期刊
GENOME BIOLOGY
卷 20, 期 -, 页码 -出版社
BMC
DOI: 10.1186/s13059-019-1718-z
关键词
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资金
- Australian Research Council [FT180100186]
- Australian National Health and Medical Research Council [1107258, 1113400, 1083656, 1078037, 1078901]
- Sylvia & Charles Viertel Charitable Foundation
- Age UK (Disconnected Mind program)
- Centre for Cognitive Ageing and Cognitive Epidemiology (Pilot Fund award)
- Age UK
- Wellcome Trust Institutional Strategic Support Fund
- University of Queensland
- Biotechnology and Biological Sciences Research Council [MR/K026992/1]
- University of Edinburgh
- Medical Research Council
- BBSRC [BB/F019394/1] Funding Source: UKRI
The rapid increase of omic data has greatly facilitated the investigation of associations between omic profiles such as DNA methylation (DNAm) and complex traits in large cohorts. Here, we propose a mixed-linear-model-based method called MOMENT that tests for association between a DNAm probe and trait with all other distal probes fitted in multiple random-effect components to account for unobserved confounders. We demonstrate by simulations that MOMENT shows a lower false positive rate and more robustness than existing methods. MOMENT has been implemented in a versatile software package called OSCA together with a number of other implementations for omic-data-based analyses.
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