sample.cluster.table: Sample-cluster table
In tgac-vumc/WECCA: Weighted clustering of array CGH data

Description Usage Arguments Value Author(s) See Also Examples

Cuts a the WECCAsc or WECCAhc generated dendrogram at a desired number of clusters. Then, produces a data.frame telling which samples belong to which cluster.

1	sample.cluster.table(cghdata.regioned, dendrogram, nclusters)

`cghdata.regioned`	A `list`-object as returned by `regioning.sc`.
`dendrogram`	Determines if and how the row dendrogram should be computed and reordered. Should be a dendrogram as returned by `WECCAsc` or `WECCAhc`.
`nclusters`	An integer with the desired number of clusters.

A data.frame with the first two columns containing the sample number and name, and the third column the cluster information.

Wessel N. van Wieringen: w.vanwieringen@vumc.nl

cutree

# generate object of class
data(WiltingCalled)

# make region data (soft and hard calls)
WiltingRegioned <- regioning(WiltingCalled)

# clustering with soft.calls
dendrogram <- WECCAsc(WiltingRegioned)

# generate a heatmap of the found clustering
WECCA.heatmap(WiltingRegioned, dendrogram)

# specify the number of clusters to be extracted from the dendrogram
nclusters <- 2
table.clusters.samples <- sample.cluster.table(WiltingRegioned, dendrogram, nclusters)