glmSparseNet
This is the development version of glmSparseNet; for the stable release version, see glmSparseNet.
Network Centrality Metrics for Elastic-Net Regularized Models
Bioconductor version: Development (3.21)
glmSparseNet is an R-package that generalizes sparse regression models when the features (e.g. genes) have a graph structure (e.g. protein-protein interactions), by including network-based regularizers. glmSparseNet uses the glmnet R-package, by including centrality measures of the network as penalty weights in the regularization. The current version implements regularization based on node degree, i.e. the strength and/or number of its associated edges, either by promoting hubs in the solution or orphan genes in the solution. All the glmnet distribution families are supported, namely "gaussian", "poisson", "binomial", "multinomial", "cox", and "mgaussian".
Author: André Veríssimo [aut, cre] (ORCID:
Maintainer: André Veríssimo <andre.verissimo at tecnico.ulisboa.pt>
citation("glmSparseNet")):
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("glmSparseNet")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("glmSparseNet")| Breast survival dataset using network from STRING DB | HTML | R Script |
| Example for Classification -- Breast Invasive Carcinoma | HTML | R Script |
| Example for Survival Data -- Breast Invasive Carcinoma | HTML | R Script |
| Example for Survival Data -- Prostate Adenocarcinoma | HTML | R Script |
| Example for Survival Data -- Skin Melanoma | HTML | R Script |
| Separate 2 groups in Cox regression | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | Classification, DimensionReduction, GraphAndNetwork, Network, Regression, Software, StatisticalMethod, Survival |
| Version | 1.25.0 |
| In Bioconductor since | BioC 3.8 (R-3.5) (6 years) |
| License | GPL-3 |
| Depends | R (>= 4.3.0) |
| Imports | biomaRt, checkmate, dplyr, forcats, futile.logger, ggplot2, glue, httr, lifecycle, methods, parallel, readr, rlang, glmnet, Matrix, MultiAssayExperiment, SummarizedExperiment, survminer, TCGAutils, utils |
| System Requirements | |
| URL | https://www.github.com/sysbiomed/glmSparseNet |
| Bug Reports | https://www.github.com/sysbiomed/glmSparseNet/issues |
See More
| Suggests | BiocStyle, curatedTCGAData, knitr, magrittr, reshape2, pROC, rmarkdown, survival, testthat, VennDiagram, withr |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | glmSparseNet_1.25.0.tar.gz |
| Windows Binary (x86_64) | glmSparseNet_1.25.0.zip |
| macOS Binary (x86_64) | glmSparseNet_1.25.0.tgz |
| macOS Binary (arm64) | |
| Source Repository | git clone https://git.bioconductor.org/packages/glmSparseNet |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/glmSparseNet |
| Bioc Package Browser | https://code.bioconductor.org/browse/glmSparseNet/ |
| Package Short Url | https://bioconductor.org/packages/glmSparseNet/ |
| Package Downloads Report | Download Stats |