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Biological Network Analysis in R

Bioconductor version: Release (3.19)

the R package BioNAR, developed to step by step analysis of PPI network. The aim is to quantify and rank each protein’s simultaneous impact into multiple complexes based on network topology and clustering. Package also enables estimating of co-occurrence of diseases across the network and specific clusters pointing towards shared/common mechanisms.

Author: Colin Mclean [aut], Anatoly Sorokin [aut, cre], Oksana Sorokina [aut], J. Douglas Armstrong [aut, fnd], T. Ian Simpson [ctb, fnd]

Maintainer: Anatoly Sorokin <lptolik at>

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


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:

BioNAR: Biological Network Analysis in R HTML R Script
Reference Manual PDF


biocViews GraphAndNetwork, Network, Software
Version 1.6.0
In Bioconductor since BioC 3.16 (R-4.2) (1.5 years)
License Artistic-2.0
Depends R (>= 3.5.0), igraph (>=, poweRlaw, latex2exp, RSpectra, Rdpack
Imports stringr, viridis, clusterCons, fgsea, grid, methods, AnnotationDbi, dplyr, GO.db,>= 3.19.1), rSpectral, WGCNA, ggplot2, ggrepel, minpack.lm, cowplot, data.table, scales, stats, Matrix
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Suggests knitr, BiocStyle, magick, rmarkdown, igraphdata, testthat (>= 3.0.0), vdiffr, devtools, pander, plotly, randomcoloR
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Follow Installation instructions to use this package in your R session.

Source Package BioNAR_1.6.0.tar.gz
Windows Binary
macOS Binary (x86_64) BioNAR_1.6.0.tgz
macOS Binary (arm64) BioNAR_1.6.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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