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DNEA

Differential Network Enrichment Analysis for Biological Data

Bioconductor version: 3.23 · Package version: 1.2.0

The DNEA R package is the latest implementation of the Differential Network Enrichment Analysis algorithm and is the successor to the Filigree Java-application described in Iyer et al. (2020). The package is designed to take as input an m x n expression matrix for some -omics modality (ie. metabolomics, lipidomics, proteomics, etc.) and jointly estimate the biological network associations of each condition using the DNEA algorithm described in Ma et al. (2019). This approach provides a framework for data-driven enrichment analysis across two experimental conditions that utilizes the underlying correlation structure of the data to determine feature-feature interactions.

Installation

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

BiocManager::install("DNEA")

Details

MaintainerChristopher Patsalis <chrispatsalis@gmail.com>
AuthorChristopher Patsalis [cre, aut] (ORCID: <https://orcid.org/0009-0003-4585-0017>), Gayatri Iyer [aut], Alla Karnovsky [fnd] (NIH_GRANT: 1U01CA235487), George Michailidis [fnd] (NIH_GRANT: 1U01CA235487)
LicenseMIT + file LICENSE
URLhttps://github.com/Karnovsky-Lab/DNEA
Bug Reportshttps://github.com/Karnovsky-Lab/DNEA/issues
Downloads rank139
Source branchRELEASE_3_23
biocViewsClustering, DataImport, DifferentialExpression, Lipidomics, Metabolomics, Network, NetworkEnrichment, Proteomics, Software

Documentation

Download

Dependencies

Depends: R (>= 4.2)

Imports: BiocParallel, dplyr, gdata, glasso, igraph (>= 2.0.3), janitor, Matrix, methods, netgsa, stats, stringr, utils, SummarizedExperiment

Suggests: BiocStyle, ggplot2, Hmisc, kableExtra, knitr, pheatmap, rmarkdown, testthat (>= 3.0.0), withr, airway

Enhances: massdataset