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An integrated ChIP-seq analysis platform with customizable workflows

机译:具有可自定义工作流程的集成ChIP-seq分析平台

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Background Chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq), enables unbiased and genome-wide mapping of protein-DNA interactions and epigenetic marks. The first step in ChIP-seq data analysis involves the identification of peaks (i.e., genomic locations with high density of mapped sequence reads). The next step consists of interpreting the biological meaning of the peaks through their association with known genes, pathways, regulatory elements, and integration with other experiments. Although several programs have been published for the analysis of ChIP-seq data, they often focus on the peak detection step and are usually not well suited for thorough, integrative analysis of the detected peaks. Results To address the peak interpretation challenge, we have developed ChIPseeqer, an integrative, comprehensive, fast and user-friendly computational framework for in-depth analysis of ChIP-seq datasets. The novelty of our approach is the capability to combine several computational tools in order to create easily customized workflows that can be adapted to the user's needs and objectives. In this paper, we describe the main components of the ChIPseeqer framework, and also demonstrate the utility and diversity of the analyses offered, by analyzing a published ChIP-seq dataset. Conclusions ChIPseeqer facilitates ChIP-seq data analysis by offering a flexible and powerful set of computational tools that can be used in combination with one another. The framework is freely available as a user-friendly GUI application, but all programs are also executable from the command line, thus providing flexibility and automatability for advanced users.
机译:背景染色质免疫沉淀后再进行下一代测序(ChIP-seq),可实现蛋白质-DNA相互作用和表观遗传标记的无偏性和全基因组图谱。 ChIP-seq数据分析的第一步涉及鉴定峰(即具有高密度映射序列读数的基因组位置)。下一步包括通过与已知基因,途径,调控元件结合以及与其他实验整合来解释峰的生物学含义。尽管已经发布了一些程序来分析ChIP-seq数据,但它们通常专注于峰检测步骤,通常不适合对检测到的峰进行全面,综合的分析。结果为了解决峰解释难题,我们开发了ChIPseeqer,这是一个集成,全面,快速且用户友好的计算框架,用于深入分析ChIP-seq数据集。我们方法的新颖之处在于能够组合多种计算工具,以创建可轻松适应用户需求和目标的自定义工作流。在本文中,我们描述了ChIPseeqer框架的主要组成部分,并通过分析已发布的ChIP-seq数据集证明了所提供分析的实用性和多样性。结论ChIPseeqer通过提供一组可以相互结合使用的灵活而强大的计算工具来促进ChIP-seq数据分析。该框架可作为用户友好的GUI应用程序免费提供,但所有程序也都可以从命令行执行,因此为高级用户提供了灵活性和自动化性。

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