Global proteomics mass spectrometry data sharing infrastructure

全球蛋白质组学质谱学数据共享基础设施-项目摘要 技术的发展和质谱学(MS)中数据生成速度的加快现在使 对人类蛋白质组的系统探测，从而有助于生物分子机制的表征 对疾病的治疗反应的发展所需要的。认识到开放的科学必要性 为了使新的发现成为可能并建立已发表结果的可靠性，蛋白质组学社区 将数据共享作为一种常见做法。数千篇论文的作者已经公开重新发布了 使用我们计划支持和扩展的资源租用底层MS数据：海量Repos- 全球ProteomeXchange Consor的质谱学数据和ProteomeCentral数据门户- 微软数据存储库联盟。在这个项目中，我们建议开发新的蛋白质组学MS数据基础设施， 标准、工作流程和数据索引，以显著促进公平(可查找、可访问、可互操作和 可重复使用)访问蛋白质组学MS数据集。首先，我们将制定新的社区代表标准 中检测到的蛋白质组学鉴定和丰度的详细描述 可用的数据集，包括多肽、蛋白质、异构体和翻译后修饰。我们还将- 倾向于数据集提交、处理和索引的工作流，以支持按每个数据集的 检测到蛋白质组学鉴定。第二，我们将为研究人员创建新的基础设施，以共享受控 访问可能存在重大数据风险的人类受试者研究的蛋白质组学数据集 可辨认的。第三，我们将扩展ProteomeCentral数据门户以支持新的数据集结构， 元数据和索引，可在全球范围内集成所有Proteo- Mexchange存储库。

Global proteomics mass spectrometry data sharing infrastructure - Project Summary Technological developments and the increased pace of data generation in mass spectrometry (MS) now enable systematic probing of the human proteome, thus contributing to the characterization of biomolecular mechanisms required for the development of therapeutic responses to disease. Recognizing the scientific necessity of open data to enable new discoveries and to establish the reliability of published results, the proteomics community embraced data sharing as a common practice. The authors of thousands of papers have already publicly re- leased the underlying MS data using the resources that we propose to support and extend: the MassIVE repos- itory of mass spectrometry data and the ProteomeCentral data portal for the global ProteomeXchange consor- tium of MS data repositories. In this project, we propose to develop new proteomics MS data infrastructure, standards, workflows and data indexes to substantially advance FAIR (Findable, Accessible, Interoperable and Reusable) access to proteomics MS datasets. First, we will develop new community standards for representation of dataset metadata and for the detailed description of proteomics identifications and abundances detected in available datasets, including peptides, proteins, isoforms and post-translational modifications. We will also ex- tend workflows for dataset submission, processing and indexing to enable advanced queries by each dataset’s detected proteomics identifications. Second, we will create new infrastructure for researchers to share controlled access proteomics datasets from studies of human subjects where there may exist a significant risk of the data being identifiable. Third, we will extend the ProteomeCentral data portal to support the new dataset structures, metadata and indexes allowing for the global integration of the new levels of information across all Proteo- meXchange repositories.