Sole-Search: an integrated analysis program for peak detection and functional annotation using ChIP-seq data.
Sole-Search: an integrated analysis program for peak detection and functional annotation using ChIP-seq data.
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DOI：
10.1093/nar/gkp1012
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发表时间：
2010-01
影响因子：
14.9
通讯作者：
Farnham PJ
中科院分区：
文献类型：
--
作者：
Blahnik KR;Dou L;O'Geen H;McPhillips T;Xu X;Cao AR;Iyengar S;Nicolet CM;Ludäscher B;Korf I;Farnham PJ
下一代测序正在彻底改变整个人类基因组中转录因子结合位点的鉴定。然而，使用染色质免疫沉淀和高通量测序收集的大型数据集的生物信息学分析通常是阻碍研究人员试图从他们的实验中获得生物学见解的障碍。我们开发了集成的峰召唤和分析软件（Sole-Search），它可以通过用户友好的界面获得，并且(i)将原始数据转换为基因组浏览器上可视化的格式，（ii）使用基于统计的方法输出峰位置排名，克服了假阳性的重大问题，（iii）识别离每个峰最近的基因，（iv）相对于基因结构对每个峰的位置进行分类。(v)提供诸如每条染色体和每个基因的结合位点数目等信息；（vi）允许用户确定两个不同实验之间的重叠。此外，该程序执行输入基因组的扩增和删除区域的分析。该软件是基于网络和自动化的，允许所有调查人员轻松和即时访问。我们通过收集、分析和比较六种不同的人类转录因子/细胞系组合的ChIP-seq数据来展示我们软件的实用性。
Next-generation sequencing is revolutionizing the identification of transcription factor binding sites throughout the human genome. However, the bioinformatics analysis of large datasets collected using chromatin immunoprecipitation and high-throughput sequencing is often a roadblock that impedes researchers in their attempts to gain biological insights from their experiments. We have developed integrated peak-calling and analysis software (Sole-Search) which is available through a user-friendly interface and (i) converts raw data into a format for visualization on a genome browser, (ii) outputs ranked peak locations using a statistically based method that overcomes the significant problem of false positives, (iii) identifies the gene nearest to each peak, (iv) classifies the location of each peak relative to gene structure, (v) provides information such as the number of binding sites per chromosome and per gene and (vi) allows the user to determine overlap between two different experiments. In addition, the program performs an analysis of amplified and deleted regions of the input genome. This software is web-based and automated, allowing easy and immediate access to all investigators. We demonstrate the utility of our software by collecting, analyzing and comparing ChIP-seq data for six different human transcription factors/cell line combinations.
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