BioNERO

DOI: 10.18129/B9.bioc.BioNERO  

Biological Network Reconstruction Omnibus

Bioconductor version: Release (3.16)

BioNERO aims to integrate all aspects of biological network inference in a single package, including data preprocessing, exploratory analyses, network inference, and analyses for biological interpretations. BioNERO can be used to infer gene coexpression networks (GCNs) and gene regulatory networks (GRNs) from gene expression data. Additionally, it can be used to explore topological properties of protein-protein interaction (PPI) networks. GCN inference relies on the popular WGCNA algorithm. GRN inference is based on the "wisdom of the crowds" principle, which consists in inferring GRNs with multiple algorithms (here, CLR, GENIE3 and ARACNE) and calculating the average rank for each interaction pair. As all steps of network analyses are included in this package, BioNERO makes users avoid having to learn the syntaxes of several packages and how to communicate between them. Finally, users can also identify consensus modules across independent expression sets and calculate intra and interspecies module preservation statistics between different networks.

Author: Fabricio Almeida-Silva [cre, aut] , Thiago Venancio [aut]

Maintainer: Fabricio Almeida-Silva <fabricio_almeidasilva at hotmail.com>

Installation

To install this package, start R (version "4.2") and enter:

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

BiocManager::install("BioNERO")

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("BioNERO")

 

HTML	R Script	Gene coexpression network inference
HTML	R Script	Gene regulatory network inference with BioNERO
HTML	R Script	Network comparison: consensus modules and module preservation
PDF		Reference Manual
Text		NEWS

Details

biocViews	GeneExpression, GeneRegulation, GraphAndNetwork, Network, Preprocessing, Software, SystemsBiology
Version	1.6.1
In Bioconductor since	BioC 3.13 (R-4.1) (2 years)
License	GPL-3
Depends	R (>= 4.1)
Imports	WGCNA, dynamicTreeCut, matrixStats, sva, RColorBrewer, ComplexHeatmap, ggplot2, ggrepel, patchwork, reshape2, igraph, ggnetwork, intergraph, networkD3, ggnewscale, NetRep, stats, grDevices, graphics, utils, methods, BiocParallel, minet, GENIE3, SummarizedExperiment
LinkingTo
Suggests	knitr, rmarkdown, testthat (>= 3.0.0), BiocStyle, DESeq2, covr
SystemRequirements
Enhances
URL	https://github.com/almeidasilvaf/BioNERO
BugReports	https://github.com/almeidasilvaf/BioNERO/issues
Depends On Me
Imports Me	cageminer
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	BioNERO_1.6.1.tar.gz
Windows Binary	BioNERO_1.6.1.zip
macOS Binary (x86_64)	BioNERO_1.6.1.tgz
macOS Binary (arm64)	BioNERO_1.6.1.tgz
Source Repository	git clone https://git.bioconductor.org/packages/BioNERO
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/BioNERO
Bioc Package Browser	https://code.bioconductor.org/browse/BioNERO/
Package Short Url	https://bioconductor.org/packages/BioNERO/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.16	Source Archive