## ---- eval=FALSE---------------------------------------------------------
## source("http://bioconductor.org/biocLite.R")
## biocLite(MethylMix)

## ---- eval=FALSE---------------------------------------------------------
## cancerSite <- "OV"
## targetDirectory <- paste0(getwd(), "/")
## GetData(cancerSite, targetDirectory)

## ---- eval=FALSE---------------------------------------------------------
## cancerSite <- "OV"
## targetDirectory <- paste0(getwd(), "/")
## 
## library(doParallel)
## cl <- makeCluster(5)
## registerDoParallel(cl)
## GetData(cancerSite, targetDirectory)
## stopCluster(cl)

## ---- eval=FALSE, tidy=TRUE----------------------------------------------
## cancerSite <- "OV"
## targetDirectory <- paste0(getwd(), "/")
## 
## cl <- makeCluster(5)
## registerDoParallel(cl)
## 
## # Downloading methylation data
## METdirectories <- Download_DNAmethylation(cancerSite, targetDirectory)
## # Processing methylation data
## METProcessedData <- Preprocess_DNAmethylation(cancerSite, METdirectories)
## # Saving methylation processed data
## saveRDS(METProcessedData, file = paste0(targetDirectory, "MET_", cancerSite, "_Processed.rds"))
## 
## # Downloading gene expression data
## GEdirectories <- Download_GeneExpression(cancerSite, targetDirectory)
## # Processing gene expression data
## GEProcessedData <- Preprocess_GeneExpression(cancerSite, GEdirectories)
## # Saving gene expression processed data
## saveRDS(GEProcessedData, file = paste0(targetDirectory, "GE_", cancerSite, "_Processed.rds"))
## 
## # Clustering probes to genes methylation data
## METProcessedData <- readRDS(paste0(targetDirectory, "MET_", cancerSite, "_Processed.rds"))
## res <- ClusterProbes(METProcessedData[[1]], METProcessedData[[2]])
## 
## # Putting everything together in one file
## toSave <- list(METcancer = res[[1]], METnormal = res[[2]], GEcancer = GEProcessedData[[1]], GEnormal = GEProcessedData[[2]], ProbeMapping = res$ProbeMapping)
## saveRDS(toSave, file = paste0(targetDirectory, "data_", cancerSite, ".rds"))
## 
## stopCluster(cl)

## ---- tidy=TRUE----------------------------------------------------------
library(MethylMix)
library(doParallel)
data(METcancer)
data(METnormal)
data(GEcancer)
head(METcancer[, 1:4])
head(METnormal)
head(GEcancer[, 1:4])

## ---- tidy=TRUE, warning=F-----------------------------------------------
MethylMixResults <- MethylMix(METcancer, GEcancer, METnormal)

## ---- tidy=TRUE, eval=FALSE----------------------------------------------
## library(doParallel)
## cl <- makeCluster(5)
## registerDoParallel(cl)
## MethylMixResults <- MethylMix(METcancer, GEcancer, METnormal)
## stopCluster(cl)

## ---- tidy=TRUE----------------------------------------------------------
MethylMixResults$MethylationDrivers
MethylMixResults$NrComponents
MethylMixResults$MixtureStates
MethylMixResults$MethylationStates[, 1:5]
MethylMixResults$Classifications[, 1:5]
# MethylMixResults$Models

## ---- tidy=TRUE, eval=F--------------------------------------------------
## # Plot the most famous methylated gene for glioblastoma
## plots <- MethylMix_PlotModel("MGMT", MethylMixResults, METcancer)
## plots$MixtureModelPlot

## ---- tidy=TRUE, eval=F--------------------------------------------------
## # Plot MGMT also with its normal methylation variation
## plots <- MethylMix_PlotModel("MGMT", MethylMixResults, METcancer, METnormal = METnormal)
## plots$MixtureModelPlot

## ---- tidy=TRUE, eval=F--------------------------------------------------
## # Plot a MethylMix model for another gene
## plots <- MethylMix_PlotModel("ZNF217", MethylMixResults, METcancer, METnormal = METnormal)
## plots$MixtureModelPlot

## ---- tidy=TRUE, eval=F--------------------------------------------------
## # Also plot the inverse correlation with gene expression (creates two separate plots)
## plots <- MethylMix_PlotModel("MGMT", MethylMixResults, METcancer, GEcancer, METnormal)
## plots$MixtureModelPlot
## plots$CorrelationPlot

## ---- eval = FALSE, tidy=TRUE--------------------------------------------
## # Plot all functional and differential genes
## for (gene in MethylMixResults$MethylationDrivers) {
##     MethylMix_PlotModel(gene, MethylMixResults, METcancer, METnormal = METnormal)
## }

## ---- tidy=TRUE, echo = FALSE--------------------------------------------
sessionInfo()