Calculation of minimum centroid distance for a range of cluster numbers for estimation of optimised number of clusters
Graphical user interface for Mfuzz package
Extraction of alpha cores for soft clusters
Repeated soft clustering for detection of empty clusters for estimation of optimised number of clusters
Filtering of genes based on number of non-available expression values.
Filtering of genes based on their standard deviation.
K-means clustering for gene expression data
Calculating of membership values for new data based on existing clustering
Function for soft clustering based on fuzzy c-means.
Plotting results for soft clustering with additional options
Calculation of the overlap of soft clusters
Visualisation of cluster overlap and global clustering structure
Calculation of the partition coefficient matrix for soft clustering
Standardization of microarray data for clustering.
Standardization in regards to selected time-point
Conversion of table to Expression set object.
Determines the number for which each gene has highest membership value in all cluster
Gene expression data of the yeast cell cycle
Gene expression data of the yeast cell cycle as table