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Estimating cell-type-specific DNA methylation effects in heterogeneous cellular populations.

Yen-Chen Anne FengYichen GuoLucile PainG Mark LathropCatherine LapriseMiriam F MoffattWilliam O C M CooksonLiming Liang
Published in: Epigenomics (2020)
Aim: To develop a method for estimating cell-specific effects in epigenomic association studies in the presence of cell type heterogeneity. Materials & methods: We utilized Monte Carlo Expectation-Maximization algorithm with Metropolis-Hastings sampler to reconstruct the 'missing' cell-specific methylations and to estimate their associations with phenotypes free of confounding by cell type proportions. Results: Simulations showed reliable performance of the method under various settings including when the cell type is rare. Application to a real dataset recapitulated the directly measured cell-specific methylation pattern in whole blood. Conclusion: This work provides a framework to identify important cell groups and account for cell type composition useful for studying the role of epigenetic changes in human traits and diseases.
Keyphrases
  • single cell
  • dna methylation
  • cell therapy
  • monte carlo
  • gene expression
  • genome wide
  • endothelial cells
  • stem cells
  • deep learning
  • mesenchymal stem cells
  • molecular dynamics