recipe bioconductor-curatedatlasqueryr

Queries the Human Cell Atlas






Provides access to a copy of the Human Cell Atlas, but with harmonised metadata. This allows for uniform querying across numerous datasets within the Atlas using common fields such as cell type, tissue type, and patient ethnicity. Usage involves first querying the metadata table for cells of interest, and then downloading the corresponding cells into a SingleCellExperiment object.

package bioconductor-curatedatlasqueryr

(downloads) docker_bioconductor-curatedatlasqueryr



depends bioconductor-biocgenerics:


depends bioconductor-hdf5array:


depends bioconductor-s4vectors:


depends bioconductor-singlecellexperiment:


depends bioconductor-summarizedexperiment:


depends r-assertthat:

depends r-base:


depends r-cli:

depends r-dbi:

depends r-dbplyr:


depends r-dplyr:

depends r-duckdb:

depends r-glue:

depends r-httr:

depends r-purrr:


depends r-rlang:

depends r-seurat:

depends r-seuratobject:

depends r-stringr:

depends r-tibble:



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-curatedatlasqueryr

and update with::

   mamba update bioconductor-curatedatlasqueryr

To create a new environment, run:

mamba create --name myenvname bioconductor-curatedatlasqueryr

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

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