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Front Pharmacol. 2018 Jun 26;9:681. doi: 10.3389/fphar.2018.00681. eCollection 2018.

Discovery of the Consistently Well-Performed Analysis Chain for SWATH-MS Based Pharmacoproteomic Quantification.

Fu J1, Tang J1,2, Wang Y1, Cui X1,2, Yang Q1,2, Hong J1, Li X1,2, Li S1,2, Chen Y3, Xue W2, Zhu F1,2.

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College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
School of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China.
Bioinformatics and Drug Design Group, Department of Pharmacy, Center for Computational Science and Engineering, National University of Singapore, Singapore, Singapore.


Sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH-MS) has emerged as one of the most popular techniques for label-free proteome quantification in current pharmacoproteomic research. It provides more comprehensive detection and more accurate quantitation of proteins comparing with the traditional techniques. The performance of SWATH-MS is highly susceptible to the selection of processing method. Till now, ≥27 methods (transformation, normalization, and missing-value imputation) are sequentially applied to construct numerous analysis chains for SWATH-MS, but it is still not clear which analysis chain gives the optimal quantification performance. Herein, the performances of 560 analysis chains for quantifying pharmacoproteomic data were comprehensively assessed. Firstly, the most complete set of the publicly available SWATH-MS based pharmacoproteomic data were collected by comprehensive literature review. Secondly, substantial variations among the performances of various analysis chains were observed, and the consistently well-performed analysis chains (CWPACs) across various datasets were for the first time generalized. Finally, the log and power transformations sequentially followed by the total ion current normalization were discovered as one of the best performed analysis chains for the quantification of SWATH-MS based pharmacoproteomic data. In sum, the CWPACs identified here provided important guidance to the quantification of proteomic data and could therefore facilitate the cutting-edge research in any pharmacoproteomic studies requiring SWATH-MS technique.


SWATH-MS; normalization; pharmacoproteomics; processing method; transformation

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