To install this package, start R and enter:
## try http if https is not available source("https://bioconductor.org/biocLite.R") biocLite("iBBiG")
In most cases, you don't need to download the package archive at all.
Bioconductor version: 3.1
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>
Citation (from within R,
enter citation("iBBiG")
):
To install this package, start R and enter:
## try http if https is not available source("https://bioconductor.org/biocLite.R") biocLite("iBBiG")
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("iBBiG")
R Script | iBBiG User Manual | |
Reference Manual |
biocViews | Annotation, Clustering, GeneSetEnrichment, Software |
Version | 1.12.0 |
In Bioconductor since | BioC 2.10 (R-2.15) (3.5 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 | |
Suggests Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Package Source | iBBiG_1.12.0.tar.gz |
Windows Binary | iBBiG_1.12.0.zip (32- & 64-bit) |
Mac OS X 10.6 (Snow Leopard) | iBBiG_1.12.0.tgz |
Mac OS X 10.9 (Mavericks) | iBBiG_1.12.0.tgz |
Subversion source | (username/password: readonly) |
Git source | https://github.com/Bioconductor-mirror/iBBiG/tree/release-3.1 |
Package Short Url | http://bioconductor.org/packages/iBBiG/ |
Package Downloads Report | Download Stats |
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