R: Hierarchical Clustering of a Consensus Matrix

consensushc {NMF} | R Documentation

## Hierarchical Clustering of a Consensus Matrix

### Description

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

### Usage

      consensushc(object, ...)

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

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

### Arguments

`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.

### Value

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

### Methods

consensushc

  `signature(object = "matrix")`: Workhorse method for matrices.

consensushc

  `signature(object = "NMF")`: Compute the hierarchical clustering on the connectivity matrix of `object`.

consensushc

  `signature(object = "NMFfitX")`: Compute the hierarchical clustering on the consensus matrix of `object`, or on the connectivity matrix of the best fit in `object`.

[Package NMF version 0.21.0 Index]