Department of Oncology, University of Cambridge, Li Ka Shing Centre, Cambridge, UK.
Bioinformatics. 2011 Mar 1;27(5):713-4. doi: 10.1093/bioinformatics/btq685. Epub 2011 Jan 17.
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.
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.
Available as part of BioConductor version 2.6. URL: http://bioconductor.org/packages/release/bioc/html/BayesPeak.html.
在 ChIP-seq 数据中识别感兴趣的基因组区域，通常称为峰调用，旨在找到转录因子结合位点、修饰组蛋白或核小体的位置。BayesPeak 算法是为了使用贝叶斯统计技术来模拟数据结构而开发的，被证明是一种可靠的方法，但没有全基因组的实现。
在本说明中，我们介绍了 BayesPeak，这是一个用于基因组范围峰调用的 R 包，它提供了 BayesPeak 算法的灵活实现，并且与下游的 BioConductor 包兼容。BayesPeak 包引入了一种新的方法来总结后验概率输出，以及处理过拟合的方法和支持并行处理。我们简要比较了该包与其他常用的峰调用程序。
可作为 BioConductor 版本 2.6 的一部分使用。网址：http://bioconductor.org/packages/release/bioc/html/BayesPeak.html。
