unsupervised_clustering-omics_array-numeric-numeric-method: Cluster a omics_array object: performs the clustering.

In fbertran/Patterns: Deciphering Biological Networks with Patterned Heterogeneous Measurements

Cluster a omics_array object: performs the clustering.

Description

Based on soft clustering performed by the Mfuzz package.

Usage

## S4 method for signature 'omics_array,numeric,numeric'
unsupervised_clustering(
  M1,
  clust,
  mestim,
  M2 = NULL,
  data_log = TRUE,
  screen = NULL,
  heatmap = TRUE,
  new.window = TRUE
)

Arguments

M1	Object of omics_array class.
clust	Number of clusters.
mestim	Fuzzification parameter.
M2	[NULL] Object of omics_array class,
data_log	[TRUE] Should data be logged?
screen	[NULL] Specify 'mfrow' parameter.
heatmap	[TRUE] Plot heatmaps?
new.window	[TRUE] Use new window?

Value

An object of class omics_array with the group slot updated by groups deduced from the soft clustering result.

Author(s)

Bertrand Frederic, Myriam Maumy-Bertrand.

Examples

if(require(CascadeData)){
data(micro_S, package="CascadeData")
M<-as.omics_array(micro_S[51:100,],1:4,6)
mc<-unsupervised_clustering_auto_m_c(M)
MwithGrp=unsupervised_clustering(M, 4, mc$m, screen=NULL, heatmap=FALSE, new.window = FALSE)
# Other options
unsupervised_clustering(M, 4, mc$m, screen=c(2,2), heatmap=TRUE, new.window = FALSE)
# Plot the clusters
plot(MwithGrp)
}

fbertran/Patterns documentation built on Dec. 8, 2022, 8:48 p.m.