Home > Publications Database > Privacy-preserving multicenter differential protein abundance analysis with FedProt. > print |
001 | 280783 | ||
005 | 20250907001857.0 | ||
024 | 7 | _ | |a 10.1038/s43588-025-00832-7 |2 doi |
024 | 7 | _ | |a pmid:40646319 |2 pmid |
024 | 7 | _ | |a pmc:PMC12374843 |2 pmc |
024 | 7 | _ | |a altmetric:165597112 |2 altmetric |
037 | _ | _ | |a DZNE-2025-00967 |
041 | _ | _ | |a English |
082 | _ | _ | |a 004 |
100 | 1 | _ | |a Burankova, Yuliya |0 0009-0001-4570-1068 |b 0 |
245 | _ | _ | |a Privacy-preserving multicenter differential protein abundance analysis with FedProt. |
260 | _ | _ | |a London |c 2025 |b Nature Research |
336 | 7 | _ | |a article |2 DRIVER |
336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1756205926_31524 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a ARTICLE |2 BibTeX |
336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
520 | _ | _ | |a Quantitative mass spectrometry has revolutionized proteomics by enabling simultaneous quantification of thousands of proteins. Pooling patient-derived data from multiple institutions enhances statistical power but raises serious privacy concerns. Here we introduce FedProt, the first privacy-preserving tool for collaborative differential protein abundance analysis of distributed data, which utilizes federated learning and additive secret sharing. In the absence of a multicenter patient-derived dataset for evaluation, we created two: one at five centers from E. coli experiments and one at three centers from human serum. Evaluations using these datasets confirm that FedProt achieves accuracy equivalent to the DEqMS method applied to pooled data, with completely negligible absolute differences no greater than 4 × 10-12. By contrast, -log10P computed by the most accurate meta-analysis methods diverged from the centralized analysis results by up to 25-26. |
536 | _ | _ | |a 352 - Disease Mechanisms (POF4-352) |0 G:(DE-HGF)POF4-352 |c POF4-352 |f POF IV |x 0 |
588 | _ | _ | |a Dataset connected to CrossRef, PubMed, , Journals: pub.dzne.de |
650 | _ | 2 | |a Humans |2 MeSH |
650 | _ | 2 | |a Proteomics: methods |2 MeSH |
650 | _ | 2 | |a Mass Spectrometry |2 MeSH |
650 | _ | 2 | |a Escherichia coli: metabolism |2 MeSH |
650 | _ | 2 | |a Privacy |2 MeSH |
650 | _ | 2 | |a Algorithms |2 MeSH |
700 | 1 | _ | |a Abele, Miriam |b 1 |
700 | 1 | _ | |a Bakhtiari, Mohammad |0 0000-0002-4169-9669 |b 2 |
700 | 1 | _ | |a von Toerne, Christine |0 0000-0002-4132-4322 |b 3 |
700 | 1 | _ | |a Barth, Teresa K |b 4 |
700 | 1 | _ | |a Schweizer, Lisa |0 0000-0002-1165-7804 |b 5 |
700 | 1 | _ | |a Giesbertz, Pieter |0 P:(DE-2719)9001718 |b 6 |u dzne |
700 | 1 | _ | |a Schmidt, Johannes R |0 0000-0002-2026-9715 |b 7 |
700 | 1 | _ | |a Kalkhof, Stefan |0 0000-0001-6121-7105 |b 8 |
700 | 1 | _ | |a Müller-Deile, Janina |0 0000-0001-6081-5664 |b 9 |
700 | 1 | _ | |a van Veelen, Peter A |0 0000-0002-7898-9408 |b 10 |
700 | 1 | _ | |a Mohammed, Yassene |0 0000-0003-3265-3332 |b 11 |
700 | 1 | _ | |a Hammer, Elke |0 0000-0002-1507-0402 |b 12 |
700 | 1 | _ | |a Arend, Lis |0 0000-0001-7990-8385 |b 13 |
700 | 1 | _ | |a Adamowicz, Klaudia |0 0000-0002-9418-4386 |b 14 |
700 | 1 | _ | |a Laske, Tanja |0 0000-0002-7922-7595 |b 15 |
700 | 1 | _ | |a Hartebrodt, Anne |b 16 |
700 | 1 | _ | |a Frisch, Tobias |b 17 |
700 | 1 | _ | |a Meng, Chen |b 18 |
700 | 1 | _ | |a Matschinske, Julian |b 19 |
700 | 1 | _ | |a Späth, Julian |b 20 |
700 | 1 | _ | |a Röttger, Richard |b 21 |
700 | 1 | _ | |a Schwämmle, Veit |b 22 |
700 | 1 | _ | |a Hauck, Stefanie M |0 0000-0002-1630-6827 |b 23 |
700 | 1 | _ | |a Lichtenthaler, Stefan F |0 P:(DE-2719)2181459 |b 24 |
700 | 1 | _ | |a Imhof, Axel |0 0000-0003-2993-8249 |b 25 |
700 | 1 | _ | |a Mann, Matthias |0 0000-0003-1292-4799 |b 26 |
700 | 1 | _ | |a Ludwig, Christina |0 0000-0002-6131-7322 |b 27 |
700 | 1 | _ | |a Kuster, Bernhard |0 0000-0002-9094-1677 |b 28 |
700 | 1 | _ | |a Baumbach, Jan |0 0000-0002-0282-0462 |b 29 |
700 | 1 | _ | |a Zolotareva, Olga |0 P:(DE-2719)9002089 |b 30 |u dzne |
773 | _ | _ | |a 10.1038/s43588-025-00832-7 |g Vol. 5, no. 8, p. 675 - 688 |0 PERI:(DE-600)3029424-1 |n 8 |p 675 - 688 |t Nature computational science |v 5 |y 2025 |x 2662-8457 |
856 | 4 | _ | |u https://pub.dzne.de/record/280783/files/DZNE-2025-00967%20SUP%2BSRC.zip |
856 | 4 | _ | |y OpenAccess |u https://pub.dzne.de/record/280783/files/DZNE-2025-00967%20SRC.xlsx |
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