Package for noise-robust soft clustering of gene expression time-series data (including a graphical user interface)
|Author||Matthias Futschik <firstname.lastname@example.org>|
|Date of publication||None|
|Maintainer||Matthias Futschik <email@example.com>|
acore: Extraction of alpha cores for soft clusters
cselection: Repeated soft clustering for detection of empty clusters for...
Dmin: Calculation of minimum centroid distance for a range of...
fill.NA: Replacement of missing values
filter.NA: Filtering of genes based on number of non-available...
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...
mestimate: Estimate for optimal fuzzifier m
mfuzz: Function for soft clustering based on fuzzy c-means.
mfuzzColorBar: Plots a colour bar
Mfuzzgui: Graphical user interface for Mfuzz package
mfuzz.plot: Plotting results for soft clustering
mfuzz.plot2: Plotting results for soft clustering with additional options
overlap: Calculation of the overlap of soft clusters
overlap.plot: Visualisation of cluster overlap and global clustering...
partcoef: Calculation of the partition coefficient matrix for soft...
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...
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