TY - JOUR A1 - Dai, Chengxin A1 - Füllgrabe, Anja A1 - Pfeuffer, Julianus A1 - Solovyeva, Elizaveta M. A1 - Deng, Jingwen A1 - Moreno, Pablo A1 - Kamatchinathan, Selvakumar A1 - Kundu, Deepti Jaiswal A1 - George, Nancy A1 - Fexovy, Silvie A1 - Grüning, Björn A1 - Föll, Melanie Christine A1 - Griss, Johannes A1 - Vaudel, Marc A1 - Audain, Enrique A1 - Locard-Paulet, Marie A1 - Turewicz, Michael A1 - Eisenacher, Martin A1 - Uszkoreit, Julian A1 - Van Den Bossche, Tim A1 - Schwämmle, Veit A1 - Webel, Henry A1 - Schulze, Stefan A1 - Bouyssié, David A1 - Jayaram, Savita A1 - Duggineni, Vinay Kumar A1 - Samaras, Patroklos A1 - Wilhelm, Mathias A1 - Choi, Meena A1 - Wang, Mingxun A1 - Kohlbacher, Oliver A1 - Brazma, Alvis A1 - Papatheodorou, Irene A1 - Bandeira, Nuno A1 - Deutsch, Eric W. A1 - Vizcaíno, Juan Antonio A1 - Bai, Mingze A1 - Sachsenberg, Timo A1 - Levitsky, Lev I. A1 - Perez-Riverol, Yasset T1 - A proteomics sample metadata representation for multiomics integration and big data analysis JF - Nature Communications N2 - 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. Y1 - 2021 U6 - https://doi.org/https://doi.org/10.1038/s41467-021-26111-3 VL - 12 IS - 5854 ER -