title: Untargeted, spectral library-free analysis of data-independent acquisition proteomics data generated using Orbitrap mass spectrometers.
abstract: We describe an improved version of the data-independent acquisition (DIA) computational analysis tool DIA-Umpire, and show that it enables highly sensitive, untargeted, and direct (spectral library-free) analysis of DIA data obtained using the Orbitrap family of mass spectrometers. DIA-Umpire v2 implements an improved feature detection algorithm with two additional filters based on the isotope pattern and fractional peptide mass analysis. The targeted re-extraction step of DIA-Umpire is updated with an improved scoring function and a more robust, semiparametric mixture modeling of the resulting scores for computing posterior probabilities of correct peptide identification in a targeted setting. Using two publicly available Q Exactive DIA datasets generated using HEK-293 cells and human liver microtissues, we demonstrate that DIA-Umpire can identify similar number of peptide ions, but with better identification reproducibility between replicates and samples, as with conventional data-dependent acquisition. We further demonstrate the utility of DIA-Umpire using a series of Orbitrap Fusion DIA experiments with HeLa cell lysates profiled using conventional data-dependent acquisition and using DIA with different isolation window widths.
authors.affiliation: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
authors.forename: Chih-Chiang
authors.initials: CC
authors.lastname: Tsou
authors.affiliation: Institute of Chemistry, Academia Sinica, Taipei, Taiwan.
authors.forename: Chia-Feng
authors.initials: CF
authors.lastname: Tsai
authors.affiliation: Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
authors.forename: Guo Ci
authors.initials: GC
authors.lastname: Teo
authors.affiliation: Institute of Chemistry, Academia Sinica, Taipei, Taiwan.
authors.forename: Yu-Ju
authors.initials: YJ
authors.lastname: Chen
authors.affiliation: Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.|Department of Pathology, University of Michigan, Ann Arbor, MI, USA.
authors.forename: Alexey I
authors.initials: AI
authors.lastname: Nesvizhskii
mesh_terms: D019295:Computational Biology / Q000379:methods*; D057809:HEK293 Cells; D006367:HeLa Cells; D006801:Humans; D013058:Mass Spectrometry / Q000379:methods*; D040901:Proteomics / Q000379:methods*
keywords: Bioinformatics; Data-independent acquisition