## ----echo=TRUE,warning=FALSE,results='hide'----------------------------------- #if(!requireNamespace("BiocManager", quietly = TRUE)) # install.packages("BiocManager") #BiocManager::install("EnMCB") ## ----echo=TRUE,warning=FALSE,results='hide'----------------------------------- suppressPackageStartupMessages(library(EnMCB)) methylation_dataset<-create_demo() res<-IdentifyMCB(methylation_dataset) ## ----echo=TRUE,warning=FALSE,results='hide'----------------------------------- MCB<-res$MCBinformation ## ----echo=TRUE,warning=FALSE,results='hide'----------------------------------- MCB<-MCB[MCB[,"CpGs_num"]>=5,] ## ----echo=TRUE,warning=FALSE,results='hide'----------------------------------- # sample the dataset into training set and testing set trainingset<-colnames(methylation_dataset) %in% sample(colnames(methylation_dataset),0.6*length(colnames(methylation_dataset))) testingset<-!trainingset #build the models library(survival) data(demo_survival_data) models<-metricMCB(MCB, training_set = methylation_dataset[,trainingset], Surv = demo_survival_data[trainingset], Method = "cox",ci = TRUE) #select the best onemodel<-models$best_cox_model$cox_model ## ----echo=TRUE,warning=FALSE,results='hide'----------------------------------- newcgdata<-data.frame(t(methylation_dataset[,testingset])) prediction_results<-predict(onemodel, newcgdata) ## ----echo=TRUE,warning=FALSE,results='hide'----------------------------------- # You can choose one of MCBs: select_single_one=1 em<-ensemble_model(t(MCB[select_single_one,]), training_set=methylation_dataset[,trainingset], Surv_training=demo_survival_data[trainingset]) ## ----echo=TRUE,warning=FALSE,results='hide'----------------------------------- em_prediction_results<-ensemble_prediction(ensemble_model = em, prediction_data = methylation_dataset[,testingset]) ## ----echo=TRUE---------------------------------------------------------------- sessionInfo()