recipe bioconductor-sctreeviz

R/Bioconductor package to interactively explore and visualize single cell RNA-seq datasets with hierarhical annotations






scTreeViz provides classes to support interactive data aggregation and visualization of single cell RNA-seq datasets with hierarchies for e.g. cell clusters at different resolutions. The `TreeIndex` class provides methods to manage hierarchy and split the tree at a given resolution or across resolutions. The `TreeViz` class extends `SummarizedExperiment` and can performs quick aggregations on the count matrix defined by clusters.

package bioconductor-sctreeviz

(downloads) docker_bioconductor-sctreeviz



depends bioconductor-epivizr:


depends bioconductor-epivizrdata:


depends bioconductor-epivizrserver:


depends bioconductor-s4vectors:


depends bioconductor-scater:


depends bioconductor-scran:


depends bioconductor-singlecellexperiment:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-clustree:

depends r-data.table:

depends r-digest:

depends r-ggplot2:

depends r-ggraph:

depends r-httr:

depends r-igraph:

depends r-matrix:

depends r-rtsne:

depends r-seurat:

depends r-sys:



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-sctreeviz

and update with::

   mamba update bioconductor-sctreeviz

To create a new environment, run:

mamba create --name myenvname bioconductor-sctreeviz

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

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