BayesPeak-an R package for analysing ChIP-seq data

Jonathan Cairns, Christiana Spyrou, Rory Stark, Mike L. Smith, Andy G. Lynch, Simon Tavaré

Research output: Contribution to journalArticlepeer-review

32 Scopus citations

Abstract

Motivation: Identification of genomic regions of interest in ChIP-seq data, commonly referred to as peak-calling, aims to find the locations of transcription factor binding sites, modified histones or nucleosomes. The BayesPeak algorithm was developed to model the data structure using Bayesian statistical techniques and was shown to be a reliable method, but did not have a full-genome implementation. Results: In this note we present BayesPeak, an R package for genome-wide peak-calling that provides a flexible implementation of the BayesPeak algorithm and is compatible with downstream BioConductor packages. The BayesPeak package introduces a new method for summarizing posterior probability output, along with methods for handling overfitting and support for parallel processing. We briefly compare the package with other common peak-callers.

Original languageEnglish
Article numberbtq685
Pages (from-to)713-714
Number of pages2
JournalBioinformatics
Volume27
Issue number5
DOIs
StatePublished - Mar 2011
Externally publishedYes

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