recipe bioconductor-duoclustering2018

Data, Clustering Results and Visualization Functions From Duò et al (2018)



GPL (>=2)



Preprocessed experimental and simulated scRNA-seq data sets used for evaluation of clustering methods for scRNA-seq data in Duò et al (2018). Also contains results from applying several clustering methods to each of the data sets, and functions for plotting method performance.

package bioconductor-duoclustering2018

(downloads) docker_bioconductor-duoclustering2018



depends bioconductor-data-packages:


depends bioconductor-experimenthub:


depends curl:

depends r-base:


depends r-dplyr:

depends r-ggplot2:

depends r-ggthemes:

depends r-magrittr:

depends r-mclust:

depends r-purrr:

depends r-reshape2:

depends r-tidyr:

depends r-viridis:



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-duoclustering2018

and update with::

   mamba update bioconductor-duoclustering2018

To create a new environment, run:

mamba create --name myenvname bioconductor-duoclustering2018

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-duoclustering2018/tags`_ for valid values for ``<tag>``)

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