Installation | Introduction | Walk through | Prerequisites | Loading the data | Transforming the data | Applying the joint mixture model to identify DMCs and DEGs | Plotting the conditional probabilities estimated for each chromosome | Plotting the estimated posterior probability of the gene belonging to the K clusters

Installation | Introduction | Walk through | Prerequisites | Loading the data | Loading the methylation and annotation data | The betaHMM workflow | Model parameter estimation | Summary of model parameters | DMC identification | Summary of the DMCs identified | Plot the density estimates of the model parameter estimates | DMR identification from DMCs identified | Summary of the DMRs identified | Plot to visualise the DMCs and DMRs | Threshold identification in DNA samples belonging to a specific condition | Plotting the results from threshold identification function

Introduction | Walk through | Prerequisites | Loading the data | Identifying methylation thresholds in a DNA sample | Summary statistics of the clustering solution | Plotting the information criterion values of all models | Thresholds objectively inferred from the clustering solution | Plotting the density estimates of the clustering solution | Plotting the uncertainties in the clustering solution | Identifying DMCs between R = 2 samples | AUC and WD metrics for finding similarities in the R cumulative distributions in each of the K clusters | Plotting the uncertainty in the clustering solution | Retrieving the most differentially methylated CpG sites | Plotting the empirical cumulative distribution function | References