Package: fabia
Title: FABIA: Factor Analysis for Bicluster Acquisition
Version: 2.36.0
Date: 2020-01-30
Author: Sepp Hochreiter <hochreit@bioinf.jku.at>
Maintainer: Andreas Mitterecker <mitterecker@bioinf.jku.at>
Depends: R (>= 3.6.0), Biobase
Imports: methods, graphics, grDevices, stats, utils
LinkingTo:
Description: 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.
License: LGPL (>= 2.1)
Collate: AllClasses.R AllGenerics.R fabia.R
        methods-Factorization-class.R zzz.R
URL: http://www.bioinf.jku.at/software/fabia/fabia.html
Packaged: 2020-10-28 00:06:50 UTC; biocbuild
biocViews: StatisticalMethod, Microarray, DifferentialExpression,
        MultipleComparison, Clustering, Visualization
git_url: https://git.bioconductor.org/packages/fabia
git_branch: RELEASE_3_12
git_last_commit: 881c213
git_last_commit_date: 2020-10-27
Date/Publication: 2020-10-27
NeedsCompilation: yes
Built: R 4.0.3; x86_64-apple-darwin13.4.0; 2021-03-27 05:17:55 UTC; unix
