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Mfuzz (version 2.32.0)

Soft clustering of time series gene expression data

Description

Package for noise-robust soft clustering of gene expression time-series data (including a graphical user interface)

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Version

Version

2.32.0

License

GPL-2

Maintainer

Matthias Futschik

Last Published

February 15th, 2017

Functions in Mfuzz (2.32.0)

Calculating of membership values for new data based on existing clustering

Estimate for optimal fuzzifier m

K-means clustering for gene expression data

Plotting results for k-means clustering

Randomisation of data

Standardization of microarray data for clustering.

Plots a colour bar

Plotting results for soft clustering with additional options

Gene expression data of the yeast cell cycle as table

Gene expression data of the yeast cell cycle as table

Filtering of genes based on number of non-available expression values.

Filtering of genes based on their standard deviation.

Visualisation of cluster overlap and global clustering structure

Calculation of the partition coefficient matrix for soft clustering

Repeated soft clustering for detection of empty clusters for estimation of optimised number of clusters

Extraction of alpha cores for soft clusters

Function for soft clustering based on fuzzy c-means.

Plotting results for soft clustering

Determines the number for which each gene has highest membership value in all cluster

Gene expression data of the yeast cell cycle

Calculation of minimum centroid distance for a range of cluster numbers for estimation of optimised number of clusters

Replacement of missing values

Graphical user interface for Mfuzz package

Calculation of the overlap of soft clusters

Standardization in regards to selected time-point

Conversion of table to Expression set object.