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

ABSTRACT: Initial discovery-based analysis using data independent acquisition (DIA) can obtain deep proteome coverage with high data completeness; however, the development of targeted PRM assays based on subsequent bioinformatic predictions can be tedious and time-consuming because of the complexity of the output. We address this limitation with a Python script that rapidly generates a PRM method for the TIMS-QTOF platform using DIA data and a user-defined target list.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Stanley Stevens  

LAB HEAD: Stanley M. Stevens, Ph.D.

PROVIDER: PXD049405 | Pride | 2024-09-06

REPOSITORIES: Pride