School of Life Science and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China.
BMC Bioinformatics. 2010 Feb 9;11:81. doi: 10.1186/1471-2105-11-81.
ChIP-Seq, which combines chromatin immunoprecipitation (ChIP) with high-throughput massively parallel sequencing, is increasingly being used for identification of protein-DNA interactions in vivo in the genome. However, to maximize the effectiveness of data analysis of such sequences requires the development of new algorithms that are able to accurately predict DNA-protein binding sites.
Here, we present SIPeS (Site Identification from Paired-end Sequencing), a novel algorithm for precise identification of binding sites from short reads generated by paired-end solexa ChIP-Seq technology. In this paper we used ChIP-Seq data from the Arabidopsis basic helix-loop-helix transcription factor ABORTED MICROSPORES (AMS), which is expressed within the anther during pollen development, the results show that SIPeS has better resolution for binding site identification compared to two existing ChIP-Seq peak detection algorithms, Cisgenome and MACS.
When compared to Cisgenome and MACS, SIPeS shows better resolution for binding site discovery. Moreover, SIPeS is designed to calculate the mappable genome length accurately with the fragment length based on the paired-end reads. Dynamic baselines are also employed to effectively discriminate closely adjacent binding sites, for effective binding sites discovery, which is of particular value when working with high-density genomes.
ChIP-Seq 技术结合了染色质免疫沉淀（ChIP）和高通量平行测序，越来越多地用于在体内鉴定基因组中蛋白质与 DNA 的相互作用。然而，为了最大限度地提高此类序列数据分析的效果，需要开发能够准确预测 DNA-蛋白质结合位点的新算法。
在这里，我们提出了 SIPeS（来自配对末端测序的位点识别），这是一种用于从基于配对末端焦磷酸测序的 ChIP-Seq 技术生成的短读序列中精确识别结合位点的新算法。在本文中，我们使用了拟南芥基本螺旋-环-螺旋转录因子 ABORTED MICROSPORES（AMS）的 ChIP-Seq 数据，该转录因子在花粉发育过程中在花药内表达，结果表明，与现有的两种 ChIP-Seq 峰检测算法 Cisgenome 和 MACS 相比，SIPeS 具有更好的结合位点识别分辨率。
与 Cisgenome 和 MACS 相比，SIPeS 显示出更好的结合位点发现分辨率。此外，SIPeS 旨在根据基于配对末端读取的片段长度准确计算可映射基因组长度。还采用了动态基线来有效区分紧密相邻的结合位点，以便有效地发现结合位点，这在处理高密度基因组时具有特别重要的价值。
