{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T09:45:56Z","timestamp":1784627156655,"version":"3.55.0"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T00:00:00Z","timestamp":1717545600000},"content-version":"vor","delay-in-days":13,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72293581"],"award-info":[{"award-number":["72293581"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72293580"],"award-info":[{"award-number":["72293580"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["72274152"],"award-info":[{"award-number":["72274152"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,5,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Non-invasive prenatal testing (NIPT) is a quite popular approach for detecting fetal genomic aneuploidies. However, due to the limitations on sequencing read length and coverage, NIPT suffers a bottleneck on further improving performance and conducting earlier detection. The errors mainly come from reference biases and population polymorphism. To break this bottleneck, we proposed NIPT-PG, which enables the NIPT algorithm to learn from population data. A pan-genome model is introduced to incorporate variant and polymorphic loci information from tested population. Subsequently, we proposed a sequence-to-graph alignment method, which considers the read mis-match rates during the mapping process, and an indexing method using hash indexing and adjacency lists to accelerate the read alignment process. Finally, by integrating multi-source aligned read and polymorphic sites across the pan-genome, NIPT-PG obtains a more accurate z-score, thereby improving the accuracy of chromosomal aneuploidy detection. We tested NIPT-PG on two simulated datasets and 745 real-world cell-free DNA sequencing data sets from pregnant women. Results demonstrate that NIPT-PG outperforms the standard z-score test. Furthermore, combining experimental and theoretical analyses, we demonstrate the probably approximately correct learnability of NIPT-PG. In summary, NIPT-PG provides a new perspective for fetal chromosomal aneuploidies detection. NIPT-PG may have broad applications in clinical testing, and its detection results can serve as a reference for false positive samples approaching the critical threshold.<\/jats:p>","DOI":"10.1093\/bib\/bbae266","type":"journal-article","created":{"date-parts":[[2024,6,5]],"date-time":"2024-06-05T17:41:48Z","timestamp":1717609308000},"source":"Crossref","is-referenced-by-count":9,"title":["NIPT-PG: empowering non-invasive prenatal testing to learn from population genomics through an incremental pan-genomic approach"],"prefix":"10.1093","volume":"25","author":[{"given":"Zhengfa","family":"Xue","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Xi\u2019an Jiaotong University , Xi\u2019an 710049 , China"},{"name":"Shaanxi Engineering Research Center of Medical and Health Big Data, Xi\u2019an Jiaotong University , Xi\u2019an 710049 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aifen","family":"Zhou","sequence":"additional","affiliation":[{"name":"Institute of Maternal and Child Health , Wuhan Children\u2019s Hospital (Wuhan Maternal and Child Health care Hospital), Tongji Medical College, , Wuhan 430015 , China"},{"name":"Huazhong University of Science and Technology , Wuhan Children\u2019s Hospital (Wuhan Maternal and Child Health care Hospital), Tongji Medical College, , Wuhan 430015 , China"},{"name":"Department of Obstetrics , Wuhan Children\u2019s Hospital (Wuhan Maternal and Child Health care Hospital), Tongji Medical College, , Wuhan 430015 , China"},{"name":"Huazhong University of Science and Technology , Wuhan Children\u2019s Hospital (Wuhan Maternal and Child Health care Hospital), Tongji Medical College, , Wuhan 430015 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xi\u2019an Jiaotong University , Xi\u2019an 710049 , China"},{"name":"Shaanxi Engineering Research Center of Medical and Health Big Data, Xi\u2019an Jiaotong University , Xi\u2019an 710049 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Linxuan","family":"Li","sequence":"additional","affiliation":[{"name":"BGI Research , Shenzhen 518083 , China"},{"name":"College of Life Sciences, University of Chinese Academy of Sciences , Beijing 100049 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huanhuan","family":"Zhu","sequence":"additional","affiliation":[{"name":"BGI Research , Shenzhen 518083 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Jin","sequence":"additional","affiliation":[{"name":"BGI Research , Shenzhen 518083 , China"},{"name":"School of Medicine, South China University of Technology , Guangzhou 510006 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3862-6557","authenticated-orcid":false,"given":"Jiayin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xi\u2019an Jiaotong University , Xi\u2019an 710049 , China"},{"name":"Shaanxi Engineering Research Center of Medical and Health Big Data, Xi\u2019an Jiaotong University , Xi\u2019an 710049 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2024,6,5]]},"reference":[{"key":"2024060512305083500_ref1","doi-asserted-by":"crossref","first-page":"2014","DOI":"10.1056\/NEJMc2216144","article-title":"High-resolution and noninvasive fetal exome screening","volume":"389","author":"Brand","year":"2023","journal-title":"N Engl J 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