MetNet
This is the released version of MetNet; for the devel version, see MetNet.
Inferring metabolic networks from untargeted high-resolution mass spectrometry data
Bioconductor version: Release (3.21)
MetNet contains functionality to infer metabolic network topologies from quantitative data and high-resolution mass/charge information. Using statistical models (including correlation, mutual information, regression and Bayes statistics) and quantitative data (intensity values of features) adjacency matrices are inferred that can be combined to a consensus matrix. Mass differences calculated between mass/charge values of features will be matched against a data frame of supplied mass/charge differences referring to transformations of enzymatic activities. In a third step, the two levels of information are combined to form a adjacency matrix inferred from both quantitative and structure information.
Author: Thomas Naake [aut, cre], Liesa Salzer [ctb], Elva Maria Novoa-del-Toro [ctb]
Maintainer: Thomas Naake <thomasnaake at googlemail.com>
citation("MetNet")):
Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("MetNet")
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("MetNet")| Workflow for high-resolution metabolomics data | HTML | R Script |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | ImmunoOncology, MassSpectrometry, Metabolomics, Network, Regression, Software |
| Version | 1.26.0 |
| In Bioconductor since | BioC 3.8 (R-3.5) (6.5 years) |
| License | GPL (>= 3) |
| Depends | R (>= 4.1.0), S4Vectors(>= 0.28.1), SummarizedExperiment(>= 1.20.0) |
| Imports | bnlearn (>= 4.3), BiocParallel(>= 1.12.0), corpcor (>= 1.6.10), dplyr (>= 1.0.3), ggplot2 (>= 3.3.3), GeneNet (>= 1.2.15), GENIE3(>= 1.7.0), methods (>= 3.5), parmigene (>= 1.0.2), psych (>= 2.1.6), rlang (>= 0.4.10), stabs (>= 0.6), stats (>= 3.6), tibble (>= 3.0.5), tidyr (>= 1.1.2) |
| System Requirements | |
| URL |
See More
| Suggests | BiocGenerics(>= 0.24.0), BiocStyle(>= 2.6.1), glmnet (>= 4.1-1), igraph (>= 1.1.2), knitr (>= 1.11), rmarkdown (>= 1.15), testthat (>= 2.2.1), Spectra(>= 1.4.1), MsCoreUtils(>= 1.6.0) |
| 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 | MetNet_1.26.0.tar.gz |
| Windows Binary (x86_64) | MetNet_1.26.0.zip |
| macOS Binary (x86_64) | MetNet_1.26.0.tgz |
| macOS Binary (arm64) | MetNet_1.26.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/MetNet |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/MetNet |
| Bioc Package Browser | https://code.bioconductor.org/browse/MetNet/ |
| Package Short Url | https://bioconductor.org/packages/MetNet/ |
| Package Downloads Report | Download Stats |