acore |
Extraction of alpha cores for soft clusters |
cselection |
Repeated soft clustering for detection of empty clusters for estimation of optimised number of clusters |
Dmin |
Calculation of minimum centroid distance for a range of cluster numbers for estimation of optimised number of clusters |
fill.NA |
Replacement of missing values |
filter.NA |
Filtering of genes based on number of non-available expression values. |
filter.std |
Filtering of genes based on their standard deviation. |
kmeans2 |
K-means clustering for gene expression data |
kmeans2.plot |
Plotting results for k-means clustering |
membership |
Calculating of membership values for new data based on existing clustering |
mestimate |
Estimate for optimal fuzzifier m |
mfuzz |
Function for soft clustering based on fuzzy c-means. |
mfuzz.plot |
Plotting results for soft clustering |
mfuzz.plot2 |
Plotting results for soft clustering with additional options |
mfuzzColorBar |
Plots a colour bar |
Mfuzzgui |
Graphical user interface for Mfuzz package |
overlap |
Calculation of the overlap of soft clusters |
overlap.plot |
Visualisation of cluster overlap and global clustering structure |
partcoef |
Calculation of the partition coefficient matrix for soft clustering |
randomise |
Randomisation of data |
standardise |
Standardization of microarray data for clustering. |
standardise2 |
Standardization in regards to selected time-point |
table2eset |
Conversion of table to Expression set object. |
top.count |
Determines the number for which each gene has highest membership value in all cluster |
yeast |
Gene expression data of the yeast cell cycle |
yeast.table |
Gene expression data of the yeast cell cycle as table |
yeast.table2 |
Gene expression data of the yeast cell cycle as table |