unsupervised_clustering_auto_m_c,omics_array-method | R Documentation |
Based on soft clustering performed by the Mfuzz package.
## 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 )
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. |
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 |
Bertrand Frederic, Myriam Maumy-Bertrand.
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) }
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