recipe bioconductor-iseq

Bayesian Hierarchical Modeling of ChIP-seq Data Through Hidden Ising Models



GPL (>= 2)




biotools: iseq, doi: 10.1111/j.1541-0420.2009.01379.x

Bayesian hidden Ising models are implemented to identify IP-enriched genomic regions from ChIP-seq data. They can be used to analyze ChIP-seq data with and without controls and replicates.

package bioconductor-iseq

(downloads) docker_bioconductor-iseq



depends libblas:


depends libgcc-ng:


depends liblapack:


depends r-base:




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-iseq

and update with::

   mamba update bioconductor-iseq

To create a new environment, run:

mamba create --name myenvname bioconductor-iseq

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

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