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Implementing Metabolomics Analyses into Galaxy Workflows: Towards Genome-Metabolome Large-Scale Data Fusion

在 Galaxy 工作流程中实施代谢组学分析：迈向基因组-代谢组大规模数据融合

基本信息

批准号：
NE/K011294/1
负责人：
Mark Viant
金额：
$ 3.5万
依托单位：
University of Birmingham
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2013
资助国家：
英国
起止时间：
2013 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FK011294%2F1
关键词：
Implementing Metabolomics Analyses into Galaxy

项目摘要

"Genomic and post-genomic studies are transforming our mechanistic understanding of organism-environment interactions." While this statement is certainly true, it masks many of the major challenges that have had to be overcome during the last decade. Today, genomics approaches are widely used by researchers from across the breadth of NERC science, utilising established (and ever cheaper) technologies and analysis pipelines, and delivering high impact publications. The same cannot yet be said for metabolomics, which is a considerably less mature approach, both analytically and computationally. The analytical challenges in metabolomics have restricted its use to experts of analytical chemistry, while the computational challenges have restricted the knowledge that can be mined from these rich datasets. Here we address the latter point, drawing from the wisdom and experience of genomics researchers. One of the reasons for the success of environmental genomics is that biologists, without an in-depth knowledge of biostatistics and programming, have been able to construct and execute Next Gen Sequencing (NGS) data analyses using standardised workflows. Galaxy (http://galaxyproject.org/) - headlined as "Online bioinformatics analysis for everyone" - has emerged as the leading open-source workflow platform for NGS data analysis, with many standard processing tools accessible from its Web-based user interface. This workflow software is also being applied successfully to proteomics and chemo-informatics. Researchers at BGI (Beijing Genomics Institute) in China, our Project Partner on this application, have considerable expertise in Galaxy, since this web-based data analysis and workflow system forms the basis of its data analysis platform. They also have close links with the Galaxy development team. We propose to 'hop' Dr Davidson from Professor Viant's environmental metabolomics laboratory and NBAF-B at the University of Birmingham into a computational laboratory at BGI-Hong Kong. Here he will gain specialist expertise in Galaxy workflows and implement our existing metabolomics pipelines into Galaxy. This is an extremely important step towards making metabolomics analysis pipelines more effective (by integrating powerful algorithms from the ever growing toolbox of metabolomics analysis methods), more standardised (enabling greater cross comparison of results from different studies), and considerably more accessible to biologists. Our aim is for both data and analysis tools to be accessible from a software platform that provides a single, user-friendly interface for developing computational pipelines in a form that can be shared and reused by the environmental community. Ultimately this will facilitate the integration of genomic and metabolomic datasets, enabling novel studies of the mechanisms underpinning stress responses of organisms within our environment. Here we will focus on the analysis of multi-omics datasets of Daphnia spp., to further investigate the molecular responses to environmental toxicants. Our international team of investigators provides a unique combination of expertise spanning environmental metabolomics (Viant, Davidson), environmental genomics (Colbourne, Zhou) and computational workflows (Li), and are all strongly tied by a common interest and track record in the handling, analyses and interpretation of large-scale 'omics datasets. While Colbourne, Davidson and Viant are based in the School of Biosciences, University of Birmingham, and Li and Zhou reside at BGI in China, all investigators are part of the newly launched Joint BGI-Birmingham Environment and Health Centre at Birmingham that will provide a world-class academic, research and training environment for the integration of state-of-the-art sequencing, metabolomic and bioinformatics technologies.

“基因组和后基因组研究正在改变我们对生物体与环境相互作用的机械理解。"虽然这种说法当然是正确的，但它掩盖了过去十年中必须克服的许多重大挑战。今天，基因组学方法被NERC科学领域的研究人员广泛使用，利用成熟的（而且越来越便宜的）技术和分析管道，并提供高影响力的出版物。代谢组学还不能这么说，它是一种在分析和计算上都相当不成熟的方法。代谢组学中的分析挑战限制了分析化学专家的使用，而计算挑战限制了可以从这些丰富的数据集中挖掘的知识。在这里，我们解决后一点，从基因组学研究人员的智慧和经验。环境基因组学成功的原因之一是，生物学家在没有深入了解生物统计学和编程的情况下，已经能够使用标准化的工作流程构建和执行下一代测序（NGS）数据分析。Galaxy（http：//galaxyproject.org/）-标题为"人人在线生物信息学分析"-已成为NGS数据分析的领先开源工作流程平台，可从其基于网络的用户界面访问许多标准处理工具。该工作流程软件也被成功地应用于蛋白质组学和化学信息学。中国华大基因（北京基因组研究所）的研究人员是我们在该应用程序上的项目合作伙伴，他们在Galaxy方面拥有相当丰富的专业知识，因为这种基于网络的数据分析和工作流程系统构成了其数据分析平台的基础。他们还与Galaxy开发团队有着密切的联系。我们建议将Davidson博士从伯明翰大学Viant教授的环境代谢组学实验室和NBAF-B“跳”到BGI香港的计算实验室。在这里，他将获得Galaxy工作流程方面的专业知识，并将我们现有的代谢组学管道实施到Galaxy中。这是朝着使代谢组学分析管道更有效（通过整合来自不断增长的代谢组学分析方法工具箱的强大算法），更标准化（能够更好地交叉比较不同研究的结果）以及生物学家更容易获得的方向迈出的极其重要的一步。我们的目标是让数据和分析工具都可以从一个软件平台上访问，该平台提供了一个单一的、用户友好的界面，用于以一种可以被环境界共享和重复使用的形式开发计算管道。最终，这将促进基因组学和代谢组学数据集的整合，从而能够对我们环境中生物体的应激反应机制进行新的研究。在这里，我们将重点分析水蚤的多组学数据集，以进一步研究对环境毒物的分子反应。我们的国际研究团队提供独特的专业知识组合，涵盖环境代谢组学（Viant，Davidson），环境基因组学（Colbourne，Zhou）和计算工作流程（Li），并且在处理，分析和解释大规模组学数据集方面都有共同的兴趣和良好的记录。Colbourne、Davidson和Viant都在伯明翰大学生物科学学院工作，Li和Zhou则在中国华大基因工作，所有研究人员都是新成立的伯明翰华大基因-伯明翰联合环境与健康中心的一部分，该中心将为整合最先进的测序、代谢组学和生物信息学技术提供世界一流的学术、研究和培训环境。