# K-means clustering for gene expression data

### Description

This function is a wrapper function for
`kmeans`

of the `e1071`

package. It performs
hard clustering of genes based on their expression values using
the k-means algorithm.

### Usage

1 | ```
kmeans2(eset,k,iter.max=100)
``` |

### Arguments

`eset` |
object of the class |

`k` |
number of clusters. |

`iter.max` |
maximal number of iterations. |

### Value

An list of clustering components (see
`kmeans`

).

### Author(s)

Matthias E. Futschik (http://itb.biologie.hu-berlin.de/~futschik)

### See Also

`kmeans`

### Examples

1 2 3 4 5 6 7 8 9 10 11 | ```
if (interactive()){
data(yeast)
# Data pre-processing
yeastF <- filter.NA(yeast)
yeastF <- fill.NA(yeastF)
yeastF <- standardise(yeastF)
# K-means clustering and visualisation
kl <- kmeans2(yeastF,k=20)
kmeans2.plot(yeastF,kl=kl,mfrow=c(2,2))
}
``` |