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<Description>Quantitative mass spectrometry has transformed proteomics by allowing the simultaneous quantification of thousands of proteins. To boost statistical power, it is necessary to increase sample sizes by combining patient-derived data from various institutions. However, this practice raises significant privacy concerns. We created this dataset comtaining 30 healthy donors and 30 patients suffering from focal segmental glomerulosclerosis - a rare kidney disease - and distributed them to three independent proteomics centers. This distributed data were used as a proof of concept to introduce FedProt - the first privacy-preserving tool for collaborative differential protein abundance analysis of distributed data.</Description>
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