calcInform {attract} | R Documentation

## Function calculates the informativeness metric (average MSS) for a set of cluster assignments.

### Description

Function calculates the informativeness metric (average MSS) for a set of cluster assignments.

### Usage

    calcInform(exprs.dat, cl, class.vector)

### Arguments

`exprs.dat` | a `matrix` of gene expression values.
`cl` | a `vector` of cluster assignments.
`class.vector` | a `vector` specifying the group membership of the samples.

### Details

This function is also called internally by `findSynexprs`.

### Value

A numeric value representing the average MSS value (informativeness metric) for a set of cluster assignments. For an informative cluster, the RSS values should be very small relative to those produced by the informativeness metric (the MSS values).

### Author(s)

Jessica Mar

### References

Mar, J., C. Wells, and J. Quackenbush, Defining an Informativeness Metric for Clustering Gene Expression Data. to appear, 2010.

### Examples

    ## Not run:
    library(cluster)
    data(subset.loring.eset)
    clustObj <- agnes(as.dist(1-t(cor(exprs(subset.loring.eset)))))
    cinform.vals <- NULL
    for( i in 1:10 ){
    	cinform.vals <- c(cinform.vals, calcInform(exprs(subset.loring.eset), cutree(clustObj,i), pData(subset.loring.eset)$celltype))
    }
    k <- (1:10)[cinform.vals==max(cinform.vals)]			# gives the optimal number of clusters

    ## End(Not run)

[Package attract version 1.46.0 Index]