期刊
NATURE COMMUNICATIONS
卷 10, 期 -, 页码 -出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/s41467-019-10864-z
关键词
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资金
- Fundamental Research Funds for the Central Universities
- Research Funds of Renmin University of China [19XNLG08]
- Renmin University of China [19XNLG08]
- Hong Kong Research Grants Council [PF13-11656, 22302815, 12316116, 12301417, 16307818]
- National Science Funding of China [61501389]
- Hong Kong University of Science and Technology [R9405, IGN17SC02]
- Research Grants Council of the Hong KongSpecial Administrative Region [24301416, 14306417]
- Research Committee of the Chinese University of Hong Kong
In epigenome-wide association studies, the measured signals for each sample are a mixture of methylation profiles from different cell types. Current approaches to the association detection claim whether a cytosine-phosphate-guanine (CpG) site is associated with the phenotype or not at aggregate level and can suffer from low statistical power. Here, we propose a statistical method, HIgh REsolution (HIRE), which not only improves the power of association detection at aggregate level as compared to the existing methods but also enables the detection of risk-CpG sites for individual cell types.
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