andrewholding/Brundle: Normalisation Tools for Inter-Condition Variability of ChIP-Seq Data
Version 1.0.7

Inter-sample condition variability is a key challenge of normalising ChIP-seq data. This implementation uses either spike-in or a second factor as a control for normalisation. Input can either be from 'DiffBind' or a matrix formatted for 'DESeq2'. The output is either a 'DiffBind' object or the default 'DESeq2' output. Either can then be processed as normal. Supporting manuscript Guertin, Markowetz and Holding (2017) .

Getting started

Package details

AuthorAndrew N Holding
Bioconductor views ChIPSeq Sequencing Software Technology
MaintainerAndrew N Holding <[email protected]>
LicenseCC BY 4.0
Version1.0.7
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("andrewholding/Brundle")
andrewholding/Brundle documentation built on Jan. 1, 2018, 6:15 p.m.