Predicting Disease Progression Based on Methylation Correlated Blocks using Ensemble Models


[Up] [Top]

Documentation for package ‘EnMCB’ version 1.19.0

Help Pages

anno_matrix IlluminaHumanMethylation450kanno
as.data.frame.ridgemat data frame ridge matrix
as.ridgemat ridge matrix
CompareMCB Compare multiple methylation correlated blocks lists
create_demo create demo matrix
demo_data Expression matrix of demo dataset.
demo_MCBinformation MCB information.
demo_survival_data Survival data of demo dataset.
DiffMCB Differential expressed methylation correlated blocks
draw_survival_curve draw survival curve
ensemble_model Trainging stacking ensemble model for Methylation Correlation Block
ensemble_prediction fitting function using stacking ensemble model for Methylation Correlation Block
fast_roc_calculation Fast calculation of AUC for ROC using parallel strategy
IdentifyMCB Identification of methylation correlated blocks
IdentifyMCB_parallel Identification of methylation correlated blocks with parallel algorithm
metricMCB Calculation of the metric matrix for Methylation Correlation Block
metricMCB.cv Calculation of model AUC for Methylation Correlation Blocks using cross validation
multi_coxph multivariate survival analysis using coxph
predict.mcb.coxph.penal predict coxph penal using MCB
pre_process_methylation Preprocess the Beta value matrix
univ_coxph univariate and multivariate survival analysis using coxph