recipe bioconductor-omicplotr

Visual Exploration of Omic Datasets Using a Shiny App






A Shiny app for visual exploration of omic datasets as compositions, and differential abundance analysis using ALDEx2. Useful for exploring RNA-seq, meta-RNA-seq, 16s rRNA gene sequencing with visualizations such as principal component analysis biplots (coloured using metadata for visualizing each variable), dendrograms and stacked bar plots, and effect plots (ALDEx2). Input is a table of counts and metadata file (if metadata exists), with options to filter data by count or by metadata to remove low counts, or to visualize select samples according to selected metadata.

package bioconductor-omicplotr

(downloads) docker_bioconductor-omicplotr



depends bioconductor-aldex2:


depends r-base:


depends r-compositions:

depends r-dt:

depends r-jsonlite:

depends r-knitr:

depends r-matrixstats:

depends r-rmarkdown:

depends r-shiny:

depends r-vegan:

depends r-zcompositions:



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-omicplotr

and update with::

   mamba update bioconductor-omicplotr

To create a new environment, run:

mamba create --name myenvname bioconductor-omicplotr

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

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