recipe bioconductor-dapar

Tools for the Differential Analysis of Proteins Abundance with R






The package DAPAR is a Bioconductor distributed R package which provides all the necessary functions to analyze quantitative data from label-free proteomics experiments. Contrarily to most other similar R packages, it is endowed with rich and user-friendly graphical interfaces, so that no programming skill is required (see `Prostar` package).

package bioconductor-dapar

(downloads) docker_bioconductor-dapar



depends bioconductor-annotationdbi:


depends bioconductor-biobase:


depends bioconductor-clusterprofiler:


depends bioconductor-dapardata:


depends bioconductor-graph:


depends bioconductor-impute:


depends bioconductor-limma:


depends bioconductor-mfuzz:


depends bioconductor-msnbase:




depends bioconductor-preprocesscore:


depends bioconductor-vsn:


depends r-apcluster:

depends r-base:


depends r-cluster:

depends r-cp4p:

depends r-dendextend:

depends r-diptest:

depends r-doparallel:

depends r-dplyr:

depends r-factoextra:

depends r-factominer:

depends r-forcats:

depends r-foreach:

depends r-ggplot2:

depends r-gplots:

depends r-highcharter:

depends r-igraph:

depends r-imp4p:

depends r-knitr:

depends r-lme4:

depends r-matrix:

depends r-multcomp:

depends r-norm:

depends r-openxlsx:

depends r-purrr:

depends r-rcolorbrewer:

depends r-readxl:

depends r-reshape2:

depends r-scales:

depends r-stringr:

depends r-tibble:

depends r-tidyr:

depends r-tidyverse:

depends r-vioplot:

depends r-visnetwork:



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-dapar

and update with::

   mamba update bioconductor-dapar

To create a new environment, run:

mamba create --name myenvname bioconductor-dapar

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

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