recipe bioconductor-structtoolbox

Data processing & analysis tools for Metabolomics and other omics






An extensive set of data (pre-)processing and analysis methods and tools for metabolomics and other omics, with a strong emphasis on statistics and machine learning. This toolbox allows the user to build extensive and standardised workflows for data analysis. The methods and tools have been implemented using class-based templates provided by the struct (Statistics in R Using Class-based Templates) package. The toolbox includes pre-processing methods (e.g. signal drift and batch correction, normalisation, missing value imputation and scaling), univariate (e.g. ttest, various forms of ANOVA, Kruskal–Wallis test and more) and multivariate statistical methods (e.g. PCA and PLS, including cross-validation and permutation testing) as well as machine learning methods (e.g. Support Vector Machines). The STATistics Ontology (STATO) has been integrated and implemented to provide standardised definitions for the different methods, inputs and outputs.

package bioconductor-structtoolbox

(downloads) docker_bioconductor-structtoolbox



depends bioconductor-struct:


depends r-base:


depends r-ggplot2:

depends r-ggthemes:

depends r-gridextra:

depends r-scales:

depends r-sp:



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-structtoolbox

and update with::

   mamba update bioconductor-structtoolbox

To create a new environment, run:

mamba create --name myenvname bioconductor-structtoolbox

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

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