Department of Mathematics, University of Turku, FI-20014 Turku, Finland.
Nucleic Acids Res. 2012 Jan;40(1):e1. doi: 10.1093/nar/gkr839. Epub 2011 Oct 18.
We developed a computational procedure for optimizing the binding site detections in a given ChIP-seq experiment by maximizing their reproducibility under bootstrap sampling. We demonstrate how the procedure can improve the detection accuracies beyond those obtained with the default settings of popular peak calling software, or inform the user whether the peak detection results are compromised, circumventing the need for arbitrary re-iterative peak calling under varying parameter settings. The generic, open-source implementation is easily extendable to accommodate additional features and to promote its widespread application in future ChIP-seq studies. The peakROTS R-package and user guide are freely available at http://www.nic.funet.fi/pub/sci/molbio/peakROTS.
我们开发了一种计算程序,通过在自举采样下最大化其重现性来优化给定 ChIP-seq 实验中的结合位点检测。我们展示了该程序如何在不使用流行的峰调用软件的默认设置的情况下提高检测精度,或者通知用户峰检测结果是否受到影响,从而避免在不同参数设置下进行任意迭代的峰调用。通用的开源实现可以轻松扩展以适应其他功能,并促进其在未来的 ChIP-seq 研究中的广泛应用。peakROTS R 包和用户指南可在 http://www.nic.funet.fi/pub/sci/molbio/peakROTS 免费获得。