iBBiG

DOI: 10.18129/B9.bioc.iBBiG    

This package is for version 3.11 of Bioconductor; for the stable, up-to-date release version, see iBBiG.

Iterative Binary Biclustering of Genesets

Bioconductor version: 3.11

iBBiG is a bi-clustering algorithm which is optimizes for binary data analysis. We apply it to meta-gene set analysis of large numbers of gene expression datasets. The iterative algorithm extracts groups of phenotypes from multiple studies that are associated with similar gene sets. iBBiG does not require prior knowledge of the number or scale of clusters and allows discovery of clusters with diverse sizes

Author: Daniel Gusenleitner, Aedin Culhane

Maintainer: Aedin Culhane <aedin at jimmy.harvard.edu>

Installation

To install this package, start R (version "4.0") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("iBBiG")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("iBBiG")

 

PDF	R Script	iBBiG User Manual
PDF		Reference Manual

Details

biocViews	Annotation, Clustering, GeneSetEnrichment, Software
Version	1.32.0
In Bioconductor since	BioC 2.10 (R-2.15) (8.5 years)
License	Artistic-2.0
Depends	biclust
Imports	stats4, xtable, ade4
LinkingTo
Suggests	methods
SystemRequirements
Enhances
URL	http://bcb.dfci.harvard.edu/~aedin/publications/
Depends On Me
Imports Me	miRSM
Suggests Me
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	iBBiG_1.32.0.tar.gz
Windows Binary	iBBiG_1.32.0.zip (32- & 64-bit)
macOS 10.13 (High Sierra)	iBBiG_1.32.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/iBBiG
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/iBBiG
Package Short Url	https://bioconductor.org/packages/iBBiG/
Package Downloads Report	Download Stats