{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T03:55:13Z","timestamp":1772855713437,"version":"3.50.1"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1013526","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T00:00:00Z","timestamp":1760054400000}}],"reference-count":30,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T00:00:00Z","timestamp":1759190400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R21DA055672"],"award-info":[{"award-number":["R21DA055672"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["P01AI106684"],"award-info":[{"award-number":["P01AI106684"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01DK138458"],"award-info":[{"award-number":["R01DK138458"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2225775"],"award-info":[{"award-number":["2225775"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2310217"],"award-info":[{"award-number":["2310217"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007408","name":"Medical Center, University of Pittsburgh","doi-asserted-by":"publisher","award":["N\/A"],"award-info":[{"award-number":["N\/A"]}],"id":[{"id":"10.13039\/100007408","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Large-scale single-cell projects generate rapidly growing datasets, but downstream analysis is often confounded by data sources, requiring data integration methods to do correction. Existing data integration methods typically require data centralization, raising privacy and security concerns. Here, we introduce Federated Harmony, a novel method combining properties of federated learning with Harmony algorithm to integrate decentralized omics data. This approach preserves privacy by avoiding raw data sharing while maintaining integration performance comparable to Harmony. Experiments on various types of single-cell data showcase superior results, highlighting a novel data integration approach for distributed multi-omics data without compromising data privacy or analytical performance.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1013526","type":"journal-article","created":{"date-parts":[[2025,9,30]],"date-time":"2025-09-30T17:45:23Z","timestamp":1759254323000},"page":"e1013526","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":2,"title":["Harmony-based data integration for distributed single-cell multi-omics data"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-8996-8963","authenticated-orcid":true,"given":"Ruizhi","family":"Yuan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ziqi","family":"Rong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3619-2852","authenticated-orcid":true,"given":"Haoran","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianhao","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiyue","family":"Tao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6143-9314","authenticated-orcid":true,"given":"Lu","family":"Tang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2025,9,30]]},"reference":[{"issue":"8","key":"pcbi.1013526.ref001","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1038\/s41576-023-00580-2","article-title":"Methods and applications for single-cell and spatial multi-omics","volume":"24","author":"K Vandereyken","year":"2023","journal-title":"Nat Rev Genet"},{"key":"pcbi.1013526.ref002","doi-asserted-by":"crossref","DOI":"10.7554\/eLife.27041","article-title":"The Human Cell Atlas","volume":"6","author":"A Regev","year":"2017","journal-title":"Elife"},{"issue":"6","key":"pcbi.1013526.ref003","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1016\/j.tibtech.2017.02.012","article-title":"Why Batch Effects Matter in Omics Data, and How to Avoid Them","volume":"35","author":"WWB Goh","year":"2017","journal-title":"Trends Biotechnol"},{"issue":"5","key":"pcbi.1013526.ref004","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1038\/nbt.4096","article-title":"Integrating single-cell transcriptomic data across different conditions, technologies, and species","volume":"36","author":"A Butler","year":"2018","journal-title":"Nat Biotechnol"},{"issue":"5","key":"pcbi.1013526.ref005","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1038\/nbt.4091","article-title":"Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors","volume":"36","author":"L Haghverdi","year":"2018","journal-title":"Nat Biotechnol"},{"issue":"6","key":"pcbi.1013526.ref006","doi-asserted-by":"crossref","first-page":"685","DOI":"10.1038\/s41587-019-0113-3","article-title":"Efficient integration of heterogeneous single-cell transcriptomes using Scanorama","volume":"37","author":"B Hie","year":"2019","journal-title":"Nat Biotechnol"},{"issue":"3","key":"pcbi.1013526.ref007","doi-asserted-by":"crossref","first-page":"964","DOI":"10.1093\/bioinformatics\/btz625","article-title":"BBKNN: fast batch alignment of single cell transcriptomes","volume":"36","author":"K Pola\u0144ski","year":"2020","journal-title":"Bioinformatics"},{"issue":"12","key":"pcbi.1013526.ref008","doi-asserted-by":"crossref","first-page":"1289","DOI":"10.1038\/s41592-019-0619-0","article-title":"Fast, sensitive and accurate integration of single-cell data with Harmony","volume":"16","author":"I Korsunsky","year":"2019","journal-title":"Nat Methods"},{"issue":"3","key":"pcbi.1013526.ref009","article-title":"ComBat-seq: batch effect adjustment for RNA-seq count data","volume":"2","author":"Y Zhang","year":"2020","journal-title":"NAR Genom Bioinform"},{"key":"pcbi.1013526.ref010","article-title":"A privacy concern: Bioinformatics and storing biodata.","author":"DN Ferguson","year":"2021","journal-title":"The ADMI 2021 Symposium"},{"key":"pcbi.1013526.ref011","unstructured":"National Institutes of Health. Genomic Data Sharing Policy. Available from: https:\/\/sharing.nih.gov\/genomic-data-sharing-policy"},{"key":"pcbi.1013526.ref012","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-319-57959-7","volume-title":"The eu general data protection regulation (gdpr). A Practical Guide","author":"P Voigt","year":"2017","edition":"1"},{"key":"pcbi.1013526.ref013","unstructured":"Personal Information Protection Law (PIPL), 2021."