DMRcate-package: DMR calling from bisulfite sequencing and Illumina array data

In timpeters82/DMRcate-devel: Methylation array and sequencing spatial analysis methods

DMR calling from bisulfite sequencing and Illumina array data

Description

De novo identification and extraction of differentially methylated regions (DMRs) in the human genome using Illumina array and bisulfite sequencing data. DMRcate extracts and annotates differentially methylated regions (DMRs) using a kernel-smoothed estimate. Functions are provided for filtering probes possibly confounded by SNPs and cross-hybridisation. Includes GRanges generation and plotting functions.

Author(s)

Tim J. Peters <[e-mail]>

References

Peters TJ, Buckley MJ, Statham A, Pidsley R, Samaras K, Lord RV, Clark SJ and Molloy PL. De novo identification of differentially methylated regions in the human genome. Epigenetics & Chromatin 2015, 8:6, doi:10.1186/1756-8935-8-6

Peters TJ, Buckley MJ, Chen Y, Smyth GK, Goodnow CC and Clark SJ. Calling differentially methylated regions from whole genome bisulphite sequencing with DMRcate. Nucleic Acids Research 2021, 49(19):e109. doi:10.1093/nar/gkab637.

Examples

library(ExperimentHub)
library(limma)
eh <- ExperimentHub()
FlowSorted.Blood.EPIC <- eh[["EH1136"]]
tcell <- FlowSorted.Blood.EPIC[,colData(FlowSorted.Blood.EPIC)$CD4T==100 |
                                colData(FlowSorted.Blood.EPIC)$CD8T==100]
detP <- minfi::detectionP(tcell)
remove <- apply(detP, 1, function (x) any(x > 0.01))
tcell <- tcell[!remove,]
tcell <- minfi::preprocessFunnorm(tcell)
#Subset to chr2 only
tcell <- tcell[seqnames(tcell) == "chr2",]
tcellms <- minfi::getM(tcell)
tcellms.noSNPs <- rmSNPandCH(tcellms, dist=2, mafcut=0.05)
tcell$Replicate[tcell$Replicate==""] <- tcell$Sample_Name[tcell$Replicate==""]
tcellms.noSNPs <- avearrays(tcellms.noSNPs, tcell$Replicate)
tcell <- tcell[,!duplicated(tcell$Replicate)]
tcell <- tcell[rownames(tcellms.noSNPs),]
colnames(tcellms.noSNPs) <- colnames(tcell)
assays(tcell)[["M"]] <- tcellms.noSNPs
assays(tcell)[["Beta"]] <- minfi::ilogit2(tcellms.noSNPs)
type <- factor(tcell$CellType)
design <- model.matrix(~type) 
myannotation <- cpg.annotate("array", tcell, 
                             arraytype = "EPICv1", analysis.type="differential",
                             design=design, coef=2)
dmrcoutput <- dmrcate(myannotation, lambda=1000, C=2)
results.ranges <- extractRanges(dmrcoutput, genome = "hg19")
groups <- c(CD8T="magenta", CD4T="forestgreen")
cols <- groups[as.character(type)]
DMR.plot(ranges=results.ranges, dmr=1, 
         CpGs=minfi::getBeta(tcell), what="Beta", 
         arraytype = "EPICv1", phen.col=cols, genome="hg19")

timpeters82/DMRcate-devel documentation built on Oct. 2, 2024, 10:33 a.m.