A Galaxy‐based multi‐omic informatics hub for cancer researchers

 描述（由申请人提供）：银河生物信息学框架被数千名癌症研究人员使用，主要用于基于基因组学的研究。它的开放和灵活的环境，使不同的生物信息学软件通过用户友好的基于Web的界面进行互操作。尽管其在基因组生物信息学方面的价值已得到证实，但Galaxy在癌症研究方面的潜力尚未完全实现。银河系的一个新兴潜力领域是多组信息学。多组学整合了高通量基因组学、转录组学、蛋白质组学和代谢组学数据，以揭示癌症中的新分子发现。例如，将代谢组学信息与基因组学和/或蛋白质组学数据相结合，揭示了致癌作用背后的基因和蛋白质变异的生物化学后果。将基因组或转录组数据与基于质谱（MS）的蛋白质组学数据（蛋白质基因组学）整合鉴定与基因组突变相关的新蛋白质变体。整合宏基因组数据与基于MS的蛋白质组学数据（元蛋白质组学）识别微生物群落表达的蛋白质，从而深入了解微生物组对致癌作用的生物化学贡献。尽管他们的潜在回报，这些多组学的方法需要使用各种信息学工具的范围之外的大多数板凳研究人员。幸运的是，Galaxy提供了一个解决方案。我们建议扩展Galaxy并为多组学信息学创建一个强大的统一中心。我们将专注于通过独立的多组学可视化平台（MVP）增强Galaxy，以实现结果可视化和解释。我们将建立新的Galaxy扩展，使代谢物分析，结果解释和有针对性的临床验证研究。我们将扩展当前基于Galaxy的工具，为蛋白质组学和元蛋白质组学信息学创建一个完整的解决方案，使易于构建的工作流程确保准确的结果。最后，我们将通过各种传播和培训活动，使癌症研究人员能够在工作中使用Galaxy进行多组学研究。我们将通过以下具体目标实现这些成果：1）扩展与Galaxy兼容的多组学可视化平台（MVP），以利用癌症知识库和信息学资源增强结果解释和数据交换; 2）扩展Galaxy和MVP工具，用于癌症研究中的代谢物分析; 3）扩展Galaxy和MVP工具，用于整合基因组-蛋白质组信息学和工作流程。4)通过传播、推广和培训活动，促进癌症研究人员使用多组学工作流程和相关工具。我们的工作将通过与合作者网络一起推动癌症项目来指导。我们将与不同经济学领域的成熟软件和方法的开发人员合作，并利用明尼苏达超级计算研究所的世界级基础设施。我们的成果将直接补充目前通过NIH ITCR计划资助的其他项目。我们工作的结果将是一个由癌症研究人员组成的大型网络，他们有权利用高影响力的多组学方法，最终催化新的发现，这将有助于减少癌症的痛苦和死亡。

 DESCRIPTION (provided by applicant): The Galaxy bioinformatics framework is used by thousands of cancer researchers, primarily for genomics-based studies. It's open and flexible environment enables interoperation of diverse bioinformatics software via a user-friendly web-based interface. Despite its proven value for genomic bioinformatics, Galaxy's potential for enabling cancer research has not been fully realized. One area of emerging potential for Galaxy is multi- omic informatics. Multi-omics integrates high throughput genomic, transcriptomic, proteomic and metabolomics data to reveal new molecular discoveries in cancer. For example, integrating metabolomics information with genomic and/or proteomic data reveals biochemical consequences of gene and protein variations underlying carcinogenesis. Integration of genomic or transcriptomic data with mass spectrometry (MS)-based proteomic data (proteogenomics) identifies novel protein variants linked to genome mutations. Integration of metagenomic data with MS-based proteomic data (metaproteomics) identifies proteins expressed by microbial communities giving insights into biochemical contributions from the microbiome to carcinogenesis. Despite their potential pay-off, these multi-omic approaches require use of diverse informatics tools out of the reach of most bench researchers. Fortunately, Galaxy offers a solution. We propose to extend Galaxy and create a powerful, unified hub for multi-omic informatics. We will focus on enhancing Galaxy with a stand-alone Multi-omics Visualization Platform (MVP) for results visualization and interpretation. We will build novel Galaxy extensions enabling metabolite profiling, results interpretation and targeted clinical validation studies. We will extend current Galaxy-based tools to create a complete solution for proteogenomic and metaproteomic informatics, making easy-to-build workflows that ensure accurate results. Finally, we will empower cancer researchers to use Galaxy for multi-omics in their work via a variety of dissemination and training activities. We will achieve these outcomes via these Specific Aims: 1) Extend a Galaxy-compatible Multi-omics Visualization Platform (MVP) for enhanced results interpretation and data exchange utilizing cancer knowledge bases and informatics resources; 2) Extend Galaxy and the MVP tool for metabolite profiling in cancer research; 3) Extend Galaxy and the MVP tool for integrative genomic-proteomic informatics and workflows.; 4) Catalyze the use of multi-omic workflows and associated tools by cancer researchers via dissemination, promotion and training activities. Our work will be guided via driving cancer projects with a network of collaborators. We will partner with developers of established software and methods in different 'omic domains, and utilize world-class infrastructure at the Minnesota Supercomputing Institute. Our deliverables will directly complement other projects currently funded through the NIH ITCR program. The upshot of our work will be a large network of cancer researchers empowered to utilize high impact, multi-omic approaches, ultimately catalyzing new discoveries that will help decrease the suffering and death from cancer.