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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.

Original publication

DOI

10.1186/s13059-019-1718-z

Type

Journal article

Journal

Genome biology

Publication Date

05/2019

Volume

20

Addresses

Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, 4072, Australia.

Keywords

Humans, Linear Models, Genetic Techniques, DNA Methylation, Phenotype, Computer Simulation, Software, Aged, Metabolomics