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
| Maintainer | Christopher Patsalis <chrispatsalis@gmail.com> |
| 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) |
| License | MIT + file LICENSE |
| URL | https://github.com/Karnovsky-Lab/DNEA |
| Bug Reports | https://github.com/Karnovsky-Lab/DNEA/issues |
| Downloads rank | 139 |
| Source branch | RELEASE_3_23 |
| biocViews | Clustering, DataImport, DifferentialExpression, Lipidomics, Metabolomics, Network, NetworkEnrichment, Proteomics, Software |
Documentation
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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