recipe bioconductor-cellscore

Tool for Evaluation of Cell Identity from Transcription Profiles






The CellScore package contains functions to evaluate the cell identity of a test sample, given a cell transition defined with a starting (donor) cell type and a desired target cell type. The evaluation is based upon a scoring system, which uses a set of standard samples of known cell types, as the reference set. The functions have been carried out on a large set of microarray data from one platform (Affymetrix Human Genome U133 Plus 2.0). In principle, the method could be applied to any expression dataset, provided that there are a sufficient number of standard samples and that the data are normalized.

package bioconductor-cellscore

(downloads) docker_bioconductor-cellscore



depends bioconductor-biobase:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-gplots:


depends r-lsa:


depends r-rcolorbrewer:


depends r-squash:




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-cellscore

and update with::

   mamba update bioconductor-cellscore

To create a new environment, run:

mamba create --name myenvname bioconductor-cellscore

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

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