Calculating of membership values for new data based on existing clustering

Description

Function that calculates the membership values of genes based on provided data and existing clustering

Usage

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membership(x,clusters,m)

Arguments

x

expression vector or expression matrix

clusters

cluster centroids from existing clustering

m

fuzzification parameter

Value

Matrix of membership values for new genes

Note

This function calculates membership values for new data based on existing cluster centroids and fuzzification parameter. It can be useful, for instance, when comparing two time series, to assess whether the same gene in the different time series changes its cluster association.

Author(s)

Matthias E. Futschik (http://www.sysbiolab.eu)

Examples

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if (interactive()){
 data(yeast)
 yeastF <- filter.NA(yeast)
 yeastF <- fill.NA(yeastF) # for illustration only; rather use knn method
 yeastF <- standardise(yeastF)
 
 cl <- mfuzz(yeastF,c=20,m=1.25)

 m <- 1.25
 clusters <- cl[[1]]
 x <- matrix(rnorm(2*17),nrow=2) # new expression matrix with two genes 
 mem.tmp <- membership(x,clusters=clusters,m=m) #membership values  
}

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