ABI Development: Galaxy-P: A new community-based informatics paradigm for MS-based proteomics

明尼苏达大学双城分校获得一笔赠款，用于开发一个框架，用于整合质谱（MS）蛋白质组学研究的工具，该框架建立在社区驱动的基因组数据分析分析框架基础上，名为Galaxy。 Galaxy由宾夕法尼亚州立大学开发，专门设计用于使生命科学家能够使用现有的应用程序，同时通过数据捕获、工作流程开发和共享来增强再现性功能。 该项目将通过部署和集成一系列用于基于MS的蛋白质组学数据分析的关键软件程序来扩展该框架，从而创建用于蛋白质组学的Galaxy工具模块，即Galaxy-P（http：//getgalaxyp.org/）。对计算和信息学的依赖是使用高通量分析平台在基因组、蛋白质组和代谢组水平上进行全系统分子研究所固有的。 分析和管理这些数据需要信息学解决方案，包括用于采集、处理、分析、注释和传播数据的软件以及所使用的实验程序。 不幸的是，在许多情况下，这些信息学解决方案不能满足研究人员的需求，降低了它们的使用和采用，从而在使用高通量技术的生物研究中产生了分析瓶颈。 这在仍然成熟的基于MS的蛋白质组学领域尤其如此，其中一个显著的缺点是难以访问和组装有用的软件到集成的工作流程或管道中，特别是缺乏计算专业知识的用户。 数据分析往往留给核心蛋白质组学实验室或计算专家，项目研究人员的参与有限。 此外，还缺乏记录和分享实验程序和工作流程的有效手段，以及更系统地采用科学界标准。因此，过程的透明度、可重复性和有效、复杂数据分析的传播受到影响。 由于这些共同的缺点，基于MS的蛋白质组学数据的完整深度和丰富性没有实现，限制了新的发现。Galaxy-P的开发不仅将为明尼苏达州的研究人员提供信息学解决方案，而且还将为广泛的系统生物学研究人员提供一个免费的平台，使基因组和蛋白质组学数据的整合和分析成为可能。此外，该项目将利用明尼苏达超级计算研究所（MSI）和地区本科院校的独特培训资源，为系统生物学的年轻科学家开发一个局域网和培训机会机制。

The University of Minnesota -- Twin Cities is awarded a grant to develop a framework for the integration of tools for mass spectrometry (MS) proteomics research that builds on the community-driven analytical framework for genomic data analysis named Galaxy. Developed at Penn State University, Galaxy is designed specifically to enable existing applications to become usable by life scientists while enhancing reproducibility functions through data capture, workflow development and sharing. This project will extend this framework by deploying and integrating a series of key software programs for MS-based proteomics data analysis, thus creating Galaxy Tool Modules for Proteomics which will be Galaxy-P (http://getgalaxyp.org/). Reliance on computation and informatics is inherent to system-wide molecular studies at the level of the genome, proteome and metabolome using high throughput analytical platforms. Analysis and management of such data requires informatics solutions, including software for capture, processing, analysis, annotation and dissemination of the data and experimental procedures used. Unfortunately, in many cases these informatics solutions do not meet the needs of the researchers, detracting from their use and adoption and thus creating an analytical bottle-neck in biological research using high throughput technologies. This is especially the case in the still maturing field of MS-based proteomics where a significant shortcoming is the difficulty in accessing and assembling useful software into integrated workflows or pipelines, especially by users who lack computational expertise. Too often data analysis is left to the core proteomics lab or expert in computation with limited involvement of the project researcher. Also lacking is an effective means to document and share experimental procedures and workflows and the more systematic adoption of scientific community standards. Consequently, process transparency, repeatability and dissemination of effective, complex data analyses suffer. Due to these collective shortcomings the full depth and richness of information of MS-based proteomics data is not realized, limiting new discoveries.Development of Galaxy-P will not only provide informatics solutions to Minnesota researchers, but also a freely-available platform enabling integration of genomic and proteomic data and analytics for a broad community of systems biology researchers. In addition, the project will leverage unique training resources in place at the Minnesota Supercomputing Institute (MSI) and area undergraduate colleges, developing a local area network and mechanism for training opportunities for young scientists in systems biology.