Calculating of membership values for new data based on existing clustering
Function that calculates the membership values of genes based on provided data and existing clustering
membership(x,clusters,m)
x |
expression vector or expression matrix |
clusters |
cluster centroids from existing clustering |
m |
fuzzification parameter |
Matrix of membership values for new genes
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.
Matthias E. Futschik (http://www.sysbiolab.eu)
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
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.