recipe bioconductor-chippeakanno

Batch annotation of the peaks identified from either ChIP-seq, ChIP-chip experiments or any experiments resulted in large number of chromosome ranges



GPL (>= 2)




biotools: chippeakanno

The package includes functions to retrieve the sequences around the peak, obtain enriched Gene Ontology (GO) terms, find the nearest gene, exon, miRNA or custom features such as most conserved elements and other transcription factor binding sites supplied by users. Starting 2.0.5, new functions have been added for finding the peaks with bi-directional promoters with summary statistics (peaksNearBDP), for summarizing the occurrence of motifs in peaks (summarizePatternInPeaks) and for adding other IDs to annotated peaks or enrichedGO (addGeneIDs). This package leverages the biomaRt, IRanges, Biostrings, BSgenome, GO.db, multtest and stat packages.

package bioconductor-chippeakanno

(downloads) docker_bioconductor-chippeakanno



depends bioconductor-annotationdbi:


depends bioconductor-biocgenerics:


depends bioconductor-biomart:


depends bioconductor-biostrings:


depends bioconductor-ensembldb:


depends bioconductor-genomeinfodb:


depends bioconductor-genomicalignments:


depends bioconductor-genomicfeatures:


depends bioconductor-genomicranges:


depends bioconductor-graph:


depends bioconductor-interactionset:


depends bioconductor-iranges:


depends bioconductor-keggrest:


depends bioconductor-multtest:


depends bioconductor-rbgl:


depends bioconductor-regioner:


depends bioconductor-rsamtools:


depends bioconductor-rtracklayer:


depends bioconductor-s4vectors:


depends bioconductor-summarizedexperiment:


depends r-base:


depends r-dbi:

depends r-dplyr:

depends r-ggplot2:

depends r-matrixstats:

depends r-venndiagram:



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-chippeakanno

and update with::

   mamba update bioconductor-chippeakanno

To create a new environment, run:

mamba create --name myenvname bioconductor-chippeakanno

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

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