calcInform {attract} | R Documentation |
Function calculates the informativeness metric (average MSS) for a set of cluster assignments.
calcInform(exprs.dat, cl, class.vector)
exprs.dat |
a |
cl |
a |
class.vector |
a |
This function is also called internally by findSynexprs
.
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).
Jessica Mar
Mar, J., C. Wells, and J. Quackenbush, Defining an Informativeness Metric for Clustering Gene Expression Data. to appear, 2010.
## 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)