`connectivity`

is an S4 generic that computes the
connectivity matrix based on the clustering of samples
obtained from a model's `predict`

method.

The consensus matrix has been proposed by Brunet et
al. (2004) to help visualising and measuring the
stability of the clusters obtained by NMF approaches. For
objects of class `NMF`

(e.g. results of a single NMF
run, or NMF models), the consensus matrix reduces to the
connectivity matrix.

```
connectivity(object, ...)
S4 (NMF)
`connectivity`(object, no.attrib = FALSE)
consensus(object, ...)
```

- object
- an object with a suitable
`predict`

method. - ...
- extra arguments to allow extension. They are
passed to
`predict`

, except for the`vector`

and`factor`

methods. - no.attrib
- a logical that indicates if attributes
containing information about the NMF model should be
attached to the result (
`TRUE`

) or not (`FALSE`

).

a square matrix of dimension the number of samples in the model, full of 0s or 1s.

The connectivity matrix of a given partition of a set of
samples (e.g. given as a cluster membership index) is the
matrix `C`

containing only 0 or 1 entries such that:

C_{ij} = 1 if sample i belongs to the same cluster as sample j, 0 otherwise

- connectivity
`signature(object = "ANY")`

: Default method which computes the connectivity matrix using the result of`predict(x, ...)`

as cluster membership index. - connectivity
`signature(object = "factor")`

: Computes the connectivity matrix using`x`

as cluster membership index. - connectivity
`signature(object = "numeric")`

: Equivalent to`connectivity(as.factor(x))`

. - connectivity
`signature(object = "NMF")`

: Computes the connectivity matrix for an NMF model, for which cluster membership is given by the most contributing basis component in each sample. See`predict,NMF-method`

. - consensus
`signature(object = "NMFfitX")`

: Pure virtual method defined to ensure`consensus`

is defined for sub-classes of`NMFfitX`

. It throws an error if called. - consensus
`signature(object = "NMF")`

: This method is provided for completeness and is identical to`connectivity`

, and returns the connectivity matrix, which, in the case of a single NMF model, is also the consensus matrix. - consensus
`signature(object = "NMFfitX1")`

: The result is the matrix stored in slot ‘consensus’. This method returns`NULL`

if the consensus matrix is empty.See

`consensus,NMFfitX1-method`

for more details. - consensus
`signature(object = "NMFfitXn")`

: This method returns`NULL`

on an empty object. The result is a matrix with several attributes attached, that are used by plotting functions such as`consensusmap`

to annotate the plots.See

`consensus,NMFfitXn-method`

for more details.

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,

```
# clustering of random data
h <- hclust(dist(rmatrix(10,20)))
connectivity(cutree(h, 2))
```

```
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
## [1,] 1 1 0 1 1 0 0 0 0 1
## [2,] 1 1 0 1 1 0 0 0 0 1
## [3,] 0 0 1 0 0 1 1 1 1 0
## [4,] 1 1 0 1 1 0 0 0 0 1
## [5,] 1 1 0 1 1 0 0 0 0 1
## [6,] 0 0 1 0 0 1 1 1 1 0
## [7,] 0 0 1 0 0 1 1 1 1 0
## [8,] 0 0 1 0 0 1 1 1 1 0
## [9,] 0 0 1 0 0 1 1 1 1 0
## [10,] 1 1 0 1 1 0 0 0 0 1
```

```
connectivity(gl(2, 4))
```

```
## [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8]
## [1,] 1 1 1 1 0 0 0 0
## [2,] 1 1 1 1 0 0 0 0
## [3,] 1 1 1 1 0 0 0 0
## [4,] 1 1 1 1 0 0 0 0
## [5,] 0 0 0 0 1 1 1 1
## [6,] 0 0 0 0 1 1 1 1
## [7,] 0 0 0 0 1 1 1 1
## [8,] 0 0 0 0 1 1 1 1
```

```
```

`predict`