Package: DNEA
Title: Differential Network Enrichment Analysis for Biological Data
Version: 1.1.0
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: 0ff4d1c
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.23
