Abstract
The behavior of epigenetic mechanisms in the brain is obscured by tissue heterogeneity and disease-related histological changes. Not accounting for these confounders leads to biased results. We develop a statistical methodology that estimates and adjusts for celltype composition by decomposing neuronal and non-neuronal differential signal. This method provides a conceptual framework for deconvolving heterogeneous epigenetic data from postmortem brain studies. We apply it to find cell-specific differentially methylated regions between prefrontal cortex and hippocampus. We demonstrate the utility of the method on both Infinium 450k and CHARM data.
Original language | English (US) |
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Article number | R94 |
Journal | Genome biology |
Volume | 14 |
Issue number | 8 |
DOIs | |
State | Published - Aug 30 2013 |
Keywords
- Brain Region
- Cell-Type Heterogeneity
- DNA Methylation
- Deconvolution
- Differentially Methylated Region
- Epigenetics
- Fluorescence Activated Cell Sorting
- Glia
- Neun
- Neuron
- Postmortem Brain
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Genetics
- Cell Biology