calcInform: Function calculates the informativeness metric (average MSS)...

In attract: Methods to Find the Gene Expression Modules that Represent the Drivers of Kauffman's Attractor Landscape

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)

attract documentation built on Nov. 8, 2020, 8:04 p.m.