DMC_identification: The DMC identification function

In betaclust: A Family of Beta Mixture Models for Clustering Beta-Valued DNA Methylation Data

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"
)

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.

Value

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

See Also

beta_kr

pca.methylation.data

plot.betaclust

summary.betaclust

betaclust

Examples

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")

betaclust documentation built on Sept. 30, 2024, 9:30 a.m.