A hybrid retention time alignment algorithm for SWATH-MS data

Abstract

Recently, data-independent acquisition (DIA) MS has gained popularity as a qualitative-quantitative workflow for proteomics. One outstanding problem in the analysis of DIA-MS data is alignment of chromatographic retention times across multiple samples, which facilitates peptide identification and accurate quantification. Here, we present a novel hybrid (profile-based and feature-based) algorithm for LC-MS alignment and test it on sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH) (a type of DIA) data. Our algorithm uses a profile-based dynamic time warping algorithm to obtain a coarse alignment and corrects large retention time shifts, and then uses a feature-based bipartite matching algorithm to match feature to feature at a fine scale. We evaluated our method by comparing our aligned feature pairs to peptide identification results of pseudo-MS2 spectra exported by DIA-Umpire, a recently reported tool for deconvoluting DIA-MS data. We proposed that our method can be used to align DIA-MS data prior to identification, and the alignment can be used to delete noise peaks or screen for differentially changed features. We found that a simple alignment-enabled denoising scheme can reduce the number of pseudo-MS2 spectra exported by DIA-Umpire by up to around 40%, while retaining a comparable number of identifications. Finally, we demonstrated the utility of our tool for accurate label-free relative quantification across multiple SWATH runs.

Keywords: Bioinformatics; Data-independent acquisition; Retention time alignment.