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Bioconductor - fabia (development version)

fabia

This is the development version of fabia; for the stable release version, see fabia.

FABIA: Factor Analysis for Bicluster Acquisition

Bioconductor version: Development (3.22)

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 bioinf.jku.at>

Maintainer: Andreas Mitterecker <mitterecker at bioinf.jku.at>

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

To install this package, start R (version "4.5") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("fabia")

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

Documentation

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

browseVignettes("fabia")
Details biocViews Clustering, DifferentialExpression, Microarray, MultipleComparison, Software, StatisticalMethod, Visualization Version 2.55.0 In Bioconductor since BioC 2.7 (R-2.12) (14.5 years) License LGPL (>= 2.1) Depends R (>= 3.6.0), Biobase Imports methods, graphics, grDevices, stats, utils System Requirements URL http://www.bioinf.jku.at/software/fabia/fabia.html See More Package Archives

Follow Installation instructions to use this package in your R session.


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