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Updated: Mar 20, 2026

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
Published on: August 19, 2025
Untargeted, spectral library-free analysis of data-independent acquisition proteomics data generated using Orbitrap
Chih-Chiang Tsou1, Chia-Feng Tsai2, Guo Ci Teo3
1Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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.
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