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.
Package details |
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| Author | Sepp Hochreiter <hochreit@bioinf.jku.at> |
| Bioconductor views | Clustering DifferentialExpression Microarray MultipleComparison StatisticalMethod Visualization |
| Maintainer | Andreas Mitterecker <mitterecker@bioinf.jku.at> |
| License | LGPL (>= 2.1) |
| Version | 2.36.0 |
| URL | http://www.bioinf.jku.at/software/fabia/fabia.html |
| Package repository | View on Bioconductor |
| Installation |
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