recipe bioconductor-seqsetvis

Set Based Visualizations for Next-Gen Sequencing Data






seqsetvis enables the visualization and analysis of sets of genomic sites in next gen sequencing data. Although seqsetvis was designed for the comparison of mulitple ChIP-seq samples, this package is domain-agnostic and allows the processing of multiple genomic coordinate files (bed-like files) and signal files (bigwig files pileups from bam file).

package bioconductor-seqsetvis

(downloads) docker_bioconductor-seqsetvis



depends bioconductor-genomeinfodb:


depends bioconductor-genomicalignments:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-limma:


depends bioconductor-rsamtools:


depends bioconductor-rtracklayer:


depends bioconductor-s4vectors:


depends r-base:


depends r-cowplot:

depends r-data.table:

depends r-eulerr:

depends r-ggplot2:

depends r-ggplotify:

depends r-pbapply:

depends r-pbmcapply:

depends r-png:

depends r-rcolorbrewer:

depends r-scales:

depends r-upsetr:



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-seqsetvis

and update with::

   mamba update bioconductor-seqsetvis

To create a new environment, run:

mamba create --name myenvname bioconductor-seqsetvis

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

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