This is the development version of DNEA; to use it, please install the devel version of Bioconductor.
Differential Network Enrichment Analysis for Biological DataBioconductor version: Development (3.22)
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.
Author: Christopher Patsalis [cre, aut] ORCID: 0009-0003-4585-0017 , Gayatri Iyer [aut], Alla Karnovsky [fnd] (NIH_GRANT: 1U01CA235487), George Michailidis [fnd] (NIH_GRANT: 1U01CA235487)
Maintainer: Christopher Patsalis <chrispatsalis at gmail.com>
Citation (from within R, entercitation("DNEA")
): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("DNEA")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("DNEA")
Details biocViews Clustering, DataImport, DifferentialExpression, Lipidomics, Metabolomics, Network, NetworkEnrichment, Proteomics, Software Version 0.99.14 In Bioconductor since BioC 3.22 (R-4.5) License MIT + file LICENSE Depends R (>= 4.2) Imports BiocParallel, dplyr, gdata, glasso, igraph (>= 2.0.3), janitor, Matrix, methods, netgsa, stats, stringr, utils, SummarizedExperiment System Requirements URL https://github.com/Karnovsky-Lab/DNEA Bug Reports https://github.com/Karnovsky-Lab/DNEA/issues See More Package Archives
Follow Installation instructions to use this package in your R session.
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