{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T00:41:18Z","timestamp":1776904878225,"version":"3.51.2"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T00:00:00Z","timestamp":1773619200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T00:00:00Z","timestamp":1776902400000},"content-version":"vor","delay-in-days":38,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"National Research Foundation in Republic of Korea","award":["RS-2023-00223069"],"award-info":[{"award-number":["RS-2023-00223069"]}]},{"name":"National Research Foundation in Republic of Korea","award":["RS-2025-02214225"],"award-info":[{"award-number":["RS-2025-02214225"]}]},{"name":"NAVER-SNUH","award":["37-2024-2170"],"award-info":[{"award-number":["37-2024-2170"]}]},{"name":"BK21 Four Biomedical Science Program"},{"name":"Seoul National University College of Medicine Creative-Pioneering Researchers Program"},{"DOI":"10.13039\/501100010446","name":"Institute of Basic Science","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100010446","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Genom. Inform."],"published-print":{"date-parts":[[2026,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Large-scale genomic rearrangements are prevalent in cancer genomes and can profoundly rewire three-dimensional (3D) genome architecture, leading to aberrant oncogene activation through enhancer hijacking. The rewired 3D organization generates unique chromatin contact signatures, which can be detected using deep learning-based approaches. However, extending such analyses to single-cell resolution, which is critical to delineate clonal heterogeneity in cancer, remains a major challenge, due to the limited number of training sets as single-cell Hi-C techniques are not standardized and only limited datasets are available across different methods. Here, we introduce scCAPReSE, a few-shot learning-based framework that adopts representations from a pre-trained image foundation model, CLIP, to enable robust classification of structural variation (SV) patterns in single-cell Hi-C data. By extracting and fine-tuning base weights from the foundation model, scCAPReSE enables effective training of deep learning classifiers using only a few hundred large-scale SV examples derived from a single cancer cell line while adapting classification tasks to heterogeneous single-cell Hi-C libraries. scCAPReSE achieved over 90% classification accuracy when evaluated on sci-Hi-C datasets. When further applied to scNanoHi-C data from the K562 chronic myeloid leukemia cell line, scCAPReSE correctly identified the Philadelphia chromosome translocation but also revealed substantial cell-to-cell variability in the contribution of SV-mediated chromatin interactions, highlighting previously inaccessible heterogeneity in cancer 3D genome organization. In summary, scCAPReSE provides a broadly applicable and data-efficient framework for detecting SV-driven 3D genome reorganization at single-cell resolution, enabling quantitative dissection of cancer-specific chromatin architecture and clonal heterogeneity. The developed method is freely available at\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"https:\/\/github.com\/kaistcbfg\/CAPReSE.\" ext-link-type=\"uri\">https:\/\/github.com\/kaistcbfg\/CAPReSE.<\/jats:ext-link>\n                  <\/jats:p>","DOI":"10.1186\/s44342-026-00069-4","type":"journal-article","created":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T10:44:01Z","timestamp":1773657841000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["scCAPReSE: detection of large-scale genomic rearrangements from single-cell Hi-C based on few-shot learning"],"prefix":"10.1186","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5571-4949","authenticated-orcid":false,"given":"Kyukwang","family":"Kim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0643-0100","authenticated-orcid":false,"given":"Chul-Hwan","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5885-2754","authenticated-orcid":false,"given":"Inkyung","family":"Jung","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,3,16]]},"reference":[{"key":"69_CR1","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1038\/nrg1767","volume":"7","author":"L Feuk","year":"2006","unstructured":"Feuk L, Carson AR, Scherer SW. 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The paper was handled by another Editor and has undergone a rigorous peer review process. Author I.Jung was not involved in the journal's peer review of, or decisions related to, this manuscript.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"8"}}