## ----eval=FALSE, engine="bash"------------------------------------------- ## source("https://bioconductor.org/biocLite.R") ## biocLite("ChAMP") ## ----eval=FALSE---------------------------------------------------------- ## source("http://bioconductor.org/biocLite.R") ## biocLite(c("minfi","ChAMPdata","Illumina450ProbeVariants.db","sva","IlluminaHumanMethylation450kmanifest","limma","RPMM","DNAcopy","preprocessCore","impute","marray","wateRmelon","goseq","plyr","GenomicRanges","RefFreeEWAS","qvalue","isva","doParallel","bumphunter","quadprog","shiny","shinythemes","plotly","RColorBrewer","DMRcate","dendextend","IlluminaHumanMethylationEPICmanifest","FEM","matrixStats")) ## ----eval=FALSE, engine="bash"------------------------------------------- ## R CMD INSTALL plotly-4.5.6.tar.gz ## ----eval=FALSE, engine="bash"------------------------------------------- ## R CMD INSTALL ChAMP_2.6.4.tar.gz ## ----eval=TRUE,message=FALSE, warning=FALSE------------------------------ library("ChAMP") ## ----eval=FALSE---------------------------------------------------------- ## testDir=system.file("extdata",package="ChAMPdata") ## myLoad <- champ.load(testDir,arraytype="450K") ## ----eval=FALSE---------------------------------------------------------- ## data(EPICSimData) ## ---- out.width = 800, fig.retina = NULL,echo=F-------------------------- knitr::include_graphics("Figure/ChAMP_Pipeline.png") ## ----eval=FALSE---------------------------------------------------------- ## champ.process(directory = testDir) ## ----eval=FALSE---------------------------------------------------------- ## myLoad <- cham.load(testDir) ## CpG.GUI() ## champ.QC() # Alternatively: QC.GUI() ## myNorm <- champ.norm() ## champ.SVD() ## # If Batch detected, run champ.runCombat() here. ## myDMP <- champ.DMP() ## DMP.GUI() ## myDMR <- champ.DMR() ## DMR.GUI() ## myBlock <- champ.Block() ## Block.GUI() ## myGSEA <- champ.GSEA() ## myEpiMod <- champ.EpiMod() ## myCNA <- champ.CNA() ## myRefFree <- champ.reffree() ## # If DataSet is Blood samples, run champ.refbase() here. ## ----eval=FALSE---------------------------------------------------------- ## # myLoad <- champ.load(directory = testDir,arraytype="EPIC") ## # We simulated EPIC data from beta value instead of .idat file, ## # but user may use above code to read .idat files directly. ## # Here we we started with myLoad. ## ## data(EPICSimData) ## CpG.GUI(arraytype="EPIC") ## champ.QC() # Alternatively QC.GUI(arraytype="EPIC") ## myNorm <- champ.norm(arraytype="EPIC") ## champ.SVD() ## # If Batch detected, run champ.runCombat() here.This data is not suitable. ## myDMP <- champ.DMP(arraytype="EPIC") ## DMP.GUI() ## myDMR <- champ.DMR() ## DMR.GUI() ## myDMR <- champ.DMR(arraytype="EPIC") ## DMR.GUI(arraytype="EPIC") ## myBlock <- champ.Block(arraytype="EPIC") ## Block.GUI(arraytype="EPIC") # For this simulation data, not Differential Methylation Block is detected. ## myGSEA <- champ.GSEA(arraytype="EPIC") ## myEpiMod <- champ.EpiMod(arraytype="EPIC") ## myRefFree <- champ.reffree() ## ## # champ.CNA(arraytype="EPIC") ## # champ.CNA() function call for intensity data, which is not included in our Simulation data. ## ----eval=FALSE---------------------------------------------------------- ## library("doParallel") ## detectCores() ## ----eval=FALSE---------------------------------------------------------- ## myLoad <- champ.load(testDir) ## ## We are not running this code here because it cost about 1 minute. ## ----eval=TRUE----------------------------------------------------------- data(testDataSet) ## ----eval=TRUE----------------------------------------------------------- myLoad$pd ## ----eval=FALSE---------------------------------------------------------- ## CpG.GUI(CpG=rownames(myLoad$beta),arraytype="450K") ## ---- out.width = 800, fig.retina = NULL,echo=F-------------------------- knitr::include_graphics("Figure/CpGGUI.png") ## ----eval=TRUE,dpi=100,fig.width=7,fig.height=4,message=FALSE------------ champ.QC() ## ----eval=FALSE---------------------------------------------------------- ## QC.GUI(CpG=rownames(myLoad$beta),arraytype="450K") ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/QCGUI.jpg") ## ----eval=FALSE---------------------------------------------------------- ## myNorm <- champ.norm(beta=myLoad$beta,arraytype="450K",cores=5) ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/BMIQ.jpg") ## ----eval=TRUE,dpi=100,fig.width=8,fig.height=8,message=FALSE,warning=FALSE---- champ.SVD(beta=myNorm,pd=myLoad$pd) ## ----eval=FALSE---------------------------------------------------------- ## myCombat <- champ.runCombat(beta=myNorm,pd=myLoad$pd,batchname=c("Slide")) ## ----eval=TRUE,warning=FALSE,message=FALSE------------------------------- myDMP <- champ.DMP(beta = myNorm,pheno=myLoad$pd$Sample_Group) ## ----eval=TRUE----------------------------------------------------------- head(myDMP) ## ----eval=FALSE---------------------------------------------------------- ## DMP.GUI(DMP=myDMP,beta=myNorm,pheno=myLoad$pd$Sample_Group) ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/DMP-1.png") ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/DMP-2.png") ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/DMP-3.png") ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/DMP-4.png") ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/DMP-5.png") ## ----eval=FALSE,message=FALSE,warning=TRUE------------------------------- ## myDMR <- champ.DMR(beta=myNorm,pheno=myLoad$pd$Sample_Group,method="Bumphunter") ## ----eval=TRUE----------------------------------------------------------- head(myDMR$DMRcateDMR) ## ----eval=FALSE---------------------------------------------------------- ## DMR.GUI(DMR=myDMR) ## # It might be a little bit slow to open DMR.GUI() because function need to extract annotation for CpGs from DMR. Might take 30 seconds. ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/DMR-1.png") ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/DMR-2.png") ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/DMR-3.png") ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/DMR-4.png") ## ----eval=FALSE---------------------------------------------------------- ## myBlock <- champ.Block(beta=myNorm,pheno=myLoad$pd$Sample_Group,arraytype="450K") ## ----eval=TRUE----------------------------------------------------------- head(myBlock$Block) ## ----eval=FALSE---------------------------------------------------------- ## Block.GUI(Block=myBlock,beta=myNorm,pheno=myLoad$pd$Sample_Group,runDMP=TRUE,compare.group=NULL,arraytype="450K") ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/Block-1.png") ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/Block-2.png") ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/Block-3.png") ## ----eval=FALSE---------------------------------------------------------- ## myGSEA <- champ.GSEA(beta=myNorm,DMP=myDMP,DMR=myDMR,arraytype="450K",adjPval=0.05) ## # myDMP and myDMR could (not must) be used directly. ## ----eval=TRUE----------------------------------------------------------- head(myGSEA$DMP) # Above is the GSEA result for differential methylation probes. head(myGSEA$DMR) # Above is the GSEA result for differential methylation regions. # Too many information may be printed, so we are not going to show the result here. ## ----eval=FALSE---------------------------------------------------------- ## myEpiMod <- champ.EpiMod(beta=myNorm,pheno=myLoad$pd$Sample_Group) ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/EpiMod.jpg") ## ----eval=FALSE---------------------------------------------------------- ## myCNA <- champ.CNA(intensity=myLoad$intensity,pheno=myLoad$pd$Sample_Group) ## ---- out.width = 800, fig.retina = NULL,echo=FALSE---------------------- knitr::include_graphics("Figure/CNAGroupPlot.jpg") ## ----eval=FALSE---------------------------------------------------------- ## myRefFree <- champ.reffree(beta=myNorm,pheno=myLoad$pd$Sample_Group) ## ----eval=TRUE----------------------------------------------------------- head(myRefFree$qvBeta) ## ----eval=FALSE---------------------------------------------------------- ## myRefBase <- champ.refbase(beta=myNorm,arraytype="450K") ## # Our test data set is not blood.