recipe bioconductor-chetah

Fast and accurate scRNA-seq cell type identification






CHETAH (CHaracterization of cEll Types Aided by Hierarchical classification) is an accurate, selective and fast scRNA-seq classifier. Classification is guided by a reference dataset, preferentially also a scRNA-seq dataset. By hierarchical clustering of the reference data, CHETAH creates a classification tree that enables a step-wise, top-to-bottom classification. Using a novel stopping rule, CHETAH classifies the input cells to the cell types of the references and to "intermediate types": more general classifications that ended in an intermediate node of the tree.

package bioconductor-chetah

(downloads) docker_bioconductor-chetah



depends bioconductor-biodist:


depends bioconductor-s4vectors:


depends bioconductor-singlecellexperiment:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-corrplot:

depends r-cowplot:

depends r-dendextend:

depends r-ggplot2:

depends r-pheatmap:

depends r-plotly:

depends r-reshape2:

depends r-shiny:



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-chetah

and update with::

   mamba update bioconductor-chetah

To create a new environment, run:

mamba create --name myenvname bioconductor-chetah

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

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