title: DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics.
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.
authors.affiliation: 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.
authors.forename: Chih-Chiang
authors.initials: CC
authors.lastname: Tsou
authors.affiliation: Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
authors.forename: Dmitry
authors.initials: D
authors.lastname: Avtonomov
authors.affiliation: Lunenfeld-Tanenbaum Research Institute, Toronto, Ontario, Canada.
authors.forename: Brett
authors.initials: B
authors.lastname: Larsen
authors.affiliation: Lunenfeld-Tanenbaum Research Institute, Toronto, Ontario, Canada.
authors.forename: Monika
authors.initials: M
authors.lastname: Tucholska
authors.affiliation: Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore.
authors.forename: Hyungwon
authors.identifier: 0000000266873088
authors.initials: H
authors.lastname: Choi
authors.affiliation: 1] Lunenfeld-Tanenbaum Research Institute, Toronto, Ontario, Canada. [2] Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
authors.forename: Anne-Claude
authors.initials: AC
authors.lastname: Gingras
authors.affiliation: 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.
authors.forename: Alexey I
authors.initials: AI
authors.lastname: Nesvizhskii
mesh_terms: D000465:Algorithms; D030562:Databases, Protein; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods*; D055432:Metabolomics / Q000379:methods*; D010446:Peptide Fragments / Q000032:analysis; D011506:Proteins / Q000032:analysis; D040901:Proteomics / Q000379:methods*; D012984:Software; D057188:Workflow
chemical_list: D010446:Peptide Fragments; D011506:Proteins