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

明尼苏达大学双子城分校获得一笔赠款，用于开发一个整合质谱学(MS)蛋白质组学研究工具的框架，该框架建立在名为Galaxy的社区驱动的基因组数据分析分析框架的基础上。Galaxy由宾夕法尼亚州立大学开发，专门设计用于使现有应用程序能够供生命科学家使用，同时通过数据捕获、工作流程开发和共享来增强可重复性功能。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这一框架，从而创建用于蛋白质组学的银河工具模块，该模块将被称为银河-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。这种数据的分析和管理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，影响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造成了分析瓶颈。这在基于MS的蛋白质组学领域尤其如此，该领域的一个重大缺陷是难以访问有用的软件并将其组装成集成的工作流程或管道，尤其是缺乏计算专业知识的用户。太多时候，数据分析留给核心蛋白质组实验室或计算专家，项目研究人员的参与有限。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的标准。因此，有效、复杂的数据分析的过程透明度、可重复性和传播性受到影响。由于这些共同的缺陷，基于MS的蛋白质组学数据的信息的完全深度和丰富没有实现，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数据和分析能够集成。此外，该项目将利用明尼苏达超级计算机研究所(MSI)和地区本科学院现有的独特培训资源，开发一个局域网和机制，为年轻科学家提供系统生物学方面的培训机会。

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.