DeepRTAlign: toward accurate retention time alignment for large cohort mass spectrometry data analysis
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ABSTRACT:
ORGANISM(S): Homo Sapiens
SUBMITTER: 
Cheng Chang
PROVIDER: PXD044224 | iProX | Mon Jul 31 00:00:00 BST 2023
REPOSITORIES: iProX
Publications
DeepRTAlign: toward accurate retention time alignment for large cohort mass spectrometry data analysis.
Liu Yi Y Yang Yun Y Chen Wendong W Shen Feng F Xie Linhai L Zhang Yingying Y Zhai Yuanjun Y He Fuchu F He Fuchu F Zhu Yunping Y Chang Cheng C
Nature communications 20231211 1
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 ...[more]
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Project description: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 accuracy. Furthermore, using the MS features aligned by DeepRTAlign, we trained and validated a robust classifier to predict the early recurrence of hepatocellular carcinoma. DeepRTAlign provides an advanced solution to RT alignment in large cohort LC-MS studies, which is currently a major bottleneck in proteomics and metabolomics research.
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