recipe bioconductor-celda

CEllular Latent Dirichlet Allocation






Celda is a suite of Bayesian hierarchical models for clustering single-cell RNA-sequencing (scRNA-seq) data. It is able to perform "bi-clustering" and simultaneously cluster genes into gene modules and cells into cell subpopulations. It also contains DecontX, a novel Bayesian method to computationally estimate and remove RNA contamination in individual cells without empty droplet information. A variety of scRNA-seq data visualization functions is also included.

package bioconductor-celda

(downloads) docker_bioconductor-celda



depends bioconductor-complexheatmap:


depends bioconductor-complexheatmap:


depends bioconductor-delayedarray:


depends bioconductor-delayedarray:


depends bioconductor-s4vectors:


depends bioconductor-s4vectors:


depends bioconductor-scater:


depends bioconductor-scater:


depends bioconductor-scran:


depends bioconductor-scran:


depends bioconductor-singlecellexperiment:


depends bioconductor-singlecellexperiment:


depends bioconductor-summarizedexperiment:


depends bioconductor-summarizedexperiment:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-circlize:

depends r-data.table:

depends r-dbscan:

depends r-digest:

depends r-doparallel:

depends r-enrichr:

depends r-foreach:

depends r-ggplot2:

depends r-ggrepel:

depends r-gridextra:

depends r-gtable:

depends r-matrix:

depends r-matrixstats:

depends r-mcmcprecision:

depends r-plyr:

depends r-rcolorbrewer:

depends r-rcpp:

depends r-rcppeigen:

depends r-reshape2:

depends r-rtsne:

depends r-scales:

depends r-stringr:

depends r-uwot:

depends r-withr:



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-celda

and update with::

   mamba update bioconductor-celda

To create a new environment, run:

mamba create --name myenvname bioconductor-celda

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

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