Registration Open for Bioc2024 July 24-26


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 (3.20)

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>

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


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


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


To view documentation for the version of this package installed in your system, start R and enter:

Workflow for high-resolution metabolomics data HTML R Script
Reference Manual PDF


biocViews ImmunoOncology, MassSpectrometry, Metabolomics, Network, Regression, Software
Version 1.23.0
In Bioconductor since BioC 3.8 (R-3.5) (5.5 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)
System Requirements
See More
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)
Linking To
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report

Package Archives

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

Source Package MetNet_1.23.0.tar.gz
Windows Binary
macOS Binary (x86_64) MetNet_1.23.0.tgz
macOS Binary (arm64) MetNet_1.23.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
Bioc Package Browser
Package Short Url
Package Downloads Report Download Stats