Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software.
Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software.
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DOI：
10.1021/acs.analchem.0c02844
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发表时间：
2020-10-20
影响因子：
7.4
通讯作者：
Free RC
中科院分区：
文献类型：
--
作者：
Wilde MJ;Zhao B;Cordell RL;Ibrahim W;Singapuri A;Greening NJ;Brightling CE;Siddiqui S;Monks PS;Free RC
全二维气相色谱(GC×GC)是一种强大的分析工具，可用于非靶向和靶向分析。然而，需要更集成的工作流来处理和管理由此产生的高复杂性数据集。处理GC×GC数据的端到端工作流具有挑战性，通常需要多个工具或软件来处理单个数据集。我们描述了一种新的方法，它使用商业软件中现有的未得到充分利用的接口来集成自由和开源/外部脚本和工具，在单一软件环境中根据个人研究人员的需求定制工作流程。为了演示这一概念，该界面被成功地用于在大规模GC×GC代谢组学数据集上完成首次比对。分析是通过在商业软件环境中连接定制和发布的外部算法来执行的，以自动校正由常规参考标准捕获的保留时间的变化。1TR值和2TR值的变异分别从对齐前的8%和16%减少到对齐后的1%和2%以下。该界面实现了自动化和创建新功能，并增加了化学计量学工具之间的互连，为将数据处理软件与更大的基于信息学的数据管理平台整合提供了一个窗口。
Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful analytical tool for both nontargeted and targeted analyses. However, there is a need for more integrated workflows for processing and managing the resultant high-complexity datasets. End-to-end workflows for processing GC×GC data are challenging and often require multiple tools or software to process a single dataset. We describe a new approach, which uses an existing underutilized interface within commercial software to integrate free and open-source/external scripts and tools, tailoring the workflow to the needs of the individual researcher within a single software environment. To demonstrate the concept, the interface was successfully used to complete a first-pass alignment on a large-scale GC×GC metabolomics dataset. The analysis was performed by interfacing bespoke and published external algorithms within a commercial software environment to automatically correct the variation in retention times captured by a routine reference standard. Variation in 1tR and 2tR was reduced on average from 8 and 16% CV prealignment to less than 1 and 2% post alignment, respectively. The interface enables automation and creation of new functions and increases the interconnectivity between chemometric tools, providing a window for integrating data-processing software with larger informatics-based data management platforms.
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影响因子：
7.4
作者：
Johnson, Caroline H.;Ivanisevic, Julijana;Benton, H. Paul;Siuzdak, Gary
通讯作者：
Siuzdak, Gary
影响因子：
2.9
作者：
Ibrahim, Wadah;Wilde, Michael;Siddiqui, Salman
通讯作者：
Siddiqui, Salman
影响因子：
6.8
作者：
Orešič M;Hyötyläinen T;Herukka SK;Sysi-Aho M;Mattila I;Seppänan-Laakso T;Julkunen V;Gopalacharyulu PV;Hallikainen M;Koikkalainen J;Kivipelto M;Helisalmi S;Lötjönen J;Soininen H
通讯作者：
Soininen H
影响因子：
7.4
作者：
Pierce, KM;Wood, LF;Synovec, RE
通讯作者：
Synovec, RE
影响因子：
7.4
作者：
Castillo, Sandra;Mattila, Ismo;Hyotylainen, Tuulia
通讯作者：
Hyotylainen, Tuulia