# #——选项,回声= FALSE ----------------------------------------------- 选项(宽度= 72)# #——mpload消息= FALSE,缓存= TRUE ---------------------------------- 库(methylPipe)库(BSgenome.Hsapiens.UCSC.hg18) # #——methcall消息= FALSE,缓存= TRUE -------------------------------- file_loc < -系统。file('extdata'， 'test_methcall'， package='methylPipe')调用(files_location=file_loc, output_folder=tempdir()， no_overlap=TRUE，读取。上下文=“CpG Nproc = 1) # #——bsprepare消息= FALSE,缓存= TRUE ------------------------------- file_loc < -系统。file('extdata'， 'H1_chr20_CG_10k.txt'， package='methylPipe') #BSprepare(files_location=file_loc,output_folder=file_loc, tabix="/path-to-tabix/") uncov_GR <- GRanges(Rle('chr20')， IRanges(c(14350,69251,84185)， c(18349,73250,88184))文件(“extdata”、“H1_chr20_CG_10k_tabix_out.txt.gz”,包= methylPipe) H1.db <——BSdata(文件= H1data uncov = uncov_GR org = Hsapiens) H1.db # #——bsdataset消息= TRUE,缓存= TRUE -------------------------------- IMR90data < -系统。file('extdata'， 'IMR90_chr20_CG_10k_tabix_out.txt.gz'， package='methylPipe') IMR90.db <- BSdata(file=IMR90data, uncov=uncov_GR, org=Hsapiens) H1.IMR90. db .gzset <- BSdataSet(org=Hsapiens, group=c(" c "，"E")， IMR90=IMR90.db, H1=H1.db) H1.IMR90. db。组# #——met1 fig.width = 6, fig.height = 5, out.width = '。85\\textwidth'，message=FALSE,cache=TRUE---- gr <- GRanges("chr20"，IRanges(1,5e5)) sres <- mCsmoothing(H1.db, gr, Scorefun='sum'， Nbins=50, plot=TRUE) ## ----desstats,fig.width=6,fig.height=5,out.width='。85 \ \ textwidth、消息= FALSE fig.keep =“所有”,无花果。显示=“黑名单”,缓存= TRUE,统计数据。set <- BSdataSet(org=Hsapiens, group=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. db)集,铬= " chr20 " mcClass = mCG, Nproc = 1) stats_res # #——met2消息= FALSE,缓存= TRUE ------------------------------------ gr_file < -系统。文件(“extdata”、“GR_chr20。Rdata’,包= ' methylPipe”)负载(gr_file) resmC < - mapBSdata2GRanges (GenoRanges = GR_chr20示例= H1.db上下文= CG)头(resmC [[4 ]]) ## ---- met3、消息= FALSE缓存= TRUE ------------------------------------ 通用电气。H1 < - profileDNAmetBin (GenoRanges = GR_chr20示例= H1.db mcCLASS = mCG, nbins = 3) binmC (gec.H1) [4:5], binC (gec.H1) [4:5], binrC (gec.H1) [4:5 ,] ## ---- 子集,消息= FALSE,缓存= TRUE ---------------------------------- gec1 < - gec.H1 [start (gec.H1) < 153924] gec2 <——gec.H1(开始(gec.H1) > 153924) # #——gecset消息= FALSE,缓存= TRUE ---------------------------------- gecIMR_file < -系统。文件(“extdata”、“gec.IMR90。Rdata'， package='methylPipe') load(gecIMR_file) gel <- GElist(gecIMR90=gec. zip)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()