DOI: 10.18129/B9.bioc.MetNet    

This is the development version of MetNet; to use it, please install the devel version of Bioconductor.

Inferring metabolic networks from untargeted high-resolution mass spectrometry data

Bioconductor version: Development (3.10)

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>

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biocViews ImmunoOncology, MassSpectrometry, Metabolomics, Network, Regression, Software
Version 1.3.0
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)
Suggests BiocGenerics(>= 0.24.0), BiocStyle(>= 2.6.1), igraph (>= 1.1.2), knitr (>= 1.11)
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