Peak Finder Metaserver - a novel application for finding peaks in ChIP-seq data.
Peak Finder Metaserver - a novel application for finding peaks in ChIP-seq data.
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DOI：
10.1186/1471-2105-14-280
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发表时间：
2013-09-23
影响因子：
3
通讯作者：
Komorowski J
中科院分区：
文献类型：
--
作者：
Kruczyk M;Umer HM;Enroth S;Komorowski J
在 ChIP-seq 中寻找峰值是生物推理中的一个重要过程。在某些情况下，例如定位具有特定组蛋白修饰的核小体或寻找转录因子结合特异性，检测到的峰的精度起着重要作用。有多种基于不同算法（例如 MACS、Erange 和 HPeak）寻找峰值的应用程序（称为峰值查找器）。基准研究表明，现有的峰值查找器可以识别同一数据集的不同峰值，但不知道哪一个是最准确的。我们提出了第一个元服务器，称为 Peak Finder MetaServer (PFMS)，它从多个峰值查找器收集结果并生成一致峰值。我们的应用程序接受三种标准 ChIP-seq 数据格式：BED、BAM 和 SAM。检查了七种广泛使用的寻峰器的灵敏度和特异性。在实验中，我们使用了三个先前研究的转录因子 (TF) ChIP-seq 数据集，并确定了三个选定的峰值查找器，与其余四个相比，它们返回的结果具有高特异性和非常好的灵敏度。我们还在相同的 TF 数据集上使用三个选定的峰值查找器运行 PFMS，并获得了比单独的峰值查找器更高的特异性和灵敏度。我们表明，将多达七个峰值查找器的输出组合起来比单个峰值查找器产生更好的结果。此外，七个峰值查找器中的三个优于其余四个，并且使用这三个峰值查找器运行 PFMS 会返回更准确的结果。 PFMS 的另一个附加价值是每个包含的峰值查找器返回的峰值的单独报告。
Finding peaks in ChIP-seq is an important process in biological inference. In some cases, such as positioning nucleosomes with specific histone modifications or finding transcription factor binding specificities, the precision of the detected peak plays a significant role. There are several applications for finding peaks (called peak finders) based on different algorithms (e.g. MACS, Erange and HPeak). Benchmark studies have shown that the existing peak finders identify different peaks for the same dataset and it is not known which one is the most accurate. We present the first meta-server called Peak Finder MetaServer (PFMS) that collects results from several peak finders and produces consensus peaks. Our application accepts three standard ChIP-seq data formats: BED, BAM, and SAM. Sensitivity and specificity of seven widely used peak finders were examined. For the experiments we used three previously studied Transcription Factors (TF) ChIP-seq datasets and identified three of the selected peak finders that returned results with high specificity and very good sensitivity compared to the remaining four. We also ran PFMS using the three selected peak finders on the same TF datasets and achieved higher specificity and sensitivity than the peak finders individually. We show that combining outputs from up to seven peak finders yields better results than individual peak finders. In addition, three of the seven peak finders outperform the remaining four, and running PFMS with these three returns even more accurate results. Another added value of PFMS is a separate report of the peaks returned by each of the included peak finders.
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DOI：
10.1093/bioinformatics/btq033
发表时间：
2010-03-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Quinlan AR;Hall IM
通讯作者：
Hall IM
影响因子：
46.9
作者：
Ji, Hongkai;Jiang, Hui;Ma, Wenxiu;Johnson, David S.;Myers, Richard M.;Wong, Wing H.
通讯作者：
Wong, Wing H.
影响因子：
48
作者：
Pepke, Shirley;Wold, Barbara;Mortazavi, Ali
通讯作者：
Mortazavi, Ali
影响因子：
14.9
作者：
Jothi, Raja;Cuddapah, Suresh;Barski, Artem;Cui, Kairong;Zhao, Keji
通讯作者：
Zhao, Keji
影响因子：
48
作者：
Mortazavi, Ali;Williams, Brian A.;Wold, Barbara
通讯作者：
Wold, Barbara