Description Usage Arguments Details Value Author(s) See Also Examples

Calculates an ensemble of biclusters from different parameter setting of possible different bicluster algorithms.

1 2 |

`x` |
Data Matrix |

`confs` |
Matrix containing parameter sets |

`rep` |
Number of repetitions for each parameter set |

`maxNum` |
Maximum number of biclusters taken from each run |

`similar` |
Function to produce a similarity matrix of bicluster |

`thr` |
Threshold for similarity |

`simthr` |
Proportion of row column combinations in bicluster |

`subs` |
Vector of proportion of rows and columns for subsampling. Default c(1,1) means no subsampling. |

`bootstrap` |
Should bootstrap sampling be used (logical: replace=bootstrap). |

`support` |
Wich proportion of the runs must contain the bicluster to have enough support to report it (between 0 and 1). |

`combine` |
Function to combine the single bicluster only firstcome and hcl for hierarchical clustering are possible at the moment. |

`...` |
Arguments past to the combine function. |

Two different kinds (or both combined) of ensebmbling is possible. Ensemble of repeated runs or ensemble of runs on subsamples.

Return an object of class Biclust

Sebastian Kaiser [email protected]

`Biclust-class`

, `plaid.grid`

, `bimax.grid`

1 2 3 4 5 6 | ```
data(BicatYeast)
ensemble.plaid <- ensemble(BicatYeast,plaid.grid()[1:5],rep=1,maxNum=2, thr=0.5, subs = c(1,1))
ensemble.plaid
x <- binarize(BicatYeast)
ensemble.bimax <- ensemble(x,bimax.grid(),rep=10,maxNum=2,thr=0.5, subs = c(0.8,0.8))
ensemble.bimax
``` |

```
Loading required package: MASS
Loading required package: grid
Loading required package: colorspace
Loading required package: lattice
[1] "Support:"
[1] 0
[1] "Number of Bicluster:"
[1] 3 3 2 1 1
An object of class Biclust
call:
ensemble(x = BicatYeast, confs = plaid.grid()[1:5], rep = 1,
maxNum = 2, thr = 0.5, subs = c(1, 1))
Number of Clusters found: 5
First 5 Cluster sizes:
BC 1 BC 2 BC 3 BC 4 BC 5
Number of Rows: 46 71 137 11 30
Number of Columns: 4 4 6 10 7
[1] "Threshold: 0.3969381"
[1] "Support:"
[1] 0
[1] "Number of Bicluster:"
[1] 4 3 3 2 2 2 1 1 1 1 1 1 1 1
An object of class Biclust
call:
ensemble(x = x, confs = bimax.grid(), rep = 10, maxNum = 2, thr = 0.5,
subs = c(0.8, 0.8))
Number of Clusters found: 14
First 5 Cluster sizes:
BC 1 BC 2 BC 3 BC 4 BC 5
Number of Rows: 11 8 8 11 11
Number of Columns: 10 9 9 10 10
```

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