recipe r-signac

A framework for the analysis and exploration of single-cell chromatin data. The 'Signac' package contains functions for quantifying single-cell chromatin data, computing per-cell quality control metrics, dimension reduction and normalization, visualization, and DNA sequence motif analysis. Reference: Stuart and Butler et al. (2019) <doi:10.1016/j.cell.2019.05.031>.






package r-signac

(downloads) docker_r-signac



depends bioconductor-biocgenerics:

depends bioconductor-genomeinfodb:


depends bioconductor-genomicranges:

depends bioconductor-iranges:

depends bioconductor-rsamtools:

depends bioconductor-s4vectors:

depends libgcc-ng:


depends libstdcxx-ng:


depends r-base:


depends r-data.table:

depends r-dplyr:


depends r-fastmatch:

depends r-future:

depends r-future.apply:

depends r-ggplot2:

depends r-irlba:

depends r-matrix:

depends r-patchwork:

depends r-pbapply:

depends r-rcpp:

depends r-rcpproll:

depends r-rlang:

depends r-scales:

depends r-seuratobject:


depends r-stringi:

depends r-tidyr:

depends r-tidyselect:

depends r-vctrs:



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 r-signac

and update with::

   mamba update r-signac

To create a new environment, run:

mamba create --name myenvname r-signac

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

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