clusterComp: Estimate Microarray Cluster Stability
In clusterStab: Compute cluster stability scores for microarray data

Description Usage Arguments Details Value Author(s) References Examples

This function estimates the stability of clustering solutions using microarray data. Currently only agglomerative hierarchical clustering is supported.

## S4 method for signature 'ExpressionSet'
clusterComp(object, cl, seednum = NULL, B = 100,
sub.frac = 0.8, method = "ave", distmeth = "euclidean", adj.score = FALSE)
## S4 method for signature 'matrix'
clusterComp(object, cl, seednum = NULL, B = 100,
sub.frac = 0.8, method = "ave", distmeth = "euclidean", adj.score = FALSE)

`object`	Either a matrix or `ExpressionSet`
`cl`	The number of clusters. This may be estimated using `benhur`
`seednum`	A value to pass to `set.seed`, which will allow for exact reproducibility at a later date.
`B`	The number of permutations.
`sub.frac`	The proportion of genes to use in each subsample. This value should be in the range of 0.75 - 0.85 for best results
`method`	The linkage method to pass to `hclust`. Valid values include "average", "centroid", "ward", "single", "mcquitty", or "median".
`distmeth`	The distance method to use. Valid values include "euclidean" and "pearson", where pearson implies 1-pearson correlation.
`adj.score`	Boolean. Should the stability scores be adjusted for cluster size? Defaults to `FALSE`.

This function estimates the stability of a clustering solution by repeatedly subsampling the data and comparing the cluster membership of the subsamples to the original clusters.

The output from this function is an object of class clusterComp. See the clusterComp-class man page for more information.

James W. MacDonald <jmacdon@u.washington.edu>

A. Ben-Hur, A. Elisseeff and I. Guyon. A stability based method for discovering structure in clustered data. Pacific Symposium on Biocomputing, 2002. Smolkin, M. and Ghosh, D. (2003). Cluster stability scores for microarray data in cancer studies . BMC Bioinformatics 4, 36 - 42.