recipe bioconductor-metnet

Inferring metabolic networks from untargeted high-resolution mass spectrometry data



GPL (>= 3)



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.

package bioconductor-metnet

(downloads) docker_bioconductor-metnet



depends bioconductor-biocparallel:


depends bioconductor-genie3:


depends bioconductor-s4vectors:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-bnlearn:


depends r-corpcor:


depends r-dplyr:


depends r-genenet:


depends r-ggplot2:


depends r-parmigene:


depends r-psych:


depends r-rlang:


depends r-stabs:


depends r-tibble:


depends r-tidyr:




You need a conda-compatible package manager (currently either micromamba, mamba, or conda) and the Bioconda channel already activated (see set-up-channels).

While any of above package managers is fine, it is currently recommended to use either micromamba or mamba (see here for installation instructions). We will show all commands using mamba below, but the arguments are the same for the two others.

Given that you already have a conda environment in which you want to have this package, install with:

   mamba install bioconductor-metnet

and update with::

   mamba update bioconductor-metnet

To create a new environment, run:

mamba create --name myenvname bioconductor-metnet

with myenvname being a reasonable name for the environment (see e.g. the mamba docs for details and further options).

Alternatively, use the docker container:

   docker pull<tag>

(see `bioconductor-metnet/tags`_ for valid values for ``<tag>``)

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