DMRcate-package {DMRcate} | R Documentation |
De novo identification and extraction of differentially
methylated regions (DMRs) in the human genome using array and sequencing
data. DMRcate
extracts and annotates differentially methylated regions
(DMRs) using an array-bias corrected smoothed estimate. Functions are
provided for filtering probes possibly confounded by SNPs and
cross-hybridisation. Includes GRanges generation and plotting functions.
Tim J. Peters <t.peters@garvan.org.au>
Peters T.J., Buckley M.J., Statham, A., Pidsley R., Samaras K., Lord R.V., Clark S.J. and Molloy P.L. De novo identification of differentially methylated regions in the human genome. Epigenetics & Chromatin 2015, 8:6, doi:10.1186/1756-8935-8-6
data(dmrcatedata) myMs <- logit2(myBetas) myMs.noSNPs <- rmSNPandCH(myMs, dist=2, mafcut=0.05) patient <- factor(sub("-.*", "", colnames(myMs))) type <- factor(sub(".*-", "", colnames(myMs))) design <- model.matrix(~patient + type) myannotation <- cpg.annotate("array", myMs.noSNPs, what="M", arraytype = "450K", analysis.type="differential", design=design, coef=39) dmrcoutput <- dmrcate(myannotation, lambda=1000, C=2) results.ranges <- extractRanges(dmrcoutput, genome = "hg19") groups <- c(Tumour="magenta", Normal="forestgreen") cols <- groups[as.character(type)] samps <- c(1:6, 38+(1:6)) DMR.plot(ranges=results.ranges, dmr=1, CpGs=myBetas, phen.col=cols, genome="hg19", samps=samps)