MetNet

DOI: 10.18129/B9.bioc.MetNet    

Inferring metabolic networks from untargeted high-resolution mass spectrometry data

Bioconductor version: Release (3.8)

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 matrices are combined to form a adjacency matrix inferred from both quantitative and structure information.

Author: Thomas Naake [aut, cre]

Maintainer: Thomas Naake <thomasnaake at googlemail.com>

Citation (from within R, enter citation("MetNet")):

Installation

To install this package, start R (version "3.5") and enter:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("MetNet", version = "3.8")

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")

 

PDF R Script Workflow for Metabolomics
PDF   Reference Manual
Text   NEWS

Details

biocViews MassSpectrometry, Metabolomics, Network, Regression, Software
Version 1.0.0
License GPL-2
Depends R (>= 3.5), stats (>= 3.5)
Imports bnlearn (>= 4.3), BiocParallel(>= 1.12.0), methods (>= 3.5), mpmi (>= 0.42), parmigene (>= 1.0.2), ppcor (>= 1.1), rfPermute (>= 2.1.5), sna (>= 2.4), stabs (>= 0.6), WGCNA (>= 1.61)
LinkingTo
Suggests BiocGenerics(>= 0.24.0), BiocStyle(>= 2.6.1), igraph (>= 1.1.2), knitr (>= 1.11)
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Build Report  

Package Archives

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

Source Package MetNet_1.0.0.tar.gz
Windows Binary MetNet_1.0.0.zip
Mac OS X 10.11 (El Capitan) MetNet_1.0.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/MetNet
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/MetNet
Package Short Url http://bioconductor.org/packages/MetNet/
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