iBBiG-class: Class '"iBBiG"'

In iBBiG: Iterative Binary Biclustering of Genesets

Description

Class to contain and describe result of iBBiG Anlaysis

Objects from the Class

Objects can be created by calls of the form new("iBBiG", ...).

Slots

Seeddata:

Input binaryMatrix

RowScorexNumber:

Matrix. Score for each signature (row) in each cluster. Matrix with dimensions, Number of Rows in Seeddata x Number of clusters

Clusterscores:

Vector. Score for each cluster. It has length equal to the number of clusters

Parameters:

List of Input Parameters (if provided)

RowxNumber:

Binary or Logical Matrix with dimensions, Number of Rows in Seeddata x Number of clusters, where 1 represents cluster membership

NumberxCol:

Binary or Logical Matrix with dimensions, Number of clusters x Number of Columns in Seeddata ,where 1 represents cluster membership

Number:

Numeric. Number of modules(clusters)

info:

list. which is a general contained for other information.

Extends

Class "Biclust", directly.

Methods

RowScorexNumber

signature(x = "iBBiG"): Returns the row scores fore each cluster.

Clusterscores

signature(x = "iBBiG"): Returns the overall score for each cluster.

Seeddata

signature(x = "iBBiG"): Returns the original binary matrix, the clustering is based on.

Parameters

signature(x = "iBBiG"): Returns parameter sets, inhereted from biclust.

RowxNumber

signature(x = "iBBiG"): Returns a logical matrix indicating, which rows are included in each bicluster.

NumberxCol

signature(x = "iBBiG"): Returns a logical matrix indicating, which columns are included in each bicluster.

Number

signature(x = "iBBiG"): Returns the number of biclusters contained in the iBBiG object.

info

signature(x = "iBBiG"): Returns additional information on the particular iBBiG object, inhereted from biclust.

plot

signature(x = "iBBiG"): Plot the iBBiG clustering.

show

signature(object = "iBBiG"): Shows the Biclusters.

summary

signature(object = "iBBiG"): Summary of found bi-clusters.

[

signature(object = "iBBiG"): ...

JIdist

signature(object = "iBBiG"): ...

analyzeClust

signature(object = "iBBiG"): ...

Author(s)

Aedin Culhane, Daniel Gusenleitner

References

Daniel Gusenleitner, Eleanor A Howe, Stefan Bentink, John Quackenbush and Aedin C Culhane iBBiG: Iterative Binary Bi-clustering of Gene Sets Bioinformatics. In review.

See Also

Further functions for viewing and clustering binary data are available in the package biclust. We have written iBBiG and its classes so that it is compatible with biclust, and the class iBBiG inherits Biclust-class.

Examples

showClass("iBBiG")


#create simulated datasets
binMat<-makeArtificial()
binMat

## Create a binary matrix of 400 rows v 400 cols
## Its created as a Biclust object, so its easier to visualize
plot(binMat)

## Perform biclustering analysis on the binary matrix
res<- iBBiG(binMat@Seeddata, nModules=8)
res
plot(res)

## Compare 2 iBBiG or Biclust results
analyzeClust(res, binMat)

## Subset a cluster

res[4]
res[1:2]


## As iBBiG extends the class Biclust can use Biclust functions on it
## View the rows and columns of an iBBiG object

## Create a list of matrices, one for each cluster
Modules<-bicluster(res@Seeddata, res)
length(Modules)
lapply(Modules, dim)

# Or extract a list of a specific cluster
M1<-bicluster(res@Seeddata, res, 1)
dim(M1[[1]])
str(M1)
M1[[1]][1:5,1:3]

iBBiG documentation built on March 2, 2021, 2 a.m.