recipe bioconductor-chic

Quality Control Pipeline for ChIP-Seq Data






Quality control (QC) pipeline for ChIP-seq data using a comprehensive set of QC metrics, including previously proposed metrics as well as novel ones, based on local characteristics of the enrichment profile. The package provides functions to calculate a set of QC metrics, a compendium with reference values and machine learning models to score sample quality.

package bioconductor-chic

(downloads) docker_bioconductor-chic



depends bioconductor-biocgenerics:




depends bioconductor-genomeintervals:


depends bioconductor-genomicranges:


depends bioconductor-iranges:


depends bioconductor-rsamtools:


depends bioconductor-s4vectors:


depends r-base:


depends r-caret:

depends r-catools:

depends r-progress:

depends r-randomforest:

depends r-spp:



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-chic

and update with::

   mamba update bioconductor-chic

To create a new environment, run:

mamba create --name myenvname bioconductor-chic

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

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