deltak: Function to calculate the change in the area under the curve...

In clusterCons: Consensus Clustering using Multiple Algorithms and Parameters

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);

clusterCons documentation built on March 18, 2022, 5:16 p.m.