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

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. Finally, we apply GPS to the identification of blood-base

SUBMITTER: Scott AM 

PROVIDER: S-EPMC10257694 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature