{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T18:09:39Z","timestamp":1775758179790,"version":"3.50.1"},"reference-count":45,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T00:00:00Z","timestamp":1773446400000},"content-version":"vor","delay-in-days":1533,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Flemish Government via the Flanders AI Research Program","award":["174B09119"],"award-info":[{"award-number":["174B09119"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Current spatial proteomics data analysis workflows are limited in efficiency and scalability when applied to gigapixel sized datasets. Moreover, they often lack extensive quality control tools and exhibit limited interoperability with existing spatial omics analysis ecosystems.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We introduce Harpy, a new Python workflow capable of accelerated processing of large spatial proteomics datasets. We demonstrate the utility of Harpy on four datasets and show that it can rapidly apply state-of-the-art segmentation and feature extraction via parallel processing. Each analysis step is accompanied by appropriate quality control steps. Scalable clustering of cells and pixels allows identification of cell types, processed up to 27 times faster than previously reported. Processing and visualization can be performed locally or on high-performance computing servers. Additionally, Harpy integrates well with existing spatial single-cell analysis tools in the Python and R software ecosystem.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Harpy is available on GitHub at https:\/\/github.com\/saeyslab\/harpy and archived on Zenodo at https:\/\/doi.org\/10.5281\/zenodo.15546703.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btag122","type":"journal-article","created":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T12:32:51Z","timestamp":1773145971000},"source":"Crossref","is-referenced-by-count":0,"title":["Scalable analysis of whole slide spatial proteomics with Harpy"],"prefix":"10.1093","volume":"42","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4022-715X","authenticated-orcid":false,"given":"Benjamin","family":"Rombaut","sequence":"first","affiliation":[{"name":"VIB-UGent Center for Inflammation Research Data Mining and Modelling for Biomedicine, , 9000 Ghent,","place":["Belgium"]},{"name":"Ghent University Department of Mathematics, Computer Science and Statistics, , 9000 Ghent,","place":["Belgium"]},{"name":"VIB Center for AI and Computational Biology , 9000 Ghent,","place":["Belgium"]}]},{"given":"Arne","family":"Defauw","sequence":"additional","affiliation":[{"name":"VIB Technologies VIB Spatial Catalyst, , 9000 Ghent,","place":["Belgium"]}]},{"given":"Frank","family":"Vernaillen","sequence":"additional","affiliation":[{"name":"VIB Technologies VIB Spatial Catalyst, , 9000 Ghent,","place":["Belgium"]}]},{"given":"Julien","family":"Mortier","sequence":"additional","affiliation":[{"name":"VIB Technologies VIB Spatial Catalyst, , 9000 Ghent,","place":["Belgium"]}]},{"given":"Evelien","family":"Van Hamme","sequence":"additional","affiliation":[{"name":"VIB Technologies VIB Spatial Catalyst, , 9000 Ghent,","place":["Belgium"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7119-5330","authenticated-orcid":false,"given":"Sofie","family":"Van Gassen","sequence":"additional","affiliation":[{"name":"VIB-UGent Center for Inflammation Research Data Mining and Modelling for Biomedicine, , 9000 Ghent,","place":["Belgium"]},{"name":"Ghent University Department of Mathematics, Computer Science and Statistics, , 9000 Ghent,","place":["Belgium"]},{"name":"VIB Center for AI and Computational Biology , 9000 Ghent,","place":["Belgium"]}]},{"given":"Ruth","family":"Seurinck","sequence":"additional","affiliation":[{"name":"VIB-UGent Center for Inflammation Research Data Mining and Modelling for Biomedicine, , 9000 Ghent,","place":["Belgium"]},{"name":"Ghent University Department of Mathematics, Computer