{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T02:50:27Z","timestamp":1791341427899,"version":"4.3.1"},"reference-count":45,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2022,1,21]],"date-time":"2022-01-21T00:00:00Z","timestamp":1642723200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Stiftelsen KG Jebsen","award":["SKGJ-MED-017"],"award-info":[{"award-number":["SKGJ-MED-017"]}]},{"name":"Norwegian Research Council via the ProCardio Center for Innovation","award":["32481"],"award-info":[{"award-number":["32481"]}]},{"name":"IKTPLUSS","award":["#311341"],"award-info":[{"award-number":["#311341"]}]},{"name":"Research Council of Norway IKTPLUSS project","award":["#311341"],"award-info":[{"award-number":["#311341"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,3,10]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>T-cell receptor (TCR) sequencing has enabled the development of innovative diagnostic tests for cancers, autoimmune diseases and other applications. However, the rarity of many T-cell clonotypes presents a detection challenge, which may lead to misdiagnosis if diagnostically relevant TCRs remain undetected. To address this issue, we developed TCRpower, a novel computational pipeline for quantifying the statistical detection power of TCR sequencing methods. TCRpower calculates the probability of detecting a TCR sequence as a function of several key parameters: in-vivo TCR frequency, T-cell sample count, read sequencing depth and read cutoff. To calibrate TCRpower, we selected unique TCRs of 45 T-cell clones (TCCs) as spike-in TCRs. We sequenced the spike-in TCRs from TCCs, together with TCRs from peripheral blood, using a 5\u2032 RACE protocol. The 45 spike-in TCRs covered a wide range of sample frequencies, ranging from 5 per 100 to 1 per 1 million. The resulting spike-in TCR read counts and ground truth frequencies allowed us to calibrate TCRpower. In our TCR sequencing data, we observed a consistent linear relationship between sample and sequencing read frequencies. We were also able to reliably detect spike-in TCRs with frequencies as low as one per million. By implementing an optimized read cutoff, we eliminated most of the falsely detected sequences in our data (TCR \u03b1-chain 99.0% and TCR \u03b2-chain 92.4%), thereby improving diagnostic specificity. TCRpower is publicly available and can be used to optimize future TCR sequencing experiments, and thereby enable reliable detection of disease-relevant TCRs for diagnostic applications.<\/jats:p>","DOI":"10.1093\/bib\/bbab566","type":"journal-article","created":{"date-parts":[[2021,12,13]],"date-time":"2021-12-13T20:13:10Z","timestamp":1639426390000},"source":"Crossref","is-referenced-by-count":14,"title":["TCRpower: quantifying the detection power of T-cell receptor sequencing with a novel computational pipeline calibrated by spike-in sequences"],"prefix":"10.1093","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0165-5098","authenticated-orcid":false,"given":"Shiva","family":"Dahal-Koirala","sequence":"first","affiliation":[{"name":"K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, 0372, Norway"},{"name":"Department of Immunology, University of Oslo and Oslo University Hospital-Rikshospitalet, Oslo, 0372, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6794-9611","authenticated-orcid":false,"given":"Gabriel","family":"Balaban","sequence":"additional","affiliation":[{"name":"Biomedical Informatics, Department of Informatics, University of Oslo, 0373, Oslo, Norway"},{"name":"Department of Computational Physiology, Simula Research Laboratory, 1364, Fornebu, Norway"},{"name":"PharmaTox Strategic Research Initiative, Faculty of Mathematics and Natural Sciences, University of Oslo, 0373, Oslo, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ralf Stefan","family":"Neumann","sequence":"additional","affiliation":[{"name":"K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, 0372, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lonneke","family":"Scheffer","sequence":"additional","affiliation":[{"name":"Biomedical Informatics, Department of Informatics, University of Oslo, 0373, Oslo, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Knut Erik Aslaksen","family":"Lundin","sequence":"additional","affiliation":[{"name":"K.G. Jebsen Coeliac Disease Research Centre, University of Oslo, Oslo, 0372, Norway"},{"name":"Department of Gastroenterology, Oslo University Hospital-Rikshospitalet, 0372, Oslo, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2622-5032","authenticated-orcid":false,"given":"Victor","family":"Greiff","sequence":"additional","affiliation":[{"name":"Department of Immunology, University of Oslo and Oslo University Hospital-Rikshospitalet, Oslo, 0372, Norway"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ludvig Magne","family":"Sollid","sequence":"additional","affiliation":[{"name":"K.G. 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