recipe bioconductor-msstatssamplesize

Simulation tool for optimal design of high-dimensional MS-based proteomics experiment






The packages estimates the variance in the input protein abundance data and simulates data with predefined number of biological replicates based on the variance estimation. It reports the mean predictive accuracy of the classifier and mean protein importance over multiple iterations of the simulation.

package bioconductor-msstatssamplesize

(downloads) docker_bioconductor-msstatssamplesize



depends bioconductor-biocparallel:


depends bioconductor-msstats:


depends r-base:


depends r-caret:

depends r-ggplot2:

depends r-gridextra:

depends r-reshape2:



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-msstatssamplesize

and update with::

   mamba update bioconductor-msstatssamplesize

To create a new environment, run:

mamba create --name myenvname bioconductor-msstatssamplesize

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

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