Science and Statistics, , 9000 Ghent,","place":["Belgium"]},{"name":"VIB Center for AI and Computational Biology , 9000 Ghent,","place":["Belgium"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0415-1506","authenticated-orcid":false,"given":"Yvan","family":"Saeys","sequence":"additional","affiliation":[{"name":"VIB-UGent Center for Inflammation Research Data Mining and Modelling for Biomedicine, , 9000 Ghent,","place":["Belgium"]},{"name":"Ghent University Department of Mathematics, Computer Science and Statistics, , 9000 Ghent,","place":["Belgium"]},{"name":"VIB Center for AI and Computational Biology , 9000 Ghent,","place":["Belgium"]}]}],"member":"286","published-online":{"date-parts":[[2026,3,13]]},"reference":[{"key":"2026040913195907300_btag122-B1","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1038\/nmeth.1896","article-title":"OMERO: flexible, model-driven data management for experimental biology","volume":"9","author":"Allan","year":"2012","journal-title":"Nat Methods"},{"key":"2026040913195907300_btag122-B2","doi-asserted-by":"crossref","first-page":"2248","DOI":"10.1038\/s41592-024-02328-0","article-title":"Quality control for single-cell analysis of high-plex tissue profiles using CyLinter","volume":"21","author":"Baker","year":"2024","journal-title":"Nat Methods"},{"key":"2026040913195907300_btag122-B3","doi-asserted-by":"crossref","first-page":"16878","DOI":"10.1038\/s41598-017-17204-5","article-title":"QuPath: open source software for digital pathology image analysis","volume":"7","author":"Bankhead","year":"2017","journal-title":"Sci Rep"},{"key":"2026040913195907300_btag122-B4","doi-asserted-by":"crossref","first-page":"3802","DOI":"10.1038\/s41596-021-00556-8","article-title":"CODEX multiplexed tissue imaging with DNA-conjugated antibodies","volume":"16","author":"Black","year":"2021","journal-title":"Nat Protoc"},{"key":"2026040913195907300_btag122-B5","doi-asserted-by":"crossref","first-page":"4981","DOI":"10.1038\/s41467-024-48981-z","article-title":"Sopa: a technology-invariant pipeline for analyses of image-based spatial omics","volume":"15","author":"Blampey","year":"2024","journal-title":"Nat Commun"},{"key":"2026040913195907300_btag122-B6","doi-asserted-by":"crossref","first-page":"eabq4964","DOI":"10.1126\/science.abq4964","article-title":"The dawn of spatial omics","volume":"381","author":"Bressan","year":"2023","journal-title":"Science"},{"key":"2026040913195907300_btag122-B7","doi-asserted-by":"publisher","author":"Buglakova","year":"2025","DOI":"10.48550\/arXiv.2503.19545"},{"key":"2026040913195907300_btag122-B8","doi-asserted-by":"crossref","first-page":"2212","DOI":"10.1038\/s41592-024-02539-5","article-title":"Multiplexed image analysis: what have we achieved and where are we headed?","volume":"21","author":"Bussi","year":"2024","journal-title":"Nat Methods"},{"key":"2026040913195907300_btag122-B9","author":"Cannoodt","year":"2025"},{"key":"2026040913195907300_btag122-B10","first-page":"1","article-title":"Spatial multiplexing and omics","volume":"4","author":"Carstens","year":"2024","journal-title":"Nat Rev Methods Primer"},{"key":"2026040913195907300_btag122-B11","doi-asserted-by":"crossref","first-page":"btae179","DOI":"10.1093\/bioinformatics\/btae179","article-title":"Efficient cytometry analysis with FlowSOM in python boosts interoperability with other single-cell tools","volume":"40","author":"Couckuyt","year":"2024","journal-title":"Bioinformatics"},{"key":"2026040913195907300_btag122-B12","author":"Crowell","year":"2025"},{"key":"2026040913195907300_btag122-B13","author":"Fedor","year":"2025"},{"key":"2026040913195907300_btag122-B14","author":"Goldsborough","year":"2024"},{"key":"2026040913195907300_btag122-B15","doi-asserted-by":"publisher","author":"Goldsborough","year":"2024","DOI":"10.48550\/arXiv.2408.15954"},{"key":"2026040913195907300_btag122-B16","author":"Greenwald","year":"2021"},{"key":"2026040913195907300_btag122-B17","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1016\/j.cell.2021.12.018","article-title":"Spatial