Privacy-Preserving Multi-Center Differential Protein Abundance Analysis with FedProt
Abstract
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 significant 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 LFQ E.coli experiments and one at three centers from TMT human serum. Evaluations using these datasets confirm that FedProt achieves accuracy equivalent to DEqMS applied to pooled data, with completely negligible absolute differences no greater than \text{4 \times 10^{-12}}. In contrast, -log10(p-values) computed by the most accurate meta-analysis methods diverged from the centralized analysis results by up to 25-27. FedProt is available as a web tool with detailed documentation as a FeatureCloud App.
Cite
@article{arxiv.2407.15220,
title = {Privacy-Preserving Multi-Center Differential Protein Abundance Analysis with FedProt},
author = {Yuliya Burankova and Miriam Abele and Mohammad Bakhtiari and Christine von Törne and Teresa Barth and Lisa Schweizer and Pieter Giesbertz and Johannes R. Schmidt and Stefan Kalkhof and Janina Müller-Deile and Peter A van Veelen and Yassene Mohammed and Elke Hammer and Lis Arend and Klaudia Adamowicz and Tanja Laske and Anne Hartebrodt and Tobias Frisch and Chen Meng and Julian Matschinske and Julian Späth and Richard Röttger and Veit Schwämmle and Stefanie M. Hauck and Stefan Lichtenthaler and Axel Imhof and Matthias Mann and Christina Ludwig and Bernhard Kuster and Jan Baumbach and Olga Zolotareva},
journal= {arXiv preprint arXiv:2407.15220},
year = {2025}
}
Comments
52 pages, 16 figures, 12 tables. Last two authors listed are joint last authors