{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T19:47:49Z","timestamp":1780429669822,"version":"3.54.1"},"reference-count":23,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2022,7,16]],"date-time":"2022-07-16T00:00:00Z","timestamp":1657929600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"HKSAR Government","award":["17113721"],"award-info":[{"award-number":["17113721"]}]},{"DOI":"10.13039\/100010890","name":"Oxford Nanopore Technologies","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010890","id-type":"DOI","asserted-by":"publisher"}]},{"name":"General Program","award":["JCYJ20210324134405015"],"award-info":[{"award-number":["JCYJ20210324134405015"]}]},{"name":"Shenzhen Municipal Government"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,9,20]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Accurate identification of genetic variants from family child\u2013mother\u2013father trio sequencing data is important in genomics. However, state-of-the-art approaches treat variant calling from trios as three independent tasks, which limits their calling accuracy for Nanopore long-read sequencing data. For better trio variant calling, we introduce Clair3-Trio, the first variant caller tailored for family trio data from Nanopore long-reads. Clair3-Trio employs a Trio-to-Trio deep neural network model, which allows it to input the trio sequencing information and output all of the trio\u2019s predicted variants within a single model to improve variant calling. We also present MCVLoss, a novel loss function tailor-made for variant calling in trios, leveraging the explicit encoding of the Mendelian inheritance. Clair3-Trio showed comprehensive improvement in experiments. It predicted far fewer Mendelian inheritance violation variations than current state-of-the-art methods. We also demonstrated that our Trio-to-Trio model is more accurate than competing architectures. Clair3-Trio is accessible as a free, open-source project at https:\/\/github.com\/HKU-BAL\/Clair3-Trio.<\/jats:p>","DOI":"10.1093\/bib\/bbac301","type":"journal-article","created":{"date-parts":[[2022,7,18]],"date-time":"2022-07-18T11:11:44Z","timestamp":1658142704000},"source":"Crossref","is-referenced-by-count":28,"title":["Clair3-trio: high-performance Nanopore long-read variant calling in family trios with trio-to-trio deep neural networks"],"prefix":"10.1093","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8560-3999","authenticated-orcid":false,"given":"Junhao","family":"Su","sequence":"first","affiliation":[{"name":"Department of Computer Science, The University of Hong Kong , Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6546-2324","authenticated-orcid":false,"given":"Zhenxian","family":"Zheng","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The University of Hong Kong , Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Syed Shakeel","family":"Ahmed","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The University of Hong Kong , Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4676-8587","authenticated-orcid":false,"given":"Tak-Wah","family":"Lam","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The University of Hong Kong , Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9711-6533","authenticated-orcid":false,"given":"Ruibang","family":"Luo","sequence":"additional","affiliation":[{"name":"Department of Computer Science, The University of Hong Kong , Hong Kong, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,7,17]]},"reference":[{"key":"2022092013212424600_ref1","doi-asserted-by":"crossref","first-page":"D789","DOI":"10.1093\/nar\/gku1205","article-title":"OMIM. 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