Brundle: Normalisation Tools for Inter-Condition Variability of ChIP-Seq Data

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) <doi:10.1101/182261>.

Getting started

Package details

AuthorAndrew N Holding
Bioconductor views ChIPSeq Sequencing Software Technology
MaintainerAndrew N Holding <>
LicenseCC BY 4.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the Brundle package in your browser

Any scripts or data that you put into this service are public.

Brundle documentation built on May 2, 2019, 10:14 a.m.