DeepRTAlign: toward accurate retention time alignment for large cohort mass spectrometry data analysis.

ABSTRACT: Retention time (RT) alignment is a crucial step in liquid chromatography-mass spectrometry (LC-MS)-based proteomic and metabolomic experiments, especially for large cohort studies. The most popular alignment tools are based on warping function method and direct matching method. However, existing tools can hardly handle monotonic and non-monotonic RT shifts simultaneously. Here, we develop a deep learning-based RT alignment tool, DeepRTAlign, for large cohort LC-MS data analysis. DeepRTAlign has been demonstrated to have improved performances by benchmarking it against current state-of-the-art approaches on multiple real-world and simulated proteomic and metabolomic datasets. The results also show that DeepRTAlign can improve identification sensitivity without compromising quantitative accu

SUBMITTER: Liu Y 

PROVIDER: S-EPMC10713976 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature