Package: DNEA
Title: Differential Network Enrichment Analysis for Biological Data
Version: 0.99.14
Authors@R: c(
      person(given = "Christopher", family = "Patsalis", 
             email = "chrispatsalis@gmail.com", role = c("cre", "aut"),
             comment = c(ORCID = "0009-0003-4585-0017")),
      person(given = "Gayatri", family = "Iyer", 
             email = "griyer@umich.edu", role = c("aut")),
             person(given = "Alla", family = "Karnovsky", 
             email = "akarnovs@med.umich.edu", role = c("fnd"),
             comment = c(NIH_GRANT = "1U01CA235487")),
             person(given = "George", family = "Michailidis", 
             email = "gmichail@ufl.edu", role = c("fnd"),
             comment = c(NIH_GRANT = "1U01CA235487")))
Description: 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.
License: MIT + file LICENSE
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.2
output: BiocStyle::html_document vignette: >
        %\VignetteIndexEntry{Vignette Title}
        %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8}
        ---
Imports: BiocParallel, dplyr, gdata, glasso, igraph (>= 2.0.3),
        janitor, Matrix, methods, netgsa, stats, stringr, utils,
        SummarizedExperiment
Collate: 'JSEM-internals.R' 'aggregate-features.R' 'all-classes.R'
        'all-generics.R' 'all-methods.R' 'clustering-internals.R'
        'initiator.R' 'start-here.R' 'utilities-internals.R'
        'utilities-exported.R' 'primary.R'
Depends: R (>= 4.2)
LazyData: false
Suggests: BiocStyle, ggplot2, Hmisc, kableExtra, knitr, pheatmap,
        rmarkdown, testthat (>= 3.0.0), withr, airway
Enhances: massdataset
URL: https://github.com/Karnovsky-Lab/DNEA
BugReports: https://github.com/Karnovsky-Lab/DNEA/issues
biocViews: Metabolomics, Proteomics, Lipidomics,
        DifferentialExpression, NetworkEnrichment, Network, Clustering,
        DataImport
Config/testthat/edition: 3
VignetteBuilder: knitr
git_url: https://git.bioconductor.org/packages/DNEA
git_branch: devel
git_last_commit: d511133
git_last_commit_date: 2025-07-01
Repository: Bioconductor 3.22
Date/Publication: 2025-07-01
NeedsCompilation: no
Packaged: 2025-07-01 22:40:46 UTC; biocbuild
Author: Christopher 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)
Maintainer: Christopher Patsalis <chrispatsalis@gmail.com>
Built: R 4.5.1; ; 2025-07-02 12:46:13 UTC; windows
