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BioNERO

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

Biological Network Reconstruction Omnibus


Bioconductor version: Development (3.19)

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>

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

Installation

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


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

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

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

Details

biocViews GeneExpression, GeneRegulation, GraphAndNetwork, Network, NetworkInference, Preprocessing, Software, SystemsBiology
Version 1.11.1
In Bioconductor since BioC 3.13 (R-4.1) (3 years)
License GPL-3
Depends R (>= 4.1)
Imports WGCNA, dynamicTreeCut, ggdendro, matrixStats, sva, RColorBrewer, ComplexHeatmap, ggplot2, rlang, ggrepel, patchwork, reshape2, igraph, ggnetwork, intergraph, NetRep, stats, grDevices, utils, methods, BiocParallel, minet, GENIE3, SummarizedExperiment
System Requirements
URL https://github.com/almeidasilvaf/BioNERO
Bug Reports https://github.com/almeidasilvaf/BioNERO/issues
See More
Suggests knitr, rmarkdown, testthat (>= 3.0.0), BiocStyle, DESeq2, networkD3, covr
Linking To
Enhances
Depends On Me
Imports Me cageminer
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package BioNERO_1.11.1.tar.gz
Windows Binary BioNERO_1.11.1.zip
macOS Binary (x86_64) BioNERO_1.11.1.tgz
macOS Binary (arm64) BioNERO_1.11.0.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