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.

Details

Title
Implementing the reuse of public DIA proteomics datasets: from the PRIDE database to Expression Atlas
Author
Walzer, Mathias 1   VIAFID ORCID Logo  ; García-Seisdedos, David 1   VIAFID ORCID Logo  ; Prakash, Ananth 1 ; Brack, Paul 2 ; Crowther, Peter 3 ; Graham, Robert L. 4 ; George, Nancy 1 ; Mohammed, Suhaib 1 ; Moreno, Pablo 1   VIAFID ORCID Logo  ; Papatheodorou, Irene 1   VIAFID ORCID Logo  ; Hubbard, Simon J. 2   VIAFID ORCID Logo  ; Vizcaíno, Juan Antonio 1   VIAFID ORCID Logo 

 European Molecular Biology Laboratory, EMBL-European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridge, United Kingdom (GRID:grid.225360.0) (ISNI:0000 0000 9709 7726) 
 University of Manchester, Manchester Academic Health Science Centre, Division of Evolution, Infection and Genomics, School of Biological Sciences, Faculty of Biology, Medicine and Health, Manchester, United Kingdom (GRID:grid.5379.8) (ISNI:0000000121662407) 
 Melandra Limited, Manchester, United Kingdom (GRID:grid.5379.8) 
 Queen’s University Belfast, School of Biological Sciences, Chlorine Gardens, Belfast, United Kingdom (GRID:grid.4777.3) (ISNI:0000 0004 0374 7521) 
Publication year
2022
Publication date
2022
Publisher
Nature Publishing Group
e-ISSN
20524463
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2676404142
Copyright
© The Author(s) 2022. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.