HiC-bench: comprehensive and reproducible Hi-C data analysis designed for parameter exploration and benchmarking.

HiC-bench: comprehensive and reproducible Hi-C data analysis designed for parameter exploration and benchmarking.
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DOI:
10.1186/s12864-016-3387-6
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发表时间:
2017-01-05
期刊:
影响因子:
4.4
通讯作者:
Tsirigos A
Tsirigos A
中科院分区:
生物学2区
文献类型:
--
作者:
Lazaris C;Kelly S;Ntziachristos P;Aifantis I;Tsirigos A

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染色质构象捕获技术在过去几年中迅速发展,并以前所未有的分辨率为基因组组织提供了新的见解。 Hi-C 数据的分析非常复杂且计算量大,涉及多项任务并且需要可靠的质量评估。这导致了多种用于处理 Hi-C 数据的工具和方法的开发。然而,大多数现有工具并未涵盖分析的所有方面,并且仅提供很少的质量评估选项。此外,多种工具的可用性使科学家们想知道如何最佳地使用这些工具和相关参数,以及如何解释和解决潜在的差异。最重要的是,研究人员需要确保参数和/或方法的轻微变化不会影响他们的研究结论。为了解决这些问题(比较、探索和重现),我们引入了 HiC-bench,这是一个可配置的计算平台,用于对 Hi-C 测序数据进行全面且可重现的分析。 HiC-bench 使用已发布的工具和我们自己的工具执行所有常见的 Hi-C 分析任务,例如对齐、过滤、接触矩阵生成和标准化、拓扑域识别、特定交互的评分和注释。我们还嵌入了执行质量评估和可视化的各种任务。 HiC-bench 作为数据流平台实施,强调分析的再现性。此外,用户可以轻松地以组合方式执行不同工具的参数探索和比较,并考虑每个管道任务中的所有所需参数设置。这一独特的功能有助于复杂基准研究的设计和执行,这些基准研究可能涉及分析的每个步骤中多种工具/参数选择的组合。为了证明我们平台的实用性,我们对现有和新的 TAD 调用程序进行了全面的基准测试,探索不同的矩阵校正方法、参数设置和测序深度。用户可以通过添加更多可用的工具来扩展我们的管道。 HiC-bench 包含一个易于使用且可扩展的平台,用于全面分析 Hi-C 数据集。我们期望它将促进当前的分析,并帮助科学家在三维基因组组织领域制定和测试新的假设。本文的在线版本 (doi:10.1186/s12864-016-3387-6) 包含补充材料,可供授权用户使用。
Chromatin conformation capture techniques have evolved rapidly over the last few years and have provided new insights into genome organization at an unprecedented resolution. Analysis of Hi-C data is complex and computationally intensive involving multiple tasks and requiring robust quality assessment. This has led to the development of several tools and methods for processing Hi-C data. However, most of the existing tools do not cover all aspects of the analysis and only offer few quality assessment options. Additionally, availability of a multitude of tools makes scientists wonder how these tools and associated parameters can be optimally used, and how potential discrepancies can be interpreted and resolved. Most importantly, investigators need to be ensured that slight changes in parameters and/or methods do not affect the conclusions of their studies. To address these issues (compare, explore and reproduce), we introduce HiC-bench, a configurable computational platform for comprehensive and reproducible analysis of Hi-C sequencing data. HiC-bench performs all common Hi-C analysis tasks, such as alignment, filtering, contact matrix generation and normalization, identification of topological domains, scoring and annotation of specific interactions using both published tools and our own. We have also embedded various tasks that perform quality assessment and visualization. HiC-bench is implemented as a data flow platform with an emphasis on analysis reproducibility. Additionally, the user can readily perform parameter exploration and comparison of different tools in a combinatorial manner that takes into account all desired parameter settings in each pipeline task. This unique feature facilitates the design and execution of complex benchmark studies that may involve combinations of multiple tool/parameter choices in each step of the analysis. To demonstrate the usefulness of our platform, we performed a comprehensive benchmark of existing and new TAD callers exploring different matrix correction methods, parameter settings and sequencing depths. Users can extend our pipeline by adding more tools as they become available. HiC-bench consists an easy-to-use and extensible platform for comprehensive analysis of Hi-C datasets. We expect that it will facilitate current analyses and help scientists formulate and test new hypotheses in the field of three-dimensional genome organization. The online version of this article (doi:10.1186/s12864-016-3387-6) contains supplementary material, which is available to authorized users.
染色体接触图的标准化。
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期刊: BMC genomics
影响因子: 4.4
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影响因子: --
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