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Hierarchical ensemble method based on factor graph

Bioconductor version: Release (3.19)

Package that implements the FGGA algorithm. This package provides a hierarchical ensemble method based ob factor graphs for the consistent cross-ontology annotation of protein coding genes. FGGA embodies elements of predicate logic, communication theory, supervised learning and inference in graphical models.

Author: Flavio Spetale [aut, cre]

Maintainer: Flavio Spetale <spetale at>

Citation (from within R, enter citation("fgga")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))


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:

FGGA: Factor Graph GO Annotation HTML R Script
Reference Manual PDF


biocViews Classification, GO, GraphAndNetwork, Network, NetworkInference, Software, StatisticalMethod, SupportVectorMachine
Version 1.12.0
In Bioconductor since BioC 3.13 (R-4.1) (3 years)
License GPL-3
Depends R (>= 4.3), RBGL
Imports graph, stats, e1071, methods, gRbase, jsonlite, BiocFileCache, curl, igraph
System Requirements
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Suggests knitr, rmarkdown, GOstats, GO.db, BiocGenerics, pROC, RUnit, BiocStyle
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Follow Installation instructions to use this package in your R session.

Source Package fgga_1.12.0.tar.gz
Windows Binary
macOS Binary (x86_64) fgga_1.12.0.tgz
macOS Binary (arm64) fgga_1.12.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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