recipe bioconductor-chromstar

Combinatorial and Differential Chromatin State Analysis for ChIP-Seq Data







biotools: chromstar, doi: 10.1101/038612

This package implements functions for combinatorial and differential analysis of ChIP-seq data. It includes uni- and multivariate peak-calling, export to genome browser viewable files, and functions for enrichment analyses.

package bioconductor-chromstar

(downloads) docker_bioconductor-chromstar



depends bioconductor-bamsignals:


depends bioconductor-biocgenerics:


depends bioconductor-chromstardata:


depends bioconductor-genomeinfodb:


depends bioconductor-genomicalignments:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-rsamtools:


depends bioconductor-s4vectors:


depends libblas:


depends libgcc-ng:


depends liblapack:


depends libstdcxx-ng:


depends r-base:


depends r-doparallel:

depends r-foreach:

depends r-ggplot2:

depends r-mvtnorm:

depends r-reshape2:



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-chromstar

and update with::

   mamba update bioconductor-chromstar

To create a new environment, run:

mamba create --name myenvname bioconductor-chromstar

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

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