S4 Class for Quantitative Data and Associated Networks • GraphExperiment

GraphExperiment provides users and developers with infrastructure to store quantitative data from omics assays along with networks representing how assay features (e.g., genes, proteins, metabolites) and/or observations (e.g., samples, cells, species) interact with each other. The GraphExperiment S4 class extends SingleCellExperiment to include support for igraph objects associated with features (stored in rowGraphs) and observations (stored in colGraphs).

The figure belows summarizes the GraphExperiment class in comparison to the SingleCellExperiment class.

Installation instructions

Get the latest stable R release from CRAN. Then install GraphExperiment from Bioconductor using the following code:

if (!requireNamespace("BiocManager", quietly = TRUE)) {
    install.packages("BiocManager")
}

BiocManager::install("GraphExperiment")

Citation

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

print(citation('GraphExperiment'), bibtex = TRUE)
#> To cite package 'GraphExperiment' in publications use:
#> 
#>   Almeida-Silva F (2026). _GraphExperiment: S4 Class for Quantitative
#>   Data and Associated Networks_. R package version 1.1.2,
#>   <https://github.com/almeidasilvaf/GraphExperiment>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {GraphExperiment: S4 Class for Quantitative Data and Associated Networks},
#>     author = {Fabricio Almeida-Silva},
#>     year = {2026},
#>     note = {R package version 1.1.2},
#>     url = {https://github.com/almeidasilvaf/GraphExperiment},
#>   }

Code of Conduct

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