recipe bioconductor-bigpint

Big multivariate data plotted interactively






Methods for visualizing large multivariate datasets using static and interactive scatterplot matrices, parallel coordinate plots, volcano plots, and litre plots. Includes examples for visualizing RNA-sequencing datasets and differentially expressed genes.

package bioconductor-bigpint

(downloads) docker_bioconductor-bigpint



depends bioconductor-delayedarray:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-dplyr:


depends r-ggally:


depends r-ggplot2:


depends r-gridextra:


depends r-hexbin:


depends r-hmisc:


depends r-htmlwidgets:


depends r-plotly:


depends r-plyr:


depends r-rcolorbrewer:


depends r-reshape:


depends r-shiny:


depends r-shinycssloaders:


depends r-shinydashboard:


depends r-stringr:


depends r-tidyr:




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-bigpint

and update with::

   mamba update bioconductor-bigpint

To create a new environment, run:

mamba create --name myenvname bioconductor-bigpint

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

Download stats