recipe bioconductor-intercellar

InterCellar: an R-Shiny app for interactive analysis and exploration of cell-cell communication in single-cell transcriptomics






InterCellar is implemented as an R/Bioconductor Package containing a Shiny app that allows users to interactively analyze cell-cell communication from scRNA-seq data. Starting from precomputed ligand-receptor interactions, InterCellar provides filtering options, annotations and multiple visualizations to explore clusters, genes and functions. Finally, based on functional annotation from Gene Ontology and pathway databases, InterCellar implements data-driven analyses to investigate cell-cell communication in one or multiple conditions.

package bioconductor-intercellar

(downloads) docker_bioconductor-intercellar



depends bioconductor-biomart:


depends bioconductor-complexheatmap:


depends r-base:


depends r-circlize:

depends r-colorspace:

depends r-colourpicker:

depends r-config:

depends r-data.table:

depends r-dendextend:

depends r-dplyr:

depends r-dt:

depends r-factoextra:

depends r-fmsb:

depends r-fs:

depends r-ggplot2:

depends r-golem:

depends r-htmltools:

depends r-htmlwidgets:

depends r-igraph:

depends r-plotly:

depends r-plyr:

depends r-readxl:

depends r-rlang:

depends r-scales:

depends r-shiny:

depends r-shinyalert:

depends r-shinycssloaders:

depends r-shinydashboard:

depends r-shinyfeedback:

depends r-shinyfiles:

depends r-signal:

depends r-tibble:

depends r-tidyr:

depends r-umap:

depends r-visnetwork:

depends r-wordcloud2:



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-intercellar

and update with::

   mamba update bioconductor-intercellar

To create a new environment, run:

mamba create --name myenvname bioconductor-intercellar

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

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