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## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("fabia")

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fabia

   

This package is for version 2.8 of Bioconductor; for the stable, up-to-date release version, see fabia.

FABIA: Factor Analysis for Bicluster Acquisition

Bioconductor version: 2.8

Biclustering by "Factor Analysis for Bicluster Acquisition" (FABIA). FABIA is a model-based technique for biclustering, that is clustering rows and columns simultaneously. Biclusters are found by factor analysis where both the factors and the loading matrix are sparse. FABIA is a multiplicative model that extracts linear dependencies between samples and feature patterns. It captures realistic non-Gaussian data distributions with heavy tails as observed in gene expression measurements. FABIA utilizes well understood model selection techniques like the EM algorithm and variational approaches and is embedded into a Bayesian framework. FABIA ranks biclusters according to their information content and separates spurious biclusters from true biclusters. The code is written in C++ based on Rcpp package.

Author: Sepp Hochreiter <hochreit at bioinf.jku.at>

Maintainer: Sepp Hochreiter <hochreit at bioinf.jku.at>

Citation (from within R, enter citation("fabia")):

Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("fabia")

Documentation

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

browseVignettes("fabia")

 

PDF fabia.pdf
PDF   Reference Manual

Details

biocViews Bioinformatics, Clustering, DifferentialExpression, Microarray, MultipleComparisons, Software, Statistics, Visualization
Version 1.4.0
In Bioconductor since BioC 2.7 (R-2.12) (5.5 years)
License LGPL (>= 2.1)
Depends R (>= 2.8.0), methods
Imports methods, graphics
LinkingTo
Suggests utils
SystemRequirements
Enhances
URL http://www.bioinf.jku.at/software/fabia/fabia.html
Depends On Me
Imports Me
Suggests Me
Build Report  

Package Archives

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

Package Source fabia_1.4.0.tar.gz
Windows Binary fabia_1.4.0.zip (32- & 64-bit)
Mac OS X 10.6 (Snow Leopard)
Mac OS X 10.9 (Mavericks)
Subversion source (username/password: readonly)
Git source https://github.com/Bioconductor-mirror/fabia/tree/release-2.8
Package Short Url http://bioconductor.org/packages/fabia/
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