mlBioNets

**mlBionets** is an R package designed to comprehensively analyze microbiota data using a multilayer network approach. This package enables researchers to integrate and analyze multiple types of biological data, providing a robust framework for studying complex microbial communities and their interactions within different environmental and biological contexts.

Features

Multilayer Network Construction: Build and visualize multilayer networks from microbiota data, incorporating various layers such as phylogenetic, functional, and environmental information.
Data Integration: Seamlessly integrate different types of microbiota data, including taxonomic profiles and metadata
Advanced Analysis Tools: Perform network-based analyses, including community detection, network centrality, and inter-layer connectivity.
Visualization: Generate publication-quality visualizations to illustrate complex network structures and interactions.
Customizable Workflows: Easily customize analysis workflows to suit specific research needs, facilitating reproducible and flexible data analysis.

Installation instructions

You can install the development version of mlBioNets like so:

devtools::install_github("Nertekkad/mlBioNets")
#> Using GitHub PAT from the git credential store.
#> Downloading GitHub repo Nertekkad/mlBioNets@HEAD
#> Installing package into '/tmp/RtmpiUtZG4/temp_libpath28e8722166fe8'
#> (as 'lib' is unspecified)
library(mlBioNets)

OsX users

Before installing the mlBioNets package, it is necessary to install some gfortran packages, so that it can work better, since it is necessary to compile the source code, which seems to generate problems for mac users.

It is recommended to get gfortan from xcode by running the following code in a terminal (OSX 10.10 and later):

xcode-select --install

Alternatively, the officially-supported fortran binaries are on CRAN.

Overview of the design and workflow with mlBioNets package

Diagram Workflow

Citation

Below is the citation output from using citation('mlBioNets') in R. Please run this yourself to check for any updates on how to cite mlBioNets.

print(citation('mlBioNets'), bibtex = TRUE)
#> To cite package 'mlBioNets' in publications use:
#> 
#>   Lázaro-Vidal V, Hernández-Zendejas V, Vázquez-Suárez K,
#>   Álvarez-Martínez R (2025). _mlBioNets_.
#>   doi:10.18129/B9.bioc.mlBioNets
#>   <https://doi.org/10.18129/B9.bioc.mlBioNets>,
#>   https://github.com/Nertekkad/mlBioNets/mlBioNets - R package version
#>   0.1.0, <http://www.bioconductor.org/packages/mlBioNets>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {mlBioNets},
#>     author = {Víctor Lázaro-Vidal and Valeria Hernández-Zendejas and Karel Vázquez-Suárez and Roberto Álvarez-Martínez},
#>     year = {2025},
#>     url = {http://www.bioconductor.org/packages/mlBioNets},
#>     note = {https://github.com/Nertekkad/mlBioNets/mlBioNets - R package version 0.1.0},
#>     doi = {10.18129/B9.bioc.mlBioNets},
#>   }
#> 
#>   Lázaro-Vidal V, Hernández-Zendejas V, Vázquez-Suárez K,
#>   Álvarez-Martínez R (2025). "mlBioNets: A multilayer network approach
#>   for microbiota data analysis." _bioRxiv_. doi:10.1101/TODO
#>   <https://doi.org/10.1101/TODO>,
#>   <https://www.biorxiv.org/content/10.1101/TODO>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Article{,
#>     title = {mlBioNets: A multilayer network approach for microbiota data analysis},
#>     author = {Víctor Lázaro-Vidal and Valeria Hernández-Zendejas and Karel Vázquez-Suárez and Roberto Álvarez-Martínez},
#>     year = {2025},
#>     journal = {bioRxiv},
#>     doi = {10.1101/TODO},
#>     url = {https://www.biorxiv.org/content/10.1101/TODO},
#>   }

Please note that the mlBioNets was only made possible thanks to many other R and bioinformatics software authors, which are cited either in the vignettes and/or the paper(s) describing this package.

Code of Conduct

Please note that the mlBioNets project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.