recipe bioconductor-metcirc

Navigating mass spectral similarity in high-resolution MS/MS metabolomics data metabolomics data



GPL (>= 3)




biotools: metcirc, doi: 10.1093/bioinformatics/btx159

MetCirc comprises a workflow to interactively explore high-resolution MS/MS metabolomics data. MetCirc uses the Spectra object infrastructure defined in the package Spectra that stores MS/MS spectra. MetCirc offers functionality to calculate similarity between precursors based on the normalised dot product, neutral losses or user-defined functions and visualise similarities in a circular layout. Within the interactive framework the user can annotate MS/MS features based on their similarity to (known) related MS/MS features.

package bioconductor-metcirc

(downloads) docker_bioconductor-metcirc



depends bioconductor-mscoreutils:


depends bioconductor-s4vectors:


depends bioconductor-spectra:


depends r-amap:


depends r-base:


depends r-circlize:


depends r-ggplot2:


depends r-scales:


depends r-shiny:




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-metcirc

and update with::

   mamba update bioconductor-metcirc

To create a new environment, run:

mamba create --name myenvname bioconductor-metcirc

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-metcirc/tags`_ for valid values for ``<tag>``)

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