andrewholding/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
Browse package contents
Package details |
|
|---|---|
| Author | Andrew N Holding |
| Bioconductor views | ChIPSeq Sequencing Software Technology |
| Maintainer | Andrew N Holding <andrew.holding@cruk.cam.ac.uk> |
| License | CC BY 4.0 |
| Version | 1.0.9 |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
|
