unsupervised_clustering_auto_m_c,omics_array-method {Patterns} | R Documentation |
Cluster a omics_array object: determine optimal fuzzification parameter and number of clusters.
Description
Based on soft clustering performed by the Mfuzz package.
Usage
## S4 method for signature 'omics_array'
unsupervised_clustering_auto_m_c(
M1,
clust = NULL,
mestim = NULL,
M2 = NULL,
data_log = TRUE,
screen = NULL,
crange = NULL,
repeats = NULL,
cselect = TRUE,
dminimum = FALSE
)
Arguments
M1 |
Object of omics_array class. |
clust |
[NULL] Number of clusters. |
mestim |
[NULL] Fuzzification parameter. |
M2 |
[NULL] Object of omics_array class, |
data_log |
[TRUE] Should data be logged? |
screen |
[NULL] Specify 'screen' parameter. |
crange |
[NULL] Specify 'crange' parameter. |
repeats |
[NULL] Specify 'repeats' parameter. |
cselect |
[TRUE] Estimate 'cselect' parameter. |
dminimum |
[FALSE] Estimate 'dminimum' parameter. |
Value
m |
Estimate of the optimal fuzzification parameter. |
c |
Estimate of the optimal number of clusters. |
csearch |
More result from the cselection function of the Mfuzz package |
Author(s)
Bertrand Frederic, Myriam Maumy-Bertrand.
Examples
if(require(CascadeData)){
data(micro_S, package="CascadeData")
M<-as.omics_array(micro_S[1:100,],1:4,6)
mc<-unsupervised_clustering_auto_m_c(M)
}
[Package Patterns version 1.5 Index]