recipe bioconductor-chipseqspike

Chromatin Immuno-Precipitation followed by Sequencing (ChIP-Seq) is used to determine the binding sites of any protein of interest, such as transcription factors or histones with or without a specific modification, at a genome scale. The many steps of the protocol can introduce biases that make ChIP-Seq more qualitative than quantitative. For instance, it was shown that global histone modification differences are not caught by traditional downstream data normalization techniques. A case study reported no differences in histone H3 lysine-27 trimethyl (H3K27me3) upon Ezh2 inhibitor treatment. To tackle this problem, external spike-in control were used to keep track of technical biases between conditions. Exogenous DNA from a different non-closely related species was inserted during the protocol to infer scaling factors that enabled an accurate normalization, thus revealing the inhibitor effect. ChIPSeqSpike offers tools for ChIP-Seq spike-in normalization. Ready to use scaled bigwig files and scaling factors values are obtained as output. ChIPSeqSpike also provides tools for ChIP-Seq spike-in assessment and analysis through a versatile collection of graphical functions.

Homepage

https://bioconductor.org/packages/3.9/bioc/html/ChIPSeqSpike.html

License

Artistic-2.0

Recipe

/bioconductor-chipseqspike/meta.yaml

package bioconductor-chipseqspike

(downloads) docker_bioconductor-chipseqspike

Versions

1.2.0-0

Depends bioconductor-biocgenerics

>=0.28.0,<0.29.0

Depends bioconductor-genomicranges

>=1.34.0,<1.35.0

Depends bioconductor-iranges

>=2.16.0,<2.17.0

Depends bioconductor-rsamtools

>=1.34.0,<1.35.0

Depends bioconductor-rtracklayer

>=1.42.0,<1.43.0

Depends bioconductor-s4vectors

>=0.20.0,<0.21.0

Depends bioconductor-seqplots

>=1.20.0,<1.21.0

Depends r-base

>=3.5.1,<3.5.2.0a0

Depends r-corrplot

Depends r-ggplot2

Depends r-lsd

Depends r-stringr

Requirements

Installation

With an activated Bioconda channel (see 2. Set up channels), install with:

conda install bioconductor-chipseqspike

and update with:

conda update bioconductor-chipseqspike

or use the docker container:

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

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