memrob: Calculate the membership robustness from consensus clustering...

In clusterCons: Consensus Clustering using Multiple Algorithms and Parameters

Calculate the membership robustness from consensus clustering results

Description

This function calculates the membership robustness from a consmatrix or mergematrix class object.

Usage

memrob(x,rm)

Arguments

x	either a consmatrix or mergematrix object.
rm	(optional) if a mergematrix object is passed then you must provide a reference clustering structure to calculate cluster robustness against. These structures are stored with every consmatrix object in the 'rm' slot. You would normally select a reference matrix for a cluster number matching that of the mergematrix (see example below).

Value

Returns a list of memroblist class objects, one for each cluster, and the full membership robustness matrix as a memrobmatrix class object.

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 cluscomp, consmatrix and mergematrix.

Examples

#load cmr (consensus clustering result produced by cluscomp)
data(testcmr);

#calculate the cluster robustness of the consensus matrix for pam where k=4
mr1 <- memrob(testcmr$e1_kmeans_k4);

#show the membership robustness of cluster 1
mr1$cluster1;

#calculate the cluster robustness of the merge matrix in reference
#to the clustering structure of pam where k=4
mr2 <- memrob(testcmr$merge_k4,testcmr$e1_kmeans_k4@rm);

#plot a heatmap of the full membership robustness matrix
heatmap(mr2$resultmatrix@mrm)

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