The number of mass spectrometry (MS)-based proteomics datasets in the public domain keeps increasing, particularly those generated by Data Independent Acquisition (DIA) approaches such as SWATH-MS. Unlike Data Dependent Acquisition datasets, the re-use of DIA datasets has been rather limited to date, despite its high potential, due to the technical challenges involved. We introduce a (re-)analysis pipeline for public SWATH-MS datasets which includes a combination of metadata annotation protocols, automated workflows for MS data analysis, statistical analysis, and the integration of the results into the Expression Atlas resource. Automation is orchestrated with Nextflow, using containerised open analysis software tools, rendering the pipeline readily available and reproducible. To demonstrate its utility, we reanalysed 10 public DIA datasets from the PRIDE database, comprising 1,278 SWATH-MS runs. The robustness of the analysis was evaluated, and the results compared to those obtained in the original publications. The final expression values were integrated into Expression Atlas, making SWATH-MS experiments more widely available and combining them with expression data originating from other proteomics and transcriptomics datasets.
Rising numbers of mass spectrometry proteomics datasets available in the public domain, increasingly include volumes generated from Data Independent Acquisition approaches, SWATH-MS in particular. Unlike Data Dependent Acquisition datasets, their re-use is limited, partially due to challenges in combination and use of free software for analysis in the non-specialist laboratory. We introduce a (re-)analysis pipeline for SWATH-MS data available in the PRIDE database, which includes a harmonised combination of metadata annotation protocols, automated workflows for MS data, statistical analysis and results integration into the resource Expression Atlas. Automation is orchestrated with Nextflow, using containerised open analysis software tools, rendering the pipeline readily available, reproducible and easy to update. To demonstrate its utility, we reanalysed 10 public DIA datasets, 1,278 individual SWATH-MS runs, stored in PRIDE. The robustness of the analysis was evaluated and compared to the results obtained in the original publications. The final results were exported into Expression Atlas, making quantitative results from SWATH-MS experiments more widely available and integrated with results from other reanalysed proteomics and transcriptomics datasets.
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