Background Recent large-scale undertakings such as ENCODE and Roadmap Epigenomics have generated experimental data mapped to the human reference genome (as genomic tracks) representing a variety of functional elements across a large number of cell types. Despite the high potential value of these publicly available data for a broad variety of investigations, little attention has been given to the analytical methodology necessary for their widespread utilisation. Findings We here present a first principled treatment of the analysis of collections of genomic tracks. We have developed novel computational and statistical methodology to permit comparative and confirmatory analyses across multiple and disparate data sources. We delineate a set of generic questions that are useful across a broad range of investigations and discuss the implications of choosing different statistical measures and null models. Examples include contrasting analyses across different tissues or diseases. The methodology has been implemented in a comprehensive open-source software system, the GSuite HyperBrowser. To make the functionality accessible to biologists, and to facilitate reproducible analysis, we have also developed a web-based interface providing an expertly guided and customizable way of utilizing the methodology. With this system, many novel biological questions can flexibly be posed and rapidly answered. Conclusions Through a combination of streamlined data acquisition, interoperable representation of dataset collections, and customizable statistical analysis with guided setup and interpretation, the GSuite HyperBrowser represents a first comprehensive solution for integrative analysis of track collections across the genome and epigenome. The software is available at: https://hyperbrowser.uio.no.

中文翻译：

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GSuite HyperBrowser：跨基因组和表观基因组的数据集集合的综合分析。

背景技术近来诸如ENCODE和Roadmap Epigenomics之类的大规模事业已经产生了映射到人类参考基因组（作为基因组轨迹）的实验数据，其代表了跨越多种细胞类型的多种功能元件。尽管这些公开可用的数据对于各种调查具有很高的潜在价值，但很少关注用于其广泛使用的分析方法。研究结果我们在这里介绍了对基因组轨迹分析的第一个原则性处理。我们开发了新颖的计算和统计方法，可以对多个不同数据源进行比较和确认分析。我们描述了一组在广泛调查中有用的通用问题，并讨论了选择不同的统计量度和无效模型的含义。例子包括对不同组织或疾病的对比分析。该方法已在全面的开源软件系统GSuite HyperBrowser中实现。为了使生物学家可以使用该功能并促进可重复的分析，我们还开发了基于Web的界面，为使用该方法提供了专家指导和可定制的方式。使用该系统，可以灵活地提出并迅速回答许多新颖的生物学问题。结论通过简化的数据采集，可互操作的数据集表示形式的组合，GSuite HyperBrowser以及具有指导性的设置和解释功能的可定制统计分析，代表了第一个综合解决方案，用于对基因组和表观基因组中的轨迹集合进行综合分析。该软件位于：https://hyperbrowser.uio.no。