在简单的数据库中存储质谱数据可以实现灵活和直观的探索,而无需时间或空间限制
William Kumler1, Sam LaRue2, Anitra E Ingalls1
1School of Oceanography, University of Washington, 1501 NE Boat St, Seattle, Washington 98195, United States.
Journal of proteome research
|November 24, 2025
概括
在结构化查询语言 (SQL) 数据库中存储原始质谱 (MS) 数据提供了快速,简单的查询. 这种方法保持了复杂的MS数据集的计算性能和磁盘空间效率.
科学领域:
- 分析化学 分析化学
- 生物信息学是一种生物信息学.
- 数据科学数据科学数据科学
背景情况:
- 质谱 (MS) 产生了庞大的数据集,需要专门的格式和专业知识来提取数据.
- 现有的MS数据格式可能很复杂,阻碍了快速和可访问的信息检索.
- 在MS研究中,对高效的数据管理解决方案的需求正在增长.
研究的目的:
- 评估结构化查询语言 (SQL) 数据库是否可以有效地存储原始MS数据.
- 与传统格式相比,评估SQL数据库用于查询MS数据的性能.
- 为增强的探索性分析开发一个直观的MS数据方案.
主要方法:
- 设计了一个基本的MS模式,具有直观的数据库表和字段.
- 查询了原始MS数据子集 (单个扫描,离子染色图,保留时间范围,碎片搜索).
- 使用SQLite,DuckDB和Parquet的实现与阅读时间和磁盘空间进行了比较.
主要成果:
- 拟议的SQL数据库方案允许对原始MS数据进行易于阅读的查询.
- 常见数据子集的查询性能被发现在1秒以下,即使是千兆字节大小的文件.
- 与其他流行的MS格式相比,SQL数据库方法显示出具有竞争力或优异的性能.
结论:
- 一个整齐的SQL数据模式可以有效地存储和查询各种MS数据类型.
- 这种方法可以提供透明的数据访问,而不会对计算性能或磁盘空间造成重大损害.
- 该方案提供了一个可行的替代方案,用于对大型MS数据集进行高效和交互式分析.
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