A proteomics sample metadata representation for multiomics integration and big data analysis
Dai, Chengxin; Füllgrabe, Anja; Pfeuffer, Julianus; Solovyeva, Elizaveta M.; Deng, Jingwen; Moreno, Pablo; Kamatchinathan, Selvakumar; Kundu, Deepti Jaiswal; George, Nancy; Fexova, Silvie; Grüning, Björn A.; Föll, Melanie Christine; Griss, Johannes; Vaudel, Marc; Audain, Enrique; Locard-Paulet, Marie; Turewicz, Michael; Eisenacher, Martin; Uszkoreit, Julian; Van Den Bossche, Tim; Schwämmle, Veit; Webel, Henry; Schulze, Stefan; Bouyssié, David; Jayaram, Savita; Duggineni, Vinay Kumar; Samaras, Patroklos; Wilhelm, Mathias; Choi, Meena; Wang, Mingxun; Kohlbacher, Oliver; Brazma, Alvis; Papatheodorou, Irene; Bandeira, Nuno; Deutsch, Eric W.; Vizcaíno, Juan Antonio; Bai, Mingze; Sachsenberg, Timo; Levitsky, Lev I.; Perez-Riverol, Yasset
Journal article, Peer reviewed
Published version
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Date
2021Metadata
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- Department of Clinical Science [2478]
- Registrations from Cristin [11068]
Abstract
The amount of public proteomics data is rapidly increasing but there is no standardized format to describe the sample metadata and their relationship with the dataset files in a way that fully supports their understanding or reanalysis. Here we propose to develop the transcriptomics data format MAGE-TAB into a standard representation for proteomics sample metadata. We implement MAGE-TAB-Proteomics in a crowdsourcing project to manually curate over 200 public datasets. We also describe tools and libraries to validate and submit sample metadata-related information to the PRIDE repository. We expect that these developments will improve the reproducibility and facilitate the reanalysis and integration of public proteomics datasets.