consensushc: Hierarchical Clustering of a Consensus Matrix
In renozao/NMF: Algorithms and Framework for Nonnegative Matrix Factorization (NMF)

Description Usage Arguments Value Methods (by generic)

The function consensushc computes the hierarchical clustering of a consensus matrix, using the matrix itself as a similarity matrix and average linkage. It is

consensushc(object, ...)

## S4 method for signature 'matrix'
consensushc(object, method = "average", dendrogram = TRUE)

## S4 method for signature 'NMF'
consensushc(object, ...)

## S4 method for signature 'NMFfitX'
consensushc(object, what = c("consensus", "fit"), ...)

`object`	a matrix or an `NMFfitX` object, as returned by multiple NMF runs.
`...`	extra arguments passed to next method calls
`method`	linkage method passed to `hclust`.
`dendrogram`	a logical that specifies if the result of the hierarchical clustering (en `hclust` object) should be converted into a dendrogram. Default value is `TRUE`.
`what`	character string that indicates which matrix to use in the computation.

an object of class dendrogram or hclust depending on the value of argument dendrogram.

consensushc(object = matrix): Workhorse method for matrices.
consensushc(object = NMF): Compute the hierarchical clustering on the connectivity matrix of object.
consensushc(object = NMFfitX): Compute the hierarchical clustering on the consensus matrix of object, or on the connectivity matrix of the best fit in object.