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FABIA: Factor Analysis for Bicluster Acquisition

Bioconductor version: Release (3.2)

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: Sepp Hochreiter <hochreit at>

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PDF FABIA: Manual for the R package
PDF   Reference Manual
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biocViews Clustering, DifferentialExpression, Microarray, MultipleComparison, Software, StatisticalMethod, Visualization
Version 2.16.0
In Bioconductor since BioC 2.7 (R-2.12) (5 years)
License LGPL (>= 2.1)
Depends R (>= 2.8.0), Biobase
Imports methods, graphics, grDevices, stats, utils
Depends On Me hapFabia
Imports Me
Suggests Me fabiaData
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