomedical research remains largely uncharacterized. Here we analyzed sleep tracking data, along with questionnaire responses and multi-modal phenotypic data generated from 482 normal volunteers. First, we compared wearable-derived and self-reported sleep metrics, particularly total sleep time (TST) and sleep efficiency (SE). We then identified demographic, socioeconomic and lifestyle factors associated with wearable-derived TST. Among others, male gender (β = -15.539, 95% confidence interval [CI] = -26.245 - -4.832, p = 0.005), older age (β = -0.493, CI = -0.941 - -0.044, p = 0.032) and manual labor (β = -26.856, CI = -49.715 - -3.997, p = 0.022) were associated with reduced TST, whereas alcohol consumption (β = 19.247, CI = 8.008 - 30.486, p = 8.54x10-04) was associated with increased TST. Multi-modal phenotypic data analysis showed that wearable-derived TST and SE were associated with various cardiovascular disease ... (Show More)
Study Datasets 1 dataset.
Click on a Dataset ID in the table below to learn more, and to find out who to contact about access to these data
Dataset ID | Description | Technology | Samples |
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EGAD00001005480 |
Whole-genome sequencing (WGS) data for 546 Singaporean volunteers used to estimate WGS-LTL in the study. Samples were sequenced using Illumina Hiseq X to a mean coverage of 30X.
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HiSeq X Ten | 546 |
Who archives the data?
