An Automated Pipeline to Monitor System Performance in Liquid Chromatography-Tandem Mass Spectrometry Proteomic Experiments
An Automated Pipeline to Monitor System Performance in Liquid Chromatography-Tandem Mass Spectrometry Proteomic Experiments
复制标题
DOI：
10.1021/acs.jproteome.6b00744
复制
发表时间：
2016-12-01
影响因子：
4.4
通讯作者：
MacCoss, Michael J.
中科院分区：
文献类型：
--
作者：
Bereman, Michael S.;Beri, Joshua;MacCoss, Michael J.
我们报告了一个完全自动化的管道，以监测系统的适用性自下而上的蛋白质组学实验的发展。LC-MS/MS运行自动导入Skyline，并从目标肽中提取多个无识别指标。然后将这些数据上传到Panorama Skyline文档库，在该文档库中，可以使用强大的过程控制技术（包括Levey-Jennings和Pareto图）在基于Web的界面中查看指标。该界面是通用的，并采取用户输入，这允许用户显着控制数据的可视化。管道是供应商和仪器类型中立的，支持多种采集技术（例如，MS 1过滤、数据独立采集、并行反应监测和选定反应监测），可以跟踪多台仪器的性能，并且除了初始设置之外不需要手动干预。数据可以从任何一台有互联网接入和网络浏览器的计算机上查看，便于研究人员之间共享QC数据。在此，我们描述了使用这种称为Panorama AutoQC的管道来评估一系列情况下的LC-MS/MS性能，包括识别次优仪器性能、评估超高压色谱以及识别多年来变化的主要来源肽数据收集。
We report the development of a completely automated pipeline to monitor system suitability in bottom-up proteomic experiments. LC-MS/MS runs are automatically imported into Skyline and multiple identification-free metrics are extracted from targeted peptides. These data are then uploaded to the Panorama Skyline document repository where metrics can be viewed in a web based interface using powerful process control techniques, including Levey-Jennings and Pareto plots. The interface is versatile and takes user input, which allows the user significant control over the visualization of the data. The pipeline is vendor and instrument-type neutral, supports multiple acquisition techniques (e.g., MS 1 filtering, data-independent acquisition, parallel reaction monitoring, and selected reaction monitoring), can track performance of multiple instruments, and requires no manual intervention aside from initial setup. Data can be viewed from any computer with Internet access and a web browser, facilitating sharing of QC data between researchers. Herein, we describe the use of this pipeline, termed Panorama AutoQC, to evaluate LC-MS/MS performance in a range of scenarios including identification of suboptimal instrument performance, evaluation of ultrahigh pressure chromatography, and identification of the major sources of variation throughout years of peptide data collection.