proteogenomics reveals distinct and evolutionarily conserved hepatic macrophage niches","volume":"185","author":"Guilliams","year":"2022","journal-title":"Cell"},{"key":"2026040913195907300_btag122-B18","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1038\/s41592-024-02436-x","article-title":"Vitessce: integrative visualization of multimodal and spatially resolved single-cell data","volume":"22","author":"Keller","year":"2025","journal-title":"Nat Methods"},{"key":"2026040913195907300_btag122-B19","doi-asserted-by":"crossref","first-page":"100595","DOI":"10.1016\/j.crmeth.2023.100595","article-title":"Dual-modality imaging of immunofluorescence and imaging mass cytometry for whole-slide imaging and accurate segmentation","volume":"3","author":"Kim","year":"2023","journal-title":"Cell Rep Methods"},{"key":"2026040913195907300_btag122-B20","doi-asserted-by":"crossref","first-page":"1911","DOI":"10.1038\/s41598-022-05841-4","article-title":"MACSima imaging cyclic staining (MICS) technology reveals combinatorial target pairs for CAR T cell treatment of solid tumors","volume":"12","author":"Kinkhabwala","year":"2022","journal-title":"Sci Rep"},{"key":"2026040913195907300_btag122-B21","doi-asserted-by":"crossref","first-page":"1550","DOI":"10.1109\/TMI.2017.2677499","article-title":"A dataset and a technique for generalized nuclear segmentation for computational pathology","volume":"36","author":"Kumar","year":"2017","journal-title":"IEEE Trans Med Imaging"},{"key":"2026040913195907300_btag122-B22","doi-asserted-by":"crossref","first-page":"jcs261567","DOI":"10.1242\/jcs.261567","article-title":"Believing is seeing\u2013the deceptive influence of bias in quantitative microscopy","volume":"137","author":"Lee","year":"2024","journal-title":"J Cell Sci"},{"key":"2026040913195907300_btag122-B23","author":"Leigh","year":"2017"},{"key":"2026040913195907300_btag122-B24","author":"Liu","year":"2022"},{"key":"2026040913195907300_btag122-B25","doi-asserted-by":"crossref","first-page":"4618","DOI":"10.1038\/s41467-023-40068-5","article-title":"Robust phenotyping of highly multiplexed tissue imaging data using pixel-level clustering","volume":"14","author":"Liu","year":"2023","journal-title":"Nat Commun"},{"key":"2026040913195907300_btag122-B26","doi-asserted-by":"crossref","first-page":"10026","DOI":"10.1051\/bioconf\/202412910026","article-title":"Fractal: an open-source framework for reproducible bioimage analysis at scale using OME-Zarrs","volume":"129","author":"L\u00fcthi","year":"2024","journal-title":"BIO Web Conf"},{"key":"2026040913195907300_btag122-B27","doi-asserted-by":"crossref","first-page":"5135","DOI":"10.1038\/s41467-024-48870-5","article-title":"Deep cell phenotyping and spatial analysis of multiplexed imaging with TRACERx-PHLEX","volume":"15","author":"Magness","year":"2024","journal-title":"Nat Commun"},{"key":"2026040913195907300_btag122-B28","doi-asserted-by":"crossref","first-page":"58","DOI":"10.1038\/s41592-024-02212-x","article-title":"SpatialData: an open and universal data framework for spatial omics","volume":"22","author":"Marconato","year":"2025","journal-title":"Nat Methods"},{"key":"2026040913195907300_btag122-B29","author":"Martin","year":"2024"},{"key":"2026040913195907300_btag122-B30","doi-asserted-by":"publisher","author":"McInnes","year":"2020","DOI":"10.48550\/arXiv.1802.03426"},{"key":"2026040913195907300_btag122-B31","doi-asserted-by":"crossref","first-page":"1496","DOI":"10.1038\/s41592-021-01326-w","article-title":"OME-NGFF: a next-generation file format for expanding bioimaging data-access strategies","volume":"18","author":"Moore","year":"2021","journal-title":"Nat Methods"},{"key":"2026040913195907300_btag122-B32","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1038\/s41592-021-01358-2","article-title":"Squidpy: a scalable framework for spatial omics analysis","volume":"19","author":"Palla","year":"2022","journal-title":"Nat Methods"},{"key":"2026040913195907300_btag122-B33","author":"Pollaris","year":"2024"},{"key":"2026040913195907300_btag122-B34","doi-asserted-by":"crossref","first-page":"126","DOI":"10.25080\/Majora-7b98e3ed-013","article-title":"Dask: parallel computation with blocked algorithms and task scheduling","author":"Rocklin","year":"2015","journal-title":"Proc 14th Python Sci Conf"},{"key":"2026040913195907300_btag122-B35","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1038\/s41592-021-01308-y","article-title":"MCMICRO: a scalable, modular image-processing pipeline for multiplexed tissue imaging","volume":"19","author":"Schapiro","year":"2022","journal-title":"Nat Methods"},{"key":"2026040913195907300_btag122-B36","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1038\/s41592-022-01415-4","article-title":"MITI minimum information guidelines for highly multiplexed tissue images","volume":"19","author":"Schapiro","year":"2022","journal-title":"Nat Methods"},{"key":"2026040913195907300_btag122-B37","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1038\/s41588-024-01664-3","article-title":"BANKSY unifies cell typing and tissue domain segmentation for scalable spatial omics data analysis","volume":"56","author":"Singhal","year":"2024","journal-title":"Nat Genet"},{"key":"2026040913195907300_btag122-B38","unstructured":"Sofroniew N, Lambert T, Evans K \u00a0et al \u00a0napari: a multi-dimensional image viewer for Python, 2022, 10.5281\/zenodo.6598542"},{"key":"2026040913195907300_btag122-B39","doi-asserted-by":"crossref","first-page":"592","DOI":"10.1038\/s41592-025-02595-5","article-title":"Cellpose3: one-click image restoration for improved cellular segmentation","volume":"22","author":"Stringer","year":"2025","journal-title":"Nat Methods"},{"key":"2026040913195907300_btag122-B40","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1038\/s41592-020-01018-x","article-title":"Cellpose: a generalist algorithm for cellular segmentation","volume":"18","author":"Stringer","year":"2021","journal-title":"Nat Methods"},{"key":"2026040913195907300_btag122-B41","author":"Tan","year":"2024"},{"key":"2026040913195907300_btag122-B42","doi-asserted-by":"publisher","first-page":"1336257","DOI":"10.3389\/fbinf.2024.1336257","article-title":"A perspective on FAIR quality control in multiplexed imaging data processing","volume":"4","author":"Vierdag","year":"2024","journal-title":"Front Bioinform"},{"key":"2026040913195907300_btag122-B43","doi-asserted-by":"crossref","first-page":"604","DOI":"10.1038\/s41587-023-01733-8","article-title":"The scverse project provides a computational ecosystem for single-cell omics data analysis","volume":"41","author":"Virshup","year":"2023","journal-title":"Nat Biotechnol"},{"key":"2026040913195907300_btag122-B44","author":"Virshup","year":"2021"},{"key":"2026040913195907300_btag122-B45","doi-asserted-by":"crossref","first-page":"3565","DOI":"10.1038\/s41596-023-00881-0","article-title":"An end-to-end workflow for multiplexed image processing and analysis","volume":"18","author":"Windhager","year":"2023","journal-title":"Nat Protoc"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/advance-article-pdf\/doi\/10.1093\/bioinformatics\/btag122\/67346258\/btag122.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/42\/3\/btag122\/67346258\/btag122.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/42\/3\/btag122\/67346258\/btag122.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T17:20:11Z","timestamp":1775755211000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/doi\/10.1093\/bioinformatics\/btag122\/8519620"}},"subtitle":[],"editor":[{"given":"Xin","family":"Gao","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2022,1,1]]},"references-count":45,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2022,1,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btag122","relation":{},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2026,3]]},"published":{"date-parts":[[2022,1,1]]},"article-number":"btag122"}}