Fast, axis-agnostic, dynamically summarized storage and retrieval for mass spectrometry data

Mass spectrometry, a popular technique for elucidating the molecular contents of experimental samples, creates data sets comprised of millions of three-dimensional (m/z, retention time, intensity) data points that correspond to the types and quantities of analyzed molecules. Open and commercial MS data formats are arranged by retention time, creating latency when accessing data across multiple m/z. Existing MS storage and retrieval methods have been developed to overcome the limitations of retention time-based data formats, but do not provide certain features such as dynamic summarization and storage and retrieval of point meta-data (such as signal cluster membership), precluding efficient viewing applications and certain data-processing approaches. This manuscript describes MzTree, a spatial database designed to provide real-time storage and retrieval of dynamically summarized standard and augmented MS data with fast performance in both m/z and RT directions. Performance is reported on real data with comparisons against related published retrieval systems.

质谱法（Mass spectrometry）作为解析实验样品分子组成的主流技术，可生成包含数百万个三维数据点的数据集；这些数据点以质荷比（m/z）、保留时间（retention time）与信号强度（intensity）为维度，对应被分析分子的种类与含量。开源与商用质谱（MS）数据格式均按保留时间进行组织，在跨多个质荷比调取数据时会产生访问延迟。现有质谱存储与检索方法虽已针对基于保留时间的数据格式的局限性进行了优化，但未能提供动态摘要、数据点元数据（如信号簇归属）的存储与检索等功能，从而无法支持高效可视化应用与部分数据处理方案。本文介绍了MzTree——一种专为实现动态摘要后的标准与增强型质谱数据的实时存储与检索而设计的空间数据库，其在质荷比与保留时间（RT）两个维度上均具备快速检索性能。本文基于真实实验数据，对该数据库的性能进行了测试，并与已发表的同类检索系统开展了对比验证。