{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T01:03:26Z","timestamp":1760576606735,"version":"build-2065373602"},"reference-count":42,"publisher":"Oxford University Press (OUP)","issue":"5","license":[{"start":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T00:00:00Z","timestamp":1760486400000},"content-version":"vor","delay-in-days":45,"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":["62402376","62572389","72293581","72274152"],"award-info":[{"award-number":["62402376","62572389","72293581","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":[[2025,8,31]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Detection of structural variations (SVs) through circulating tumor DNA (ctDNA) has become a key method for detecting minimal residual disease (MRD). However, the heterogeneity of ctDNA samples, characterized by variable limits of detection (LOD) and diverse structural variant types, significantly impacts detection stability and performance, posing persistent challenges for conventional SV detection tools such as Delly and Manta. These widely used methods require extensive manual parameter tuning, hindered by the combinatorial complexity of multiple parameters and heterogeneous sequencing data. To address this, we propose MRDadaptis, a novel SV detection tool that uniquely incorporates a self-adaptive parameter optimization mechanism. MRDadaptis distinguishes itself by integrating Bayesian optimization with meta-learning techniques to dynamically adjust detection parameters automatically, based on intrinsic features derived from the ctDNA sequencing data itself. This innovative approach not only reduces manual intervention but also effectively captures sample-specific characteristics, significantly improving detection stability, and detection performance. