recipe bioconductor-chromscape

Analysis of single-cell epigenomics datasets with a Shiny App






ChromSCape - Chromatin landscape profiling for Single Cells - is a ready-to-launch user-friendly Shiny Application for the analysis of single-cell epigenomics datasets (scChIP-seq, scATAC-seq, scCUT&Tag, …) from aligned data to differential analysis & gene set enrichment analysis. It is highly interactive, enables users to save their analysis and covers a wide range of analytical steps: QC, preprocessing, filtering, batch correction, dimensionality reduction, vizualisation, clustering, differential analysis and gene set analysis.

package bioconductor-chromscape

(downloads) docker_bioconductor-chromscape



depends bioconductor-batchelor:


depends bioconductor-biocparallel:


depends bioconductor-consensusclusterplus:


depends bioconductor-delayedarray:


depends bioconductor-edger:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-rsamtools:


depends bioconductor-rtracklayer:


depends bioconductor-s4vectors:


depends bioconductor-scater:


depends bioconductor-scran:


depends bioconductor-singlecellexperiment:


depends bioconductor-summarizedexperiment:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-colorramps:

depends r-colourpicker:

depends r-coop:

depends r-dplyr:

depends r-dt:

depends r-forcats:

depends r-fs:

depends r-gggenes:

depends r-ggplot2:

depends r-ggrepel:

depends r-gridextra:

depends r-irlba:

depends r-jsonlite:

depends r-kableextra:

depends r-matrix:

depends r-matrixtests:

depends r-msigdbr:

depends r-plotly:

depends r-qs:

depends r-qualv:

depends r-rcpp:

depends r-rlist:

depends r-rtsne:

depends r-shiny:

depends r-shinycssloaders:

depends r-shinydashboard:

depends r-shinydashboardplus:

depends r-shinyfiles:

depends r-shinyhelper:

depends r-shinyjs:

depends r-shinywidgets:

depends r-stringdist:

depends r-stringr:

depends r-tibble:

depends r-tidyr:

depends r-umap:

depends r-viridis:



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-chromscape

and update with::

   mamba update bioconductor-chromscape

To create a new environment, run:

mamba create --name myenvname bioconductor-chromscape

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

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