APResult-class {apcluster} | R Documentation |

## Class "APResult"

### Description

S4 class for storing results of affinity propagation
clustering. It extends the class `ExClust`

.

### Objects

Objects of this class can be created by calling `apcluster`

or `apclusterL`

for a given similarity matrix or calling
one of these procedures with a data set and a similarity measure.

### Slots

The following slots are defined for APResult objects. Most names are taken from Frey's and Dueck's original Matlab package:

`sweeps`

:number of times leveraged clustering ran with different subsets of samples

`it`

:number of iterations the algorithm ran

`p`

:input preference (either set by user or computed by

`apcluster`

or`apclusterL`

)`netsim`

:final total net similarity, defined as the sum of

`expref`

and`dpsim`

(see below)`dpsim`

:final sum of similarities of data points to exemplars

`expref`

:final sum of preferences of the identified exemplars

`netsimLev`

:total net similarity of the individual sweeps for leveraged clustering; only available for leveraged clustering

`netsimAll`

:vector containing the total net similarity for each iteration; only available if

`apcluster`

was called with`details=TRUE`

`exprefAll`

:vector containing the sum of preferences of the identified exemplars for each iteration; only available if

`apcluster`

was called with`details=TRUE`

`dpsimAll`

:vector containing the sum of similarities of data points to exemplars for each iteration; only available if

`apcluster`

was called with`details=TRUE`

`idxAll`

:matrix with sample-to-exemplar indices for each iteration; only available if

`apcluster`

was called with`details=TRUE`

### Extends

Class `"ExClust"`

, directly.

### Methods

- plot
`signature(x="APResult")`

: see`plot-methods`

- plot
`signature(x="ExClust", y="matrix")`

: see`plot-methods`

- heatmap
`signature(x="ExClust")`

: see`heatmap-methods`

- heatmap
`signature(x="ExClust", y="matrix")`

: see`heatmap-methods`

- show
`signature(object="APResult")`

: see`show-methods`

- labels
`signature(object="APResult")`

: see`labels-methods`

- cutree
`signature(object="APResult")`

: see`cutree-methods`

- length
`signature(x="APResult")`

: gives the number of clusters.- sort
`signature(x="ExClust")`

: see`sort-methods`

- as.hclust
`signature(x="ExClust")`

: see`coerce-methods`

- as.dendrogram
`signature(object="ExClust")`

: see`coerce-methods`

### Accessors

In the following code snippets, `x`

is an `APResult`

object.

- [[
`signature(x="APResult", i="index", j="missing")`

:`x[[i]]`

returns the i-th cluster as a list of indices of samples belonging to the i-th cluster.- [
`signature(x="APResult", i="index", j="missing", drop="missing")`

:`x[i]`

returns a list of integer vectors with the indices of samples belonging to this cluster. The list has as many components as the argument`i`

has elements. A list is returned even if`i`

is a single integer.- similarity
`signature(x="APResult")`

: gives the similarity matrix.

### Author(s)

Ulrich Bodenhofer, Andreas Kothmeier & Johannes Palme apcluster@bioinf.jku.at

### References

http://www.bioinf.jku.at/software/apcluster/

Bodenhofer, U., Kothmeier, A., and Hochreiter, S. (2011)
APCluster: an R package for affinity propagation clustering.
*Bioinformatics* **27**, 2463-2464.
DOI: doi:10.1093/bioinformatics/btr406.

Frey, B. J. and Dueck, D. (2007) Clustering by passing messages
between data points. *Science* **315**, 972-976.

### See Also

`apcluster`

, `apclusterL`

,
`show-methods`

, `plot-methods`

,
`labels-methods`

, `cutree-methods`

### Examples

```
## create two Gaussian clouds
cl1 <- cbind(rnorm(100, 0.2, 0.05), rnorm(100, 0.8, 0.06))
cl2 <- cbind(rnorm(50, 0.7, 0.08), rnorm(50, 0.3, 0.05))
x <- rbind(cl1, cl2)
## compute similarity matrix (negative squared Euclidean)
sim <- negDistMat(x, r=2)
## run affinity propagation
apres <- apcluster(sim, details=TRUE)
## show details of clustering results
show(apres)
## plot information about clustering run
plot(apres)
## plot clustering result
plot(apres, x)
## plot heatmap
heatmap(apres, sim)
```

*apcluster*version 1.4.11 Index]