Bioconductor version: Release (3.16)
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")
):
To install this package, start R (version "4.2") and enter:
if (!require("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("fabia")
For older versions of R, please refer to the appropriate Bioconductor release.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("fabia")
R Script | FABIA: Manual for the R package | |
Reference Manual | ||
Text | NEWS |
biocViews | Clustering, DifferentialExpression, Microarray, MultipleComparison, Software, StatisticalMethod, Visualization |
Version | 2.44.0 |
In Bioconductor since | BioC 2.7 (R-2.12) (12.5 years) |
License | LGPL (>= 2.1) |
Depends | R (>= 3.6.0), Biobase |
Imports | methods, graphics, grDevices, stats, utils |
LinkingTo | |
Suggests | |
SystemRequirements | |
Enhances | |
URL | http://www.bioinf.jku.at/software/fabia/fabia.html |
Depends On Me | hapFabia |
Imports Me | miRSM, mosbi |
Suggests Me | fabiaData |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | fabia_2.44.0.tar.gz |
Windows Binary | fabia_2.44.0.zip |
macOS Binary (x86_64) | fabia_2.44.0.tgz |
macOS Binary (arm64) | fabia_2.44.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/fabia |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/fabia |
Bioc Package Browser | https://code.bioconductor.org/browse/fabia/ |
Package Short Url | https://bioconductor.org/packages/fabia/ |
Package Downloads Report | Download Stats |
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