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HiBED

Hierarchical deconvolution for extensive cell type resolution in the human brain using DNA methylation. The HiBED deconvolution estimates proportions up to 7 cell types (GABAergic neurons, glutamatergic neurons, astrocytes, microglial cells, oligodendrocytes, endothelial cells, and stromal cells) in bulk brain tissues.

Figure1

Installation

devtools::install_github("SalasLab/HiBED")

Load package

library(HiBED)

Deconvolution function

?HiBED_deconvolution

Example

library(FlowSorted.Blood.EPIC)
library(FlowSorted.DLPFC.450k)
library(minfi)
Mset<-preprocessRaw(FlowSorted.DLPFC.450k)
Examples_Betas<-getBeta(Mset)
HiBED_result<-HiBED_deconvolution(Examples_Betas, h=2)
head(HiBED_result)

EPICv2 Solution

if you're having trouble dowloading v2 annotation files, you can find them at

library(HiBED)
library(minfi)
library(IlluminaHumanMethylationEPICv2anno.20a1.hg38)
library(IlluminaHumanMethylationEPICv2manifest)

dir should be the folder containing EPICv2 IDATs

v2_RGset = read.metharray.exp("dir",recursive = TRUE) 
annotation(v2_RGset)["array"] = "IlluminaHumanMethylationEPICv2" #Update annotation files for v2
annotation(v2_RGset)["annotation"] = "20a1.hg38"
v2_MSet <-preprocessNoob(v2_RGset)
v2_Betas<-getBeta(v2_MSet)
v2_Betas<- sesame::betasCollapseToPfx(v2_Betas)
HiBED_deconvolution(v2_Betas, h=2)

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