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 (3.15)

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 <thomasnaake at googlemail.com>, Liesa Salzer <liesa.salzer at helmholtz-muenchen.de>

Maintainer: Thomas Naake <thomasnaake at googlemail.com>

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

Installation

To install this package, start R (version "4.2") and enter:

if (!requireNamespace("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 1.13.0
In Bioconductor since BioC 3.8 (R-3.5) (3 years)
License GPL (>= 3)
Depends R (>= 4.0), S4Vectors(>= 0.28.1), SummarizedExperiment(>= 1.20.0)
Imports bnlearn (>= 4.3), BiocParallel(>= 1.12.0), dplyr (>= 1.0.3), ggplot2 (>= 3.3.3), GENIE3(>= 1.7.0), methods (>= 3.5), mpmi (>= 0.42), parmigene (>= 1.0.2), ppcor (>= 1.1), 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)
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Build Report  

Package Archives

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

Source Package
Windows Binary
macOS 10.13 (High Sierra)
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 https://bioconductor.org/packages/MetNet/
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