recipe bioconductor-sdams

Differential Abundant/Expression Analysis for Metabolomics, Proteomics and single-cell RNA sequencing Data






This Package utilizes a Semi-parametric Differential Abundance/expression analysis (SDA) method for metabolomics and proteomics data from mass spectrometry as well as single-cell RNA sequencing data. SDA is able to robustly handle non-normally distributed data and provides a clear quantification of the effect size.

package bioconductor-sdams

(downloads) docker_bioconductor-sdams



depends bioconductor-qvalue:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-trust:



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-sdams

and update with::

   mamba update bioconductor-sdams

To create a new environment, run:

mamba create --name myenvname bioconductor-sdams

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

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