This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see BioNERO.
Bioconductor version: 3.15
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")
):
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.
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 |
Reference Manual | ||
Text | NEWS |
biocViews | GeneExpression, GeneRegulation, GraphAndNetwork, Network, Preprocessing, Software, SystemsBiology |
Version | 1.4.2 |
In Bioconductor since | BioC 3.13 (R-4.1) (1.5 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 |
Follow Installation instructions to use this package in your R session.
Source Package | BioNERO_1.4.2.tar.gz |
Windows Binary | BioNERO_1.4.2.zip |
macOS Binary (x86_64) | BioNERO_1.4.2.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/BioNERO |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/BioNERO |
Package Short Url | https://bioconductor.org/packages/BioNERO/ |
Package Downloads Report | Download Stats |
Documentation »
Bioconductor
R / CRAN packages and documentation
Support »
Please read the posting guide. Post questions about Bioconductor to one of the following locations: