Scientific Data (Jun 2022)

Implementing the reuse of public DIA proteomics datasets: from the PRIDE database to Expression Atlas

  • Mathias Walzer,
  • David García-Seisdedos,
  • Ananth Prakash,
  • Paul Brack,
  • Peter Crowther,
  • Robert L. Graham,
  • Nancy George,
  • Suhaib Mohammed,
  • Pablo Moreno,
  • Irene Papatheodorou,
  • Simon J. Hubbard,
  • Juan Antonio Vizcaíno

DOI
https://doi.org/10.1038/s41597-022-01380-9
Journal volume & issue
Vol. 9, no. 1
pp. 1 – 15

Abstract

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Abstract 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.