Biclustering by "Factor Analysis for Bicluster Acquisition" (FABIA). FABIA is a modelbased 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 nonGaussian 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.
Package details 


Author  Sepp Hochreiter <[email protected]> 
Bioconductor views  Clustering DifferentialExpression Microarray MultipleComparison StatisticalMethod Visualization 
Maintainer  Sepp Hochreiter <[email protected]> 
License  LGPL (>= 2.1) 
Version  2.23.0 
URL  http://www.bioinf.jku.at/software/fabia/fabia.html 
Package repository  View on GitHub 
Installation 
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