MetNet

DOI: 10.18129/B9.bioc.MetNet  

This is the development version of MetNet; for the stable release version, see MetNet.

Inferring metabolic networks from untargeted high-resolution mass spectrometry data

Bioconductor version: Development (3.18)

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]

Maintainer: Thomas Naake <thomasnaake at googlemail.com>

Installation

To install this package, start R (version "4.3") and enter:

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("MetNet")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

PDF		Reference Manual

Details

biocViews	ImmunoOncology, MassSpectrometry, Metabolomics, Network, Regression, Software
Version	1.19.0
In Bioconductor since	BioC 3.8 (R-3.5) (4.5 years)
License	GPL (>= 3)
Depends	R (>= 4.0), 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)
LinkingTo
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)
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Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary	MetNet_1.19.0.zip
macOS Binary (x86_64)	MetNet_1.19.0.tgz
macOS Binary (arm64)
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