deltak {clusterCons}

Function to calculate the change in the area under the curve (AUC) across a range of cluster number values

Description

This function takes an "auc" class object and calculates the difference in AUC value by cluster number (called delta-K). Peaks in delta-K coincide with the cluster numbers that are most robust and provide estimates for the optimal cluster number.

Usage

deltak(x)

Arguments

x

a valid "auc" class object, normally provided as a result from the aucs function.

Value

deltak(x) returns a data.frame with the following variables.

k

cluster number as a factor

a

algorithm identifier as a factor

dk

the delta-K value

Author(s)

Dr. T. Ian Simpson [e-mail]

References

Merged consensus clustering to assess and improve class discovery with microarray data. Simpson TI, Armstrong JD and Jarman AP. BMC Bioinformatics 2010, 11:590.

See Also

Also see the aucs function.

Examples

#load a test cluscomp result set
data(testcmr)

#calculate all of the AUC values from the \code{cluscomp} result for algorithm 'kmeans'
kmeanscmr <- testcmr[grep('kmeans',names(testcmr))];
acs <- aucs(kmeanscmr);

#calculate the delta-K values
dks <- deltak(acs);