DMC_identification {betaclust} | R Documentation |
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 |
CpG_site_list |
The IlmnID of all the CpG sites analysed by
|
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
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")