Soft clustering of time series gene expression data


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Documentation for package `Mfuzz' version 1.0.0

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acore Extraction of alpha cores for soft clusters
cselection Repeated soft clustering for detection of empty 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
mfuzz Function for soft clustering based on fuzzy c-means.
mfuzz.plot Plotting results for soft clustering
mfuzzColorBar Plots a colour bar
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
top.count Determines the number for which each gene has highest membership value in all cluster
yeast Gene expression data of the yeast cell cylce