Mfuzz

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

Replacement of missing values

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

Plotting results for k-means clustering

Calculating of membership values for new data based on existing clustering

Estimate for optimal fuzzifier m

Function for soft clustering based on fuzzy c-means.

Plotting results for soft clustering

Plotting results for soft clustering with additional options

Plots a colour bar

Calculation of the overlap of soft clusters

Visualisation of cluster overlap and global clustering structure

Calculation of the partition coefficient matrix for soft clustering

Randomisation of data

Standardization of expression 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

Gene expression data of the yeast cell cycle as table