A proteomics sample metadata representation for multiomics integration and big data analysis

Chengxin Dai, Anja Füllgrabe, Julianus Pfeuffer, Elizaveta M. Solovyeva, Jingwen Deng, Pablo Moreno, Selvakumar Kamatchinathan, Deepti Jaiswal Kundu, Nancy George, Silvie Fexova, Björn Grüning, Melanie Christine Föll, Johannes Griss, Marc Vaudel, Enrique Audain, Marie Locard-Paulet, Michael Turewicz, Martin Eisenacher, Julian Uszkoreit, Tim Van Den BosscheVeit Schwämmle, Henry Webel, Stefan Schulze, David Bouyssié, Savita Jayaram, Vinay Kumar Duggineni, Patroklos Samaras, Mathias Wilhelm, Meena Choi, Mingxun Wang, Oliver Kohlbacher, Alvis Brazma, Irene Papatheodorou, Nuno Bandeira, Eric W. Deutsch, Juan Antonio Vizcaíno, Mingze Bai*, Timo Sachsenberg*, Lev I. Levitsky*, Yasset Perez-Riverol*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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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.

Original languageEnglish
Article number5854
JournalNature Communications
Issue number1
Number of pages8
Publication statusPublished - Dec 2021

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© 2021, The Author(s).


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