Development of Trans Proteomic Pipeline, an Analysis Suite for Mass Spectrometry

项目摘要 基于质谱学的蛋白质组学是鉴定、定量和鉴定蛋白质组学的关键技术。 生物学各个方面的蛋白质及其翻译后修饰的比较。MS数据集 随着仪器设备的进步而变得越来越大，实验的档案也是如此 可供重新分析和比较的数据。为了满足蛋白质组学领域的需求 为了应对大数据，我们一直在开发我们的端到端数据处理和分析工具套件， 被称为跨蛋白质组管道(TPP)。该项目将把广泛使用的TPP软件套件提升到 对其用户社区变得更加有用，使他们能够以更少的成本更快地执行分析 人力努力，以及添加目前不可能或仅处于测试阶段的功能。我们将添加 全面的端到端TPP支持数据独立采集(DIA)工作流，如SWATH-MS和 蛋白质组学工作流程，如rna-seq辅助蛋白质组学。TPP已经部分支持 这些工作流，但需要对高容量云计算进行额外的整理、强化和扩展 让我们的平台对我们所有的用户真正有用。随着蛋白质丰度的量化变得更加 为了进行更多的实验，我们还将增强现有的同位素和等压标记数据工具 作为无标签数据，并构建一个新的分析工作台，使我们的用户能够访问高级统计数据 已经存在但许多用户难以处理的分析和比较例程。除了……之外 捆绑这个统计软件，我们将建立一个框架，允许用户获取他们的量化结果 从任何传统工作流或新工作流，将其转换为统计数据 包需要，然后可视化并交互地探索统计分析的输出，因此趋势可以 在原始数据中发现并验证离群值。 将对TPP套件进行大量较小的增强，以使工具更智能，从而 通过各种工具免除了用户的配料设置参数和数据采集。我们会 为现有工具开发新的操作模式，使其能够应对用户提出的挑战 根据我们从他们那里得到的反馈。我们会继续进行多项外展工作，包括 每年教授几次软件课程，在科学会议上主办研讨会和摊位，以 与我们的用户见面并获得反馈，并开发更多公开可用的教程和食谱 用于在各种情况下使用工具和应用程序。我们当然会继续向市民发放 跨太平洋伙伴关系的进展，包括文献中的文章和科学会议上的陈述。在……里面 总结，这个提议的计划将继续推进TPP作为卓越的免费和开源的 适用于蛋白质组学中常规和大数据应用的端到端软件分析工具套件。

Project Summary Mass spectrometry (MS) based proteomics is a key technology for the identification, quantification and comparison of proteins and their post-translational modifications across all aspects of biology. MS datasets have been growing ever larger with the advancement of instrumentation, as has the archive of experimental data available for re-analysis and comparison. In order to meet the needs of the proteomics community for coping with big data, we have been developing our end-to-end suite of data processing and analysis tools, called the Trans-Proteomic Pipeline (TPP). This project will advance the widely used TPP software suite to become even more useful to its user community, enabling them to perform their analyses even faster with less human effort, and adding capabilities that are currently not possible or are only in testing stages. We will add full end-to-end TPP support for the data independent acquisition (DIA) workflows, such as SWATH-MS, and proteogenomics workflows, such as RNA-seq assisted proteomics. The TPP already has partial support for these workflows, but needs additional finishing, hardening, and extension to high capacity cloud computing platforms to become truly useful to all our users. As protein abundance quantification becomes even more essential to more experiments, we will enhance our existing tools for isotopic and isobaric labeled data as well as label-free data, and build a new analysis workbench that will give our users access to advanced statistical analysis and comparison routines that already exist but are difficult for many users to handle. In addition to bundling this statistical software, we will build a framework that allows users to take their quantitative results from any of the traditional workflows or new workflows, transform them into the formats that the statistical packages require, and then visualize and interactively explore the outputs of statistical analysis, so trends can be uncovered and outliers verified in the original data. A substantial number of smaller enhancements to the TPP suite will be made to make the tools smarter so that users are relieved of the burden setting parameters and shepherding data through various tools. We will develop new modes of operation for existing tools to be able to handle challenges presented by our users based on the feedback we receive from them. We will continue our many outreach efforts, which include teaching software courses several times per year, hosting workshops and booths at scientific conferences to meet with and gain feedback from our users, and develop many more publicly available tutorials and recipes for using the tools and applications to various circumstances. We will of course continue to disseminate the advancements of the TPP with articles in the literature and with presentations at scientific conferences. In summary, this proposed program will continue to advance the TPP as the preeminent free and open-source end-to-end software analysis tool suite for routine and big data applications in proteomics.