BCCC: The CC Bicluster algorithm

In biclust: BiCluster Algorithms

Description

Performs CC Biclustering based on the framework by Cheng and Church (2000). Searches for submatrices with a score lower than a specific treshold in a standardized data matrix.

Usage

## S4 method for signature 'matrix,BCCC'
biclust(x, method=BCCC(), delta = 1.0, alpha=1.5, number=100)

Arguments

x	Data matrix.
method	Here BCCC, to perform CC algorithm
delta	Maximum of accepted score.
alpha	Scaling factor.
number	Number of bicluster to be found.

Value

Returns an object of class Biclust.

Author(s)

Sebastian Kaiser [e-mail]

References

Cheng, Y. & Church, G.M. Biclustering of Expression Data Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology, 2000, 1, 93-103

See Also

biclust, Biclust

Examples

test <- matrix(rbinom(400, 50, 0.4), 20, 20)
res <- biclust(test, method=BCCC(), delta=1.5,  alpha=1, number=10)
res

Example output

Loading required package: MASS
Loading required package: grid
Loading required package: colorspace
Loading required package: lattice

An object of class Biclust 

call:
	biclust(x = test, method = BCCC(), delta = 1.5, alpha = 1, number = 10)

Number of Clusters found:  4 

First  4  Cluster sizes:
                   BC 1 BC 2 BC 3 BC 4
Number of Rows:       5    5    5    4
Number of Columns:    8    6    4    5

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