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Generalized precursor prediction boosts identification rates and accuracy in mass spectrometry based proteomics

Scott, Aaron M LU ; Karlsson, Christofer LU ; Mohanty, Tirthankar LU ; Hartman, Erik LU ; Vaara, Suvi T ; Linder, Adam LU ; Malmström, Johan LU orcid and Malmström, Lars LU (2023) In Communications Biology 6. p.1-13
Abstract

Data independent acquisition mass spectrometry (DIA-MS) has recently emerged as an important method for the identification of blood-based biomarkers. However, the large search space required to identify novel biomarkers from the plasma proteome can introduce a high rate of false positives that compromise the accuracy of false discovery rates (FDR) using existing validation methods. We developed a generalized precursor scoring (GPS) method trained on 2.75 million precursors that can confidently control FDR while increasing the number of identified proteins in DIA-MS independent of the search space. We demonstrate how GPS can generalize to new data, increase protein identification rates, and increase the overall quantitative accuracy.... (More)

Data independent acquisition mass spectrometry (DIA-MS) has recently emerged as an important method for the identification of blood-based biomarkers. However, the large search space required to identify novel biomarkers from the plasma proteome can introduce a high rate of false positives that compromise the accuracy of false discovery rates (FDR) using existing validation methods. We developed a generalized precursor scoring (GPS) method trained on 2.75 million precursors that can confidently control FDR while increasing the number of identified proteins in DIA-MS independent of the search space. We demonstrate how GPS can generalize to new data, increase protein identification rates, and increase the overall quantitative accuracy. Finally, we apply GPS to the identification of blood-based biomarkers and identify a panel of proteins that are highly accurate in discriminating between subphenotypes of septic acute kidney injury from undepleted plasma to showcase the utility of GPS in discovery DIA-MS proteomics.

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author
; ; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Communications Biology
volume
6
article number
628
pages
1 - 13
publisher
Nature Publishing Group
external identifiers
  • scopus:85161708244
  • pmid:37301900
ISSN
2399-3642
DOI
10.1038/s42003-023-04977-x
language
English
LU publication?
yes
additional info
© 2023. The Author(s).
id
db13119f-0fc0-4fcd-9961-91629935bb4a
date added to LUP
2023-06-12 12:08:49
date last changed
2025-01-13 01:06:16
@article{db13119f-0fc0-4fcd-9961-91629935bb4a,
  abstract     = {{<p>Data independent acquisition mass spectrometry (DIA-MS) has recently emerged as an important method for the identification of blood-based biomarkers. However, the large search space required to identify novel biomarkers from the plasma proteome can introduce a high rate of false positives that compromise the accuracy of false discovery rates (FDR) using existing validation methods. We developed a generalized precursor scoring (GPS) method trained on 2.75 million precursors that can confidently control FDR while increasing the number of identified proteins in DIA-MS independent of the search space. We demonstrate how GPS can generalize to new data, increase protein identification rates, and increase the overall quantitative accuracy. Finally, we apply GPS to the identification of blood-based biomarkers and identify a panel of proteins that are highly accurate in discriminating between subphenotypes of septic acute kidney injury from undepleted plasma to showcase the utility of GPS in discovery DIA-MS proteomics.</p>}},
  author       = {{Scott, Aaron M and Karlsson, Christofer and Mohanty, Tirthankar and Hartman, Erik and Vaara, Suvi T and Linder, Adam and Malmström, Johan and Malmström, Lars}},
  issn         = {{2399-3642}},
  language     = {{eng}},
  month        = {{06}},
  pages        = {{1--13}},
  publisher    = {{Nature Publishing Group}},
  series       = {{Communications Biology}},
  title        = {{Generalized precursor prediction boosts identification rates and accuracy in mass spectrometry based proteomics}},
  url          = {{http://dx.doi.org/10.1038/s42003-023-04977-x}},
  doi          = {{10.1038/s42003-023-04977-x}},
  volume       = {{6}},
  year         = {{2023}},
}