Package Recipe 'bioconductor-chippeakanno'

recipe bioconductor-chippeakanno

Batch annotation of the peaks identified from either ChIP-seq, ChIP-chip experiments, or any experiments that result in large number of genomic interval data

Homepage:: https://bioconductor.org/packages/3.20/bioc/html/ChIPpeakAnno.html
License:: GPL (>= 2)
Recipe:: /bioconductor-chippeakanno/meta.yaml
Links:: biotools: chippeakanno

The package encompasses a range of functions for identifying the closest gene, exon, miRNA, or custom features—such as highly conserved elements and user-supplied transcription factor binding sites. Additionally, users can retrieve sequences around the peaks and obtain enriched Gene Ontology (GO) or Pathway terms. In version 2.0.5 and beyond, new functionalities have been introduced. These include features for identifying peaks associated with bi-directional promoters along with summary statistics (peaksNearBDP), summarizing motif occurrences in peaks (summarizePatternInPeaks), and associating additional identifiers with annotated peaks or enrichedGO (addGeneIDs). The package integrates with various other packages such as biomaRt, IRanges, Biostrings, BSgenome, GO.db, multtest, and stat to enhance its analytical capabilities.

package bioconductor-chippeakanno¶

Versions:

3.44.0-0, 3.40.0-0, 3.36.0-0, 3.34.1-0, 3.32.0-0, 3.28.0-0, 3.26.0-0, 3.24.1-0, 3.24.0-0,

3.44.0-0, 3.40.0-0, 3.36.0-0, 3.34.1-0, 3.32.0-0, 3.28.0-0, 3.26.0-0, 3.24.1-0, 3.24.0-0, 3.22.0-0, 3.20.0-0, 3.18.2-0, 3.16.0-0, 3.14.2-0, 3.12.0-0, 3.10.2-0

Depends:

on bioconductor-annotationdbi >=1.72.0,<1.73.0
on bioconductor-biocgenerics >=0.56.0,<0.57.0
on bioconductor-biomart >=2.66.0,<2.67.0
on bioconductor-biostrings >=2.78.0,<2.79.0
on bioconductor-ensembldb >=2.34.0,<2.35.0
on bioconductor-genomeinfodb >=1.46.0,<1.47.0
on bioconductor-genomicalignments >=1.46.0,<1.47.0
on bioconductor-genomicfeatures >=1.62.0,<1.63.0
on bioconductor-genomicranges >=1.62.0,<1.63.0
on bioconductor-graph >=1.88.0,<1.89.0
on bioconductor-interactionset >=1.38.0,<1.39.0
on bioconductor-iranges >=2.44.0,<2.45.0
on bioconductor-keggrest >=1.50.0,<1.51.0
on bioconductor-multtest >=2.66.0,<2.67.0
on bioconductor-pwalign >=1.6.0,<1.7.0
on bioconductor-rbgl >=1.86.0,<1.87.0
on bioconductor-regioner >=1.42.0,<1.43.0
on bioconductor-rsamtools >=2.26.0,<2.27.0
on bioconductor-rtracklayer >=1.70.0,<1.71.0
on bioconductor-s4vectors >=0.48.0,<0.49.0
on bioconductor-summarizedexperiment >=1.40.0,<1.41.0
on bioconductor-universalmotif >=1.28.0,<1.29.0
on r-base >=4.5,<4.6.0a0
on r-data.table
on r-dbi
on r-dplyr
on r-ggplot2
on r-matrixstats
on r-scales
on r-stringr
on r-tibble
on r-tidyr
on r-venndiagram

Additional platforms:

Installation¶

You need a conda-compatible package manager (currently either pixi, conda, or micromamba) and the Bioconda channel already activated (see Usage). Below, we show how to install with either pixi or conda (for micromamba and mamba, commands are essentially the same as with conda).

Pixi¶

With pixi installed and the Bioconda channel set up (see Usage), to install globally, run:

pixi global install bioconductor-chippeakanno

to add into an existing workspace instead, run:

pixi add bioconductor-chippeakanno

In the latter case, make sure to first add bioconda and conda-forge to the channels considered by the workspace:

pixi workspace channel add conda-forge
pixi workspace channel add bioconda

Conda¶

With conda installed and the Bioconda channel set up (see Usage), to install into an existing and activated environment, run:

conda install bioconductor-chippeakanno

Alternatively, to install into a new environment, run:

conda create -n envname bioconductor-chippeakanno

with envname being the name of the desired environment.

Container¶

Alternatively, every Bioconda package is available as a container image for usage with your preferred container runtime. For e.g. docker, run:

docker pull quay.io/biocontainers/bioconductor-chippeakanno:<tag>

(see bioconductor-chippeakanno/tags for valid values for <tag>).

Integrated deployment¶

Finally, note that many scientific workflow management systems directly integrate both conda and container based software deployment. Thus, workflow steps can be often directly annotated to use the package, leading to automatic deployment by the respective workflow management system, thereby improving reproducibility and transparency. Check the documentation of your workflow management system to find out about the integration.

Download stats¶

Link to this page¶

Render an badge with the following MarkDown:

[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/bioconductor-chippeakanno/README.html)