A semi-automated workflow for DIA-based global discovery to pathway-driven PRM analysis.

ABSTRACT: Targeted proteomics, which includes parallel reaction monitoring (PRM), is typically utilized for more precise detection and quantitation of key proteins and/or pathways derived from complex discovery proteomics datasets. Initial discovery-based analysis using data independent acquisition (DIA) can obtain deep proteome coverage with low data missingness while targeted PRM assays can provide additional benefits in further eliminating missing data and optimizing measurement precision. However, PRM method development from bioinformatic predictions can be tedious and time-consuming because of the DIA output complexity. We address this limitation with a Python script that rapidly generates a PRM method for the TIMS-TOF platform using DIA data and a user-defined target list. To evaluate the scri

SUBMITTER: Guergues J 

PROVIDER: S-EPMC11798701 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature