DMC_identification: The DMC identification function

Description

A function to identify the most differentially methylated clusters from \(K\) clusters.

Usage

DMC_identification(
  object,
  data,
  CpG_site_list,
  threshold = 0.65,
  metric = "AUC"
)

Value

The function returns a dataframe of CpG sites and methylation values identified to belong to the most differentially methylated clusters

Arguments

object: A betaclust object
data: A dataframe of dimension \(C \times NR\) containing methylation values for \(C\) CpG sites from \(R\) samples collected from \(N\) patients which was passed as an argument to the betaclust function.
CpG_site_list: The IlmnID of all the CpG sites analysed by betaclust function.
threshold: The threshold value/s for selecting the most differentially methylated clusters, default= 0.65
metric: The metric (AUC or WD selected). default="AUC"

Details

This function selects the most diffentially methylated clusters based on AUC and WD metric calculated and returns the CpG sites belonging to those clusters.

Examples

Run this code

# \donttest{
my.seed <- 190
M <- 3
N <- 4
R <- 2
data_output <- betaclust(pca.methylation.data[1:30,2:9], M, N, R,
            model_names = "K.R",
            parallel_process = FALSE, seed = my.seed)
dmc_df <-DMC_identification(data_output,pca.methylation.data[1:30,2:9],
pca.methylation.data[1:30,1],
 threshold = 0.65, metric = "AUC")

# }