},{"key":"pcbi.1013526.ref014","unstructured":"Lei Geral de Prote\u00e7\u00e3o de Dados (LGPD), Law No. 13,709, 2018."},{"key":"pcbi.1013526.ref015","first-page":"1243","article-title":"Privacy considerations for sharing genomics data","volume":"20","author":"M Oestreich","year":"2021","journal-title":"EXCLI J"},{"issue":"6","key":"pcbi.1013526.ref016","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1038\/nrg3723","article-title":"Routes for breaching and protecting genetic privacy","volume":"15","author":"Y Erlich","year":"2014","journal-title":"Nat Rev Genet"},{"key":"pcbi.1013526.ref017","article-title":"Communication-efficient learning of deep networks from decentralized data.","volume-title":"Artificial intelligence and statistics","author":"B McMahan","year":"2017"},{"key":"pcbi.1013526.ref018","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1038\/s41746-020-00323-1","article-title":"The future of digital health with federated learning","volume":"3","author":"N Rieke","year":"2020","journal-title":"NPJ Digit Med"},{"key":"pcbi.1013526.ref019","doi-asserted-by":"crossref","first-page":"106854","DOI":"10.1016\/j.cie.2020.106854","article-title":"A review of applications in federated learning","volume":"149","author":"L Li","year":"2020","journal-title":"Comput Ind Eng"},{"key":"pcbi.1013526.ref020","doi-asserted-by":"crossref","first-page":"104780","DOI":"10.1016\/j.jbi.2025.104780","article-title":"FedIMPUTE: Privacy-preserving missing value imputation for multi-site heterogeneous electronic health records","volume":"165","author":"S Li","year":"2025","journal-title":"J Biomed Inform"},{"key":"pcbi.1013526.ref021","doi-asserted-by":"crossref","first-page":"106775","DOI":"10.1016\/j.knosys.2021.106775","article-title":"A survey on federated learning","volume":"216","author":"C Zhang","year":"2021","journal-title":"Knowl Based Syst"},{"issue":"1","key":"pcbi.1013526.ref022","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1186\/s13059-019-1850-9","article-title":"A benchmark of batch-effect correction methods for single-cell RNA sequencing data","volume":"21","author":"HTN Tran","year":"2020","journal-title":"Genome Biol"},{"issue":"1","key":"pcbi.1013526.ref023","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1038\/s41592-021-01336-8","article-title":"Benchmarking atlas-level data integration in single-cell genomics","volume":"19","author":"MD Luecken","year":"2022","journal-title":"Nat Methods"},{"key":"pcbi.1013526.ref024","article-title":"Improved distributed principal component analysis","volume":"27","author":"Y Liang","year":"2014","journal-title":"Adv Neural Inf Process Syst"},{"key":"pcbi.1013526.ref025","doi-asserted-by":"crossref","first-page":"14049","DOI":"10.1038\/ncomms14049","article-title":"Massively parallel digital transcriptional profiling of single cells","volume":"8","author":"GXY Zheng","year":"2017","journal-title":"Nat Commun"},{"key":"pcbi.1013526.ref026","article-title":"Umap: Uniform manifold approximation and projection for dimension reduction.","author":"L McInnes","year":"2018"},{"issue":"5","key":"pcbi.1013526.ref027","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1016\/j.cell.2022.01.012","article-title":"A blood atlas of COVID-19 defines hallmarks of disease severity and specificity","volume":"185","author":"DJ Ahern","year":"2022","journal-title":"Cell"},{"key":"pcbi.1013526.ref028","first-page":"104102","article-title":"Investigating privacy leakage in dimensionality reduction methods via reconstruction attack","volume":"92","author":"C Lumbut","year":"2025","journal-title":"J Inf Security Appl"},{"key":"pcbi.1013526.ref029","doi-asserted-by":"crossref","DOI":"10.1007\/978-981-99-5177-2_5","article-title":"Data reconstruction attack against principal component analysis.","volume-title":"International Symposium on Security and Privacy in Social Networks and Big Data","author":"S Kwatra","year":"2023"},{"key":"pcbi.1013526.ref030","article-title":"Heterogeneity for the win: One-shot federated clustering.","volume-title":"International Conference on Machine Learning","author":"DK Dennis","year":"2021"}],"updated-by":[{"DOI":"10.1371\/journal.pcbi.1013526","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T00:00:00Z","timestamp":1760054400000}}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1013526","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T17:47:14Z","timestamp":1760118434000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1013526"}},"subtitle":[],"editor":[{"given":"Michael","family":"Domaratzki","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2025,9,30]]},"references-count":30,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2025,9,30]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1013526","relation":{"new_version":[{"id-type":"doi","id":"10.1371\/journal.pcbi.1013526","asserted-by":"object"}]},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,30]]}}}