DNEA

[chrispatsalis]

Update the following URL to point to the GitHub repository of the package you wish to submit to Bioconductor

-Note: The package is currently stored on the Lab github but I do the maintenance and developement as a member of said lab. My github profile is chrispatsalis.

• Repository: https://github.com/Karnovsky-Lab/DNEA/

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[bioc-issue-bot]

Hi @chrispatsalis

Thanks for submitting your package. We are taking a quick look at it and you will hear back from us soon.

The DESCRIPTION file for this package is:

Package: DNEA
Title: Differential Network Enrichment Analysis for Biological Data
Version: 0.99.0
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")))
Description: The DNEA R package is the latest implementation of the 
   Differential Network Enrichment Analysis algorithm and 
   is the predecessor 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: 7.2.3
output: 
    BiocStyle::html_document
  vignette: >
    %\VignetteIndexEntry{Vignette Title}
    %\VignetteEngine{knitr::rmarkdown}
    %\VignetteEncoding{UTF-8}  
  ---
Imports: 
    BiocParallel,
    dplyr,
    gdata,
    glasso,
    igraph,
    janitor,
    Matrix,
    methods,
    netgsa,
    stats,
    stringr,
    utils
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 (>= 4.3.0)
LazyData: false
Suggests: 
    BiocStyle,
    ggplot2,
    Hmisc,
    kableExtra,
    knitr,
    pheatmap,
    rmarkdown,
    testthat (>= 3.0.0),
    withr
URL: https://github.com/Karnovsky-Lab/DNEA
biocViews: Metabolomics, Proteomics, Lipidomics, 
 DifferentialExpression, NetworkEnrichment, 
 Network, Clustering, DataImport
Config/testthat/edition: 3
VignetteBuilder: knitr

[lshep]

The package advertises input as m x n expression matrix for some -omics modality (ie. metabolomics, lipidomics, proteomics, etc.) . The package should also be able to take standard Bioconductor class structures of for this data. Minimally a SummarizedExperiment.