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

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          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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          Author and article information

          Journal
          Nat. Methods
          Nature methods
          1548-7105
          1548-7091
          Mar 2015
          : 12
          : 3
          Affiliations
          [1 ] 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.
          [2 ] Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
          [3 ] Lunenfeld-Tanenbaum Research Institute, Toronto, Ontario, Canada.
          [4 ] Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
          [5 ] 1] Lunenfeld-Tanenbaum Research Institute, Toronto, Ontario, Canada. [2] Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
          Article
          nmeth.3255 NIHMS677523
          10.1038/nmeth.3255
          25599550
          f19614af-024b-494b-a5c1-7ff112f715c9

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