recipe bioconductor-msstatsshiny

MSstats GUI for Statistical Anaylsis of Proteomics Experiments






MSstatsShiny is an R-Shiny graphical user interface (GUI) integrated with the R packages MSstats, MSstatsTMT, and MSstatsPTM. It provides a point and click end-to-end analysis pipeline applicable to a wide variety of experimental designs. These include data-dependedent acquisitions (DDA) which are label-free or tandem mass tag (TMT)-based, as well as DIA, SRM, and PRM acquisitions and those targeting post-translational modifications (PTMs). The application automatically saves users selections and builds an R script that recreates their analysis, supporting reproducible data analysis.

package bioconductor-msstatsshiny

(downloads) docker_bioconductor-msstatsshiny



depends bioconductor-marray:


depends bioconductor-msstats:


depends bioconductor-msstatsconvert:


depends bioconductor-msstatsptm:


depends bioconductor-msstatstmt:


depends r-base:


depends r-data.table:

depends r-dplyr:

depends r-dt:

depends r-ggplot2:

depends r-ggrepel:

depends r-gplots:

depends r-hmisc:

depends r-htmltools:

depends r-readxl:

depends r-shiny:

depends r-shinybs:

depends r-shinybusy:

depends r-shinyjs:

depends r-tidyr:

depends r-uuid:



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-msstatsshiny

and update with::

   mamba update bioconductor-msstatsshiny

To create a new environment, run:

mamba create --name myenvname bioconductor-msstatsshiny

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

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