## Description

The function `cophcor`

computes the cophenetic
correlation coefficient from consensus matrix
`object`

, e.g. as obtained from multiple NMF runs.

## Usage

cophcor(object, ...)
S4 (matrix)
`cophcor`(object, linkage = "average")

## Arguments

- object
- an object from which is extracted a
consensus matrix.
- ...
- extra arguments to allow extension and passed
to subsequent calls.
- linkage
- linkage method used in the hierarchical
clustering. It is passed to
`hclust`

.

## Details

The cophenetic correlation coeffificient is based on the
consensus matrix (i.e. the average of connectivity
matrices) and was proposed by Brunet et al. (2004)
to measure the stability of the clusters obtained from
NMF.

It is defined as the Pearson correlation between the
samples' distances induced by the consensus matrix (seen
as a similarity matrix) and their cophenetic distances
from a hierachical clustering based on these very
distances (by default an average linkage is used). See
Brunet et al. (2004).

## Methods

- cophcor
`signature(object = "matrix")`

:
Workhorse method for matrices.
- cophcor
`signature(object = "NMFfitX")`

:
Computes the cophenetic correlation coefficient on the
consensus matrix of `object`

. All arguments in
`...`

are passed to the method
`cophcor,matrix`

.

## References

Brunet J, Tamayo P, Golub TR and Mesirov JP (2004).
"Metagenes and molecular pattern discovery using matrix
factorization." _Proceedings of the National Academy of
Sciences of the United States of America_, *101*(12), pp.
4164-9. ISSN 0027-8424, , .