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However, analyzing the resulting high-dimensional, gigabyte-scale datasets remains challenging due to fragmented workflows, intensive computational requirements, and a lack of accessible, user-friendly tools for non-technical researchers.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>We introduce SPAC (analysis of SPAtial single-Cell datasets), a scalable, web-based platform for efficient and reproducible single-cell spatial analysis. SPAC employs a four-tier architecture that includes a modular Python-based analysis engine, seamless integration with high-performance computing (HPC) and GPU acceleration, an interactive browser interface for no-code workflow configuration, and a real-time visualization layer powered by Shiny for Python dashboards. This design empowers distinct user roles: data scientists can extend and customize analysis modules, while bench scientists can execute complete workflows and interactively explore results without coding. Built-in reproducibility features and collaborative workflow support ensure that analyses are transparent and easily shared across research teams. Using a 2.6-million-cell multiplex imaging dataset from a 4T1 breast tumor model as a benchmark, SPAC reduced unsupervised clustering time from\u2009~3\u00a0hours on a CPU to under 10\u00a0minutes with GPU acceleration, achieving more than a 20-fold speedup. It also enabled fine-grained spatial profiling of distinct tumor microenvironment compartments, demonstrating the platform\u2019s scalability and performance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>SPAC addresses major barriers in single-cell spatial analysis by uniting an intuitive, user-friendly interface with scalable, high-performance computation in a robust and reproducible framework. By streamlining complex analyses and bridging the gap between experimental and computational researchers, SPAC fosters collaborative workflows and accelerates the transformation of large-scale spatial datasets into actionable biological insights.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12859-025-06339-2","type":"journal-article","created":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T12:30:40Z","timestamp":1769689840000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["SPAC: a scalable and integrated enterprise platform for single-cell spatial analysis"],"prefix":"10.1186","volume":"27","author":[{"given":"Fang","family":"Liu","sequence":"first","affiliation":[]},{"given":"Rui","family":"He","sequence":"additional","affiliation":[]},{"given":"Thomas","family":"Sheeley","sequence":"additional","affiliation":[]},{"given":"David A.","family":"Scheiblin","sequence":"additional","affiliation":[]},{"given":"Stephen J.","family":"Lockett","sequence":"additional","affiliation":[]},{"given":"Lisa A.","family":"Ridnour","sequence":"additional","affiliation":[]},{"given":"David A.","family":"Wink","sequence":"additional","affiliation":[]},{"given":"Mark","family":"Jensen","sequence":"additional","affiliation":[]},{"given":"Janelle","family":"Cortner","sequence":"additional","affiliation":[]},{"given":"George","family":"Zaki","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,29]]},"reference":[{"key":"6339_CR1","doi-asserted-by":"publisher","first-page":"1653","DOI":"10.1016\/j.ccell.2024.09.001","volume":"42","author":"D Gong","year":"2024","unstructured":"Gong D, Arbesfeld-Qiu JM, Perrault E, Bae JW, Hwang WL. 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Our facility is accredited and approved by the Association for Accreditation of Laboratory Animal Care International and follows the Public Health Service Policy for the Care and Use of Laboratory Animals (IBC 2023-42; ACUC 21-109).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"25"}}