## -----选项，echo = false --------------------------------------------------------------------------------------------------------------------------------------------------------------------选项（width = 72）## ---- mpload，message = false，cache = true ---------------------------------------------------------------------------------------------------- library(methylPipe) library(BSgenome.Hsapiens.UCSC.hg18) ## ----methcall,message=FALSE,cache=TRUE-------------------------------- file_loc <- system.file('extdata', 'test_methcall', package='methylPipe') meth.call(files_location= file_loc，output_folder = tempdir（），no_overlap = true，read.context =“ cpg”，nproc = 1）## ---- bsprepare，message = false，cache = true ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------》，output_folder = file_loc，tabix =“/to to to to to to to to-tabix/”）uncov_gr <-granges（rle（'chr20'），iranges（c（14350,69251,84185），C（18349,73250,88184））h1data <-system.file（'extdata'，'h1_chr20_cg_10k_tabix_out.txt.gz'，package ='methylPipe'）--- bsdataset，消息= true，cache = true --------------------------------- IMR90data <- system.file('extdata', 'IMR90_chr20_CG_10k_tabix_out.txt.gz', package='methylPipe'）imr90.db <-bsdata（file = imr90data，uncov = uncov_gr，org = hsapiens）h1.imr90.set <-bsdataset（org = hsapiens，group = c（“ c”，“ e”），imr90 = imr90。db，h1 = h1.db）h1.imr90.set ## ----- met1，图。width = 6，图。= true ----- gr <-granges（“ chr20”，iranges（1,5e5））sres <-mcsmoothing（h1.db，gr，gr，corcefun ='sum'，nbins = 50，plot = true）## ---- desstats，图。width = 6，图。height= 5，out.width ='。85 \\ textwidth'，message = false，figes.keep =“ all”，fig.show =“ asis”，cache，cache'= true ---- stats.sets.set <-bsdataset（org = hsapiens，group = c（“ c”，“ c”，“ c”，“ e”，“ e”），imr_1 = imr90.db，imr_2 = imr90.db， H1_1=H1.db,H1_2=H1.db) stats_res <- methstats(stats.set,chrom="chr20",mcClass='mCG', Nproc=1) stats_res ## ----met2,message=FALSE,cache=TRUE------------------------------------ gr_file <- system.file('extdata', 'GR_chr20.Rdata', package='methylPipe') load(gr_file) resmC <- mapBSdata2GRanges(GenoRanges=GR_chr20, Sample=H1.db, context='CG') head(resmC[[4]]) ## ----met3,message=FALSE,cache=TRUE------------------------------------ gec.H1 <- profileDNAmetBin(GenoRanges=GR_chr20, Sample=H1.db, mcCLASS='mCG', nbins=3) binmC(gec.H1)[4:5,] binC(gec.H1)[4:5,] binrC(gec.H1)[4:5,] ## ----subset,message=FALSE,cache=TRUE---------------------------------- gec1 <- gec.H1[start(gec.H1) < 153924] gec2 <- gec.H1[start(gec.H1) > 153924] ## ----gecset,message=FALSE,cache=TRUE---------------------------------- gecIMR_file <- system.file('extdata', 'gec.IMR90.Rdata', package='methylPipe') load(gecIMR_file) gel <- GElist(gecIMR90=gec.IMR90, gecH1=gec.H1) print(names(gel)) ## ----pmeth,fig.width=5,fig.height=5,out.width='.85\\textwidth',message=FALSE,cache=TRUE---- library(TxDb.Hsapiens.UCSC.hg18.knownGene) txdb <- TxDb.Hsapiens.UCSC.hg18.knownGene gel <- GElist(gecIMR90=gec.IMR90[1:10], gecH1=gec.H1[1:10]) plotMeth(gel, colors=c("red","blue"), datatype=c("mC","mC"), yLim=c(.025, .025), brmeth=list(IMR90=IMR90.db, H1=H1.db), mcContext="CG", transcriptDB=txdb, chr="chr20", start=14350, end=277370, org=Hsapiens) ## ----dmr1,message=FALSE,cache=TRUE------------------------------------ DMRs <- findDMR(object= H1.IMR90.set, Nproc=1, ROI=GR_chr20, MCClass='mCG', dmrSize=6, dmrBp=800) head(DMRs) ## ----dmr2,message=FALSE,cache=TRUE------------------------------------ hyper.DMRs.conso <- consolidateDMRs(DmrGR=DMRs, pvThr=0.05, GAP=100, type="hyper") hyper.DMRs.conso[1:4] ## ----info,echo=TRUE--------------------------------------------------- sessionInfo()