Inter-laboratory mass spectrometry dataset based on passive sampling of drinking water for non-target analysis.
Inter-laboratory mass spectrometry dataset based on passive sampling of drinking water for non-target analysis.
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DOI：
10.1038/s41597-021-01002-w
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发表时间：
2021-08-24
期刊：
影响因子：
9.8
通讯作者：
Samanipour S
中科院分区：
文献类型：
--
作者：
Schulze B;van Herwerden D;Allan I;Bijlsma L;Etxebarria N;Hansen M;Merel S;Vrana B;Aalizadeh R;Bajema B;Dubocq F;Coppola G;Fildier A;Fialová P;Frøkjær E;Grabic R;Gago-Ferrero P;Gravert T;Hollender J;Huynh N;Jacobs G;Jonkers T;Kaserzon S;Lamoree M;Le Roux J;Mairinger T;Margoum C;Mascolo G;Mebold E;Menger F;Miège C;Meijer J;Moilleron R;Murgolo S;Peruzzo M;Pijnappels M;Reid M;Roscioli C;Soulier C;Valsecchi S;Thomaidis N;Vulliet E;Young R;Samanipour S
采用高分辨率质谱的非目标分析 (NTA) 是检测复杂环境样品中新出现的新型化学物质的常用方法。 NTA 通常会产生大量信息丰富的数据集，需要计算机辅助（理想情况下是自动化）策略来进行处理和解释。然而，此类策略确实提出了不同处理工作流程之间和内部的可重复性的挑战。缓解此类问题的有效策略是实施实验室间研究 (ILS)，旨在评估不同的工作流程并就协调/标准化的质量控制程序达成一致。在这里，我们展示了此类 ILS 期间生成的数据。这项研究是通过诺曼网络组织的，包括来自 11 个国家的 21 名参与者。基于饮用水处理前后被动采样的一组样品被运送到所有参与实验室进行分析，使用一种预先定义的方法和一种本地（即内部）开发的方法。生成的数据是 NTA 实验算法和工作流程未来开发的宝贵资源（即基准）。描述报告数据的机器可访问元数据文件：10.6084/m9.figshare.15028665
Non-target analysis (NTA) employing high-resolution mass spectrometry is a commonly applied approach for the detection of novel chemicals of emerging concern in complex environmental samples. NTA typically results in large and information-rich datasets that require computer aided (ideally automated) strategies for their processing and interpretation. Such strategies do however raise the challenge of reproducibility between and within different processing workflows. An effective strategy to mitigate such problems is the implementation of inter-laboratory studies (ILS) with the aim to evaluate different workflows and agree on harmonized/standardized quality control procedures. Here we present the data generated during such an ILS. This study was organized through the Norman Network and included 21 participants from 11 countries. A set of samples based on the passive sampling of drinking water pre and post treatment was shipped to all the participating laboratories for analysis, using one pre-defined method and one locally (i.e. in-house) developed method. The data generated represents a valuable resource (i.e. benchmark) for future developments of algorithms and workflows for NTA experiments. Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.15028665
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影响因子：
7.4
作者：
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通讯作者：
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影响因子：
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发表时间：
2018-06-15
影响因子：
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作者：
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通讯作者：
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