eCCC: The e-CCC Algorithm

In ewouddt/CCCBiclust: R Wrapper for Java Implementation of CCC and e-CC biclustering algorithm

Description

A R-wrapper which directly calls the original Java code for the e-CCC algorithm (http://kdbio.inesc-id.pt/software/e-ccc-biclustering/) and transforms it to the output format of the Biclust R package.

Usage

eCCC(matrix, minr = 1, minc = 1, maxErrors = 1, overlap = 0.1)

Arguments

matrix	The input matrix in which the columns are ordered by time.
minr	Integer containing the row quorum (= minimum number of genes allowed in e-CCC-Biclusters).
minc	Integer containing the column quorum (= minimum number of contiguous time points allowed in e-CCC-Biclusters).
maxErrors	Integer containing the amount of errors allowed, per gene, in the e-CCC-Biclustering algorithm (value of e).
overlap	Numeric in ]0,1[ containing the maximum percentage of overlapping allowed. The info slot will contain a logical vector which can filter the biclusters which overlap more than overlap*100 percent.

Details

PLACEHOLDER

Value

A Biclust S4 Class object containing extra information of the e-CCC algorithm result in the info slot.

Author(s)

Ewoud De Troyer

References

Sara C. Madeira and Arlindo L. Oliveira, "A polynomial time biclustering algorithm for finding genes with approximate expression patterns in gene expression time series", Algorithms for Molecular Biology 2009, 4:8 (4 June 2009)

Examples

## Not run: 
data(heatdata)
out <- eCCC(heatdata,minr=3,minc=2) 
eCCCinfo(out,filter="Bonf0.01")
out@info$eCCCpatterns$BC53[1:10,]

## End(Not run)

ewouddt/CCCBiclust documentation built on May 16, 2019, 9:41 a.m.