MetNet

DOI: 10.18129/B9.bioc.MetNet    

This package is for version 3.8 of Bioconductor; for the stable, up-to-date release version, see MetNet.

Inferring metabolic networks from untargeted high-resolution mass spectrometry data

Bioconductor version: 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>

Installation

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

if (!requireNamespace("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")

 

PDF	R Script	Workflow for Metabolomics
PDF		Reference Manual
Text		NEWS

Details

biocViews	ImmunoOncology, MassSpectrometry, Metabolomics, Network, Regression, Software
Version	1.0.1
In Bioconductor since	BioC 3.8 (R-3.5) (0.5 years)
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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Depends On Me
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Build Report

Package Archives

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

Source Package	MetNet_1.0.1.tar.gz
Windows Binary	MetNet_1.0.1.zip
Mac OS X 10.11 (El Capitan)	MetNet_1.0.1.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/
Package Downloads Report	Download Stats