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

获取全系统的基因组、蛋白质组和代谢组的分子信息（多组学数据）现在对生物学研究人员来说是可能的。联合分析和解释多组学数据的方法为基因、蛋白质和代谢物之间的分子相互作用提供了新的认识。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，以鉴定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的蛋白质组学数据相结合，以鉴定微生物群落表达的蛋白质；代谢基因组学将基因组学和蛋白质组学数据与代谢组学分析数据相结合，将基因型与功能联系起来。为了从多组数据中挖掘出新的发现，原始数据必须首先用专门的、特定于领域的软件进行分析。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使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、基于网络的多组学数据分析中心，为实验科学家提供一个解决方案。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，并通过实习项目培训生物信息学方面的本科生。该项目将利用基于网络的、用户友好的、研究支持的银河生物信息学工作平台。除了蛋白质基因组学和宏蛋白质组学之外，新的Galaxy扩展将用于代谢组学的数据分析，这是一个迫切需要统一资源来整合其许多有用但分散的软件工具的领域。结合新的交互式可视化工具、数据交换功能，以及可扩展和可访问的云资源部署，Galaxy的功能将大大增强，使更多的研究人员能够进行多基因组数据分析。该项目有以下具体目标：1)通过新的交互式可视化工具和数据交换功能增强银河系环境，这是有效的多基因组数据分析所必需的；2)扩展Galaxy环境，分析和处理各种代谢组学数据，支持代谢活动分析的工作流程；3)扩展银河环境，用于整合基因组-蛋白质组学数据分析，支持蛋白质组学和元蛋白质组学应用；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，确保更广泛的影响。这个项目的结果可以在usegalaxyp.org上找到。

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.