Federal Institute of Hydrology, Koblenz, Germany.
Rapid Commun Mass Spectrom. 2022 Jan 30;36(2):e9206. doi: 10.1002/rcm.9206.
Non-target screening techniques using high-resolution mass spectrometers become more and more important for environmental sciences. Highly reliable and sophisticated software solutions are required to deal with the large amount of data obtained from such analyses.
Processing of high-resolution LC-HRMS data was performed upon conversion into an open, XML-based data format followed by an automated assignment of chromatographic peaks using the open-source programming language R. Raw data from three different LC-HRMS systems were processed as a proof of principle.
We present a simple and straightforward algorithm to extract chromatographic peaks from previously m/z-centroided data based on the open-source programming language R and C++. The working principle and processing parameters are explained in detail. A ready-to-use script is provided in the supporting information.
The developed algorithm enables a comprehensible automated peak picking of non-target LC-MS data. Application to three completely different HRMS raw data files showed reasonable False Positives and False Negatives detection and moderate calculation times.
使用高分辨率质谱仪的非靶向筛选技术在环境科学领域变得越来越重要。需要高度可靠和复杂的软件解决方案来处理从这些分析中获得的大量数据。
将高分辨率 LC-HRMS 数据转换为开放的基于 XML 的数据格式后，使用开源编程语言 R 自动分配色谱峰，从而对其进行处理。作为原理验证，对来自三个不同 LC-HRMS 系统的原始数据进行了处理。
我们提出了一种简单直接的算法，该算法基于开源编程语言 R 和 C++，可从先前的 m/z 质心数据中提取色谱峰。详细解释了工作原理和处理参数。在支持信息中提供了一个可立即使用的脚本。
开发的算法能够实现非靶向 LC-MS 数据的可理解的自动峰提取。将其应用于三个完全不同的 HRMS 原始数据文件，结果表明该方法具有合理的假阳性和假阴性检测以及适中的计算时间。
