4.5 Article

OSCA: a tool for omic-data-based complex trait analysis

期刊

GENOME BIOLOGY
卷 20, 期 -, 页码 -

出版社

BMC
DOI: 10.1186/s13059-019-1718-z

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资金

  1. Australian Research Council [FT180100186]
  2. Australian National Health and Medical Research Council [1107258, 1113400, 1083656, 1078037, 1078901]
  3. Sylvia & Charles Viertel Charitable Foundation
  4. Age UK (Disconnected Mind program)
  5. Centre for Cognitive Ageing and Cognitive Epidemiology (Pilot Fund award)
  6. Age UK
  7. Wellcome Trust Institutional Strategic Support Fund
  8. University of Queensland
  9. Biotechnology and Biological Sciences Research Council [MR/K026992/1]
  10. University of Edinburgh
  11. Medical Research Council
  12. BBSRC [BB/F019394/1] Funding Source: UKRI

向作者/读者索取更多资源

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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