{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T12:59:32Z","timestamp":1791464372771,"version":"4.3.4"},"reference-count":49,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T00:00:00Z","timestamp":1791417600000},"content-version":"vor","delay-in-days":37,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"JST CREST","award":["JPMJCR2011"],"award-info":[{"award-number":["JPMJCR2011"]}]},{"name":"JST CREST","award":["JPMJCR25Q2"],"award-info":[{"award-number":["JPMJCR25Q2"]}]},{"name":"JSPS KAKENHI","award":["1280666"],"award-info":[{"award-number":["1280666"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Identifying antigen-specific T cell receptors (TCRs) within the diverse human repertoire remains challenging, particularly for low-frequency clonotypes. Here, we present TCR-RADAR (TCR Rare Antigen-specific Detection by Anomaly Ranking), an unsupervised approach that detects low-frequency antigen-specific TCRs through distance-based anomaly detection in TCR sequence space. Using TCRdist3 to quantify sequence distances, we identify query TCRs that are anomalous relative to reference repertoires within their V-J gene combinations. We validated this approach across three immunological contexts: COVID-19 infection, influenza vaccination, and yellow fever vaccination. For SARS-CoV-2-specific TCR detection in a COVID-19 patient, our method achieved 34.3% precision, substantially higher than similarity-based (ALICE: 8.0%) and frequency-based methods (edgeR: 5.8%, the Pogorelyy method: 6.3%), and uniquely detected low-frequency antigen-specific TCRs present at a clone count of 1. The minimal overlap with conventional approaches (0%\u20136.7% across the three datasets) indicates our method captures distinct TCR clones overlooked by existing analyses. This distance-based approach provides a complementary strategy for TCR specificity detection, particularly valuable for identifying rare antigen-specific clones essential for understanding immune responses.<\/jats:p>","DOI":"10.1093\/bib\/bbag511","type":"journal-article","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T11:32:20Z","timestamp":1788867140000},"source":"Crossref","is-referenced-by-count":0,"title":["Unsupervised identification of low-frequency antigen-specific TCRs using distance-based anomaly scoring"],"prefix":"10.1093","volume":"27","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-0365-7985","authenticated-orcid":false,"given":"Kyohei","family":"Kinoshita","sequence":"first","affiliation":[{"name":"Department of Electrical Engineering and Information Systems, Graduate School of Engineering, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 ,","place":["Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tetsuya J","family":"Kobayashi","sequence":"additional","affiliation":[{"name":"Institute of Industrial Science, The University of Tokyo , 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 ,","place":["Japan"]},{"name":"Department of Electrical Engineering and Information Systems, Graduate School of Engineering, The University of Tokyo , 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 ,","place":["Japan"]},{"name":"Universal Biology Institute, The University of Tokyo , 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033 ,","place":["Japan"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,10,8]]},"reference":[{"key":"2026100808252190600_ref1","doi-asserted-by":"publisher","first-page":"e2308511120","DOI":"10.1073\/pnas.2308511120","article-title":"The total mass, number, and distribution of immune cells in the human body","volume":"120","author":"Sender","year":"2023","journal-title":"Proc Natl Acad Sci 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