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DIA-Umpire:用于非数据依赖采集蛋白质组学的综合计算框架

DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics.

作者信息

Tsou Chih-Chiang, Avtonomov Dmitry, Larsen Brett, Tucholska Monika, Choi Hyungwon, Gingras Anne-Claude, Nesvizhskii Alexey I

机构信息

1] Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA. [2] Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.

Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.

出版信息

Nat Methods. 2015 Mar;12(3):258-64, 7 p following 264. doi: 10.1038/nmeth.3255. Epub 2015 Jan 19.

Abstract

As a result of recent improvements in mass spectrometry (MS), there is increased interest in data-independent acquisition (DIA) strategies in which all peptides are systematically fragmented using wide mass-isolation windows ('multiplex fragmentation'). DIA-Umpire (http://diaumpire.sourceforge.net/), a comprehensive computational workflow and open-source software for DIA data, detects precursor and fragment chromatographic features and assembles them into pseudo-tandem MS spectra. These spectra can be identified with conventional database-searching and protein-inference tools, allowing sensitive, untargeted analysis of DIA data without the need for a spectral library. Quantification is done with both precursor- and fragment-ion intensities. Furthermore, DIA-Umpire enables targeted extraction of quantitative information based on peptides initially identified in only a subset of the samples, resulting in more consistent quantification across multiple samples. We demonstrated the performance of the method with control samples of varying complexity and publicly available glycoproteomics and affinity purification-MS data.

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