recipe bioconductor-hgc

A fast hierarchical graph-based clustering method






HGC (short for Hierarchical Graph-based Clustering) is an R package for conducting hierarchical clustering on large-scale single-cell RNA-seq (scRNA-seq) data. The key idea is to construct a dendrogram of cells on their shared nearest neighbor (SNN) graph. HGC provides functions for building graphs and for conducting hierarchical clustering on the graph. The users with old R version could visit to get HGC package built for R 3.6.

package bioconductor-hgc

(downloads) docker_bioconductor-hgc



depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-ape:

depends r-base:


depends r-dendextend:

depends r-dplyr:

depends r-ggplot2:

depends r-matrix:

depends r-mclust:

depends r-patchwork:

depends r-rann:

depends r-rcpp:


depends r-rcppeigen:




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-hgc

and update with::

   mamba update bioconductor-hgc

To create a new environment, run:

mamba create --name myenvname bioconductor-hgc

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

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