ensemble: Ensemble Methods for Bicluster Algorithms

In biclust: BiCluster Algorithms

Description

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

Usage

ensemble(x, confs, rep = 1, maxNum = 5, similar = jaccard2, thr = 0.8, simthr =0.7,
  subs = c(1, 1), bootstrap = FALSE, support = 0, combine=firstcome, ...)

Arguments

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.

Details

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

Value

Return an object of class Biclust

Author(s)

Sebastian Kaiser [e-mail]

See Also

Biclust-class, plaid.grid, bimax.grid

Examples

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

Example output

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

biclust documentation built on May 2, 2019, 5:56 p.m.