netboost
This is the development version of netboost; for the stable release version, see netboost.
Network Analysis Supported by Boosting
Bioconductor version: Development (3.24)
Boosting-supported network analysis for high-dimensional omics data, implementing a three-step dimension reduction technique. A filter combined with the topological overlap measure first identifies the essential edges of the feature network, sparse hierarchical clustering then groups the selected features into modules, and each module is finally summarised by its first principal components. Subsequent analyses are carried out on these low-dimensional module signals instead of the original data, which makes the method well suited to epigenetics, metabolomics, transcriptomics, and other omics studies. The method is described in Schlosser et al. (2021) <doi:10.1109/TCBB.2020.2983010>.
Author: Pascal Schlosser [aut, cre] 
, Jochen Knaus [aut, ctb], Alex Waterhölter [aut, ctb]
Maintainer: Pascal Schlosser <pascal.schlosser at uniklinik-freiburg.de>
citation("netboost")):Pascal Schlosser, Jochen Knaus, Alex Waterhölter. netboost: Network Analysis Supported by Boosting. doi:10.18129/B9.bioc.netboost, R package version 2.21.5, https://bioconductor.org/packages/netboost.
Generated from the package metadata; it may differ from the package's own citation.
Installation
To install this package, start R (version "4.6") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
## The following initializes the development version of Bioconductor
BiocManager::install(version = "devel")
BiocManager::install("netboost")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("netboost")| The Netboost users guide | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | BiomedicalInformatics, Clustering, DimensionReduction, Epigenetics, GraphAndNetwork, Metabolomics, Network, Software, StatisticalMethod, Transcriptomics |
| Version | 2.21.5 |
| In Bioconductor since | BioC 3.9 (R-3.6) (7.5 years) |
| License | GPL-3 |
| Depends | R (>= 4.0.0) |
| Imports | Rcpp, RcppParallel, parallel, grDevices, graphics, stats, utils, dynamicTreeCut, WGCNA, impute, colorspace, methods |
| System Requirements | |
| URL | https://bioconductor.org/packages/release/bioc/html/netboost.html |
| Bug Reports | mailto:pascal.schlosser@uniklinik-freiburg.de |
See More
| Suggests | knitr, rmarkdown, BiocStyle |
| Linking To | Rcpp, RcppParallel |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report, r-universe |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | netboost_2.21.5.tar.gz |
| Windows Binary (x86_64) | netboost_2.21.5.zip (64-bit only) |
| macOS Binary (big-sur-x86_64) | netboost_2.21.5.tgz |
| macOS Binary (sonoma-arm64) | netboost_2.21.5.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/netboost |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/netboost |
| Package Short Url | https://bioconductor.org/packages/netboost/ |
| Package Downloads Report | Download Stats |