Bittremieux Wout, Willems Hanny, Kelchtermans Pieter, Martens Lennart, Laukens Kris, Valkenborg Dirk
†Department of Mathematics and Computer Science, University of Antwerp, Middelheimlaan 1, 2020 Antwerp, Belgium.
‡Biomedical Informatics Research Center Antwerp (biomina), University of Antwerp/Antwerp University Hospital, Wilrijkstraat 10, 2650 Edegem, Belgium.
J Proteome Res. 2015 May 1;14(5):2360-6. doi: 10.1021/acs.jproteome.5b00127. Epub 2015 Apr 2.
Over the past few years, awareness has risen that for mass-spectrometry-based proteomics methods to mature into everyday analytical and clinical practices, extensive quality assessment is mandatory. A currently overlooked source of qualitative information originates from the mass spectrometer itself. Apart from the actual mass spectral data, raw-data objects also contain parameter settings and sensory information about the mass instrument. This information gives a detailed account of the operation of the instrument, which eventually can be related to observations in mass spectral data. The advantage of instrument information at the lowest level is the high sensitivity to detect emerging defects in a timely fashion. To this end, we introduce the Instrument MONitoring DataBase (iMonDB), which allows us to automatically extract, store, and manage the instrument parameters from raw-data objects into a highly efficient database structure. This enables us to monitor the instrument parameters over a considerable time period. Time course information about the instrument performance is necessary to define the normal range of operation and to detect anomalies that may correlate with instrument failure. The proposed tools foster an additional handle on quality control and are released as open source under the permissive Apache 2.0 license. The tools can be downloaded from https://bitbucket.org/proteinspector/imondb.
在过去几年中，人们越来越意识到，要使基于质谱的蛋白质组学方法发展成为日常分析和临床实践，必须进行广泛的质量评估。目前一个被忽视的定性信息来源来自质谱仪本身。除了实际的质谱数据外，原始数据对象还包含有关质谱仪器的参数设置和传感信息。这些信息详细说明了仪器的运行情况，最终可与质谱数据中的观测结果相关联。最低级别仪器信息的优势在于能够及时检测出出现的缺陷，具有高灵敏度。为此，我们引入了仪器监测数据库（iMonDB），它使我们能够自动从原始数据对象中提取仪器参数，存储并将其管理到一个高效的数据库结构中。这使我们能够在相当长的一段时间内监测仪器参数。有关仪器性能的时间进程信息对于定义正常操作范围和检测可能与仪器故障相关的异常情况是必要的。所提出的工具为质量控制提供了额外的手段，并在宽松的Apache 2.0许可下作为开源软件发布。这些工具可从https://bitbucket.org/proteinspector/imondb下载。
