descostesn/ChIPSeqSpike: ChIP-Seq data scaling according to spike-in control
Version 0.99.20

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.

Getting started

Package details

AuthorNicolas Descostes
Bioconductor views ChIPSeq Coverage DataImport DifferentialMethylation Epigenetics HistoneModification Normalization Sequencing Transcription
MaintainerNicolas Descostes <[email protected]>
LicenseArtistic-2.0
Version0.99.20
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("descostesn/ChIPSeqSpike")
descostesn/ChIPSeqSpike documentation built on Jan. 29, 2018, 3 p.m.