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Untargeted, spectral library‐free analysis of data‐independent acquisition proteomics data generated using Orbitrap mass spectrometers
Author(s) -
Tsou ChihChiang,
Tsai ChiaFeng,
Teo Guo Ci,
Chen YuJu,
Nesvizhskii Alexey I.
Publication year - 2016
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201500526
Subject(s) - orbitrap , mass spectrometry , computer science , tandem mass tag , proteomics , peptide , identification (biology) , data acquisition , quantitative proteomics , chemistry , computational biology , chromatography , biology , biochemistry , botany , gene , operating system
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.