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FABIA: Factor Analysis for Bicluster Acquisition

Bioconductor version: Release (3.19)

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.

Author: Sepp Hochreiter <hochreit at>

Maintainer: Andreas Mitterecker <mitterecker at>

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


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


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


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

FABIA: Manual for the R package PDF R Script
Reference Manual PDF


biocViews Clustering, DifferentialExpression, Microarray, MultipleComparison, Software, StatisticalMethod, Visualization
Version 2.50.0
In Bioconductor since BioC 2.7 (R-2.12) (13.5 years)
License LGPL (>= 2.1)
Depends R (>= 3.6.0), Biobase
Imports methods, graphics, grDevices, stats, utils
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Depends On Me hapFabia, RcmdrPlugin.BiclustGUI, superbiclust
Imports Me miRSM, mosbi, BcDiag
Suggests Me fabiaData
Links To Me
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