ABI Development: A unified Galaxy-based platform for multi-omic data analysis and informatics

ABI Development：基于 Galaxy 的统一平台，用于多组学数据分析和信息学

• 批准号: 1458524
• 负责人: Timothy Griffin
• 金额: $ 178.02万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1458524&HistoricalAwards=false
• 关键词: ABI; Development; unified; Galaxy; based

Acquisition of system-wide molecular information on genomes, proteomes and metabolomes (multi-omics data) is now possible for biological researchers. Approaches that jointly analyze and interpret multi-omic data provide new understanding of the molecular interplay between genes, proteins and metabolites. For example, proteogenomics integrates DNA or RNA sequence data with mass spectrometry (MS)-based proteomics data to identify novel protein variants expressed under different conditions; metaproteomics integrates metagenomic data with MS-based proteomic data to identify proteins expressed by microbial communities; metabologenomics integrates genomic and proteomic data with metabolomic profiling data, connecting genotypes to function. To enable new discoveries mined from multi-omic data, the raw data must first be analyzed with specialized, domain specific software. Unfortunately, the requirement to master and integrate different software for large-scale data analysis discourages many researchers who may otherwise use and benefit from multi-omic approaches in their work. The goal of this project is to provide a solution to this problem by developing a unified, web-based analytical hub for multi-omic data accessible to bench scientists. Broader Impact activities will include promotion and dissemination of these software tools to the greater research community and training of undergraduates in bioinformatics via internship projects.This project will leverage the web-based, user-friendly and research enabling Galaxy bioinformatics workbench. In addition to proteogenomics and metaproteomics, novel Galaxy extensions will be built to enable data analysis for metabolomics, a field in desperate need of a unified resource to consolidate its many useful but scattered software tools. Combined with new interactive visualization tools, data exchange features, and deployment in scalable and accessible cloud-based resources, Galaxy's functionality will be significantly enhanced to empower more researchers in multi-omic data analysis. The project has these Specific Aims: 1) Enhance the Galaxy environment with new interactive visualization tools and data exchange functionalities necessary for effective multi-omic data analysis; 2) Extend the Galaxy environment to analyze and process diverse metabolomics data and support workflows for metabolic activity profiling; 3) Extend the Galaxy environment for integrative genomic-proteomic data analysis supporting proteogenomic and metaproteomic applications; 4) Ensure Broader Impact by promoting usage of Galaxy for multi-omics by the research community and providing undergraduate training opportunities in computational systems biology via a local area institutional network. Results from this project can be found at usegalaxyp.org.

生物研究人员现在可以获取有关基因组、蛋白质组和代谢组（多组学数据）的全系统分子信息。 联合分析和解释多组学数据的方法提供了对基因、蛋白质和代谢物之间分子相互作用的新理解。 例如，蛋白质基因组学将 DNA 或 RNA 序列数据与基于质谱 (MS) 的蛋白质组学数据相结合，以识别在不同条件下表达的新蛋白质变体；宏蛋白质组学将宏基因组数据与基于 MS 的蛋白质组数据相结合，以识别微生物群落表达的蛋白质；代谢基因组学将基因组和蛋白质组数据与代谢组分析数据相结合，将基因型与功能联系起来。为了从多组学数据中挖掘出新的发现，必须首先使用专门的、特定领域的软件对原始数据进行分析。 不幸的是，掌握和集成不同软件进行大规模数据分析的要求让许多研究人员望而却步，否则他们可能会在工作中使用多组学方法并从中受益。 该项目的目标是通过开发一个统一的、基于网络的分析中心，为实验室科学家提供可访问的多组学数据，从而为该问题提供解决方案。 更广泛的影响活动将包括向更大的研究界推广和传播这些软件工具，以及通过实习项目对本科生进行生物信息学培训。该项目将利用基于网络、用户友好且支持研究的 Galaxy 生物信息学工作台。 除了蛋白质组学和元蛋白质组学之外，还将构建新颖的 Galaxy 扩展来实现代谢组学的数据分析，该领域迫切需要统一的资源来整合其许多有用但分散的软件工具。 结合新的交互式可视化工具、数据交换功能以及可扩展且可访问的云资源中的部署，Galaxy 的功能将得到显着增强，从而使更多研究人员能够进行多组学数据分析。 该项目有以下具体目标：1）通过有效的多组学数据分析所需的新的交互式可视化工具和数据交换功能来增强 Galaxy 环境； 2) 扩展 Galaxy 环境以分析和处理不同的代谢组学数据并支持代谢活动分析的工作流程； 3) 扩展 Galaxy 环境以进行综合基因组-蛋白质组数据分析，支持蛋白质组和元蛋白质组应用； 4) 通过促进研究界使用 Galaxy 进行多组学，并通过本地机构网络提供计算系统生物学本科生培训机会，确保产生更广泛的影响。 该项目的结果可以在 usegalaxyp.org 上找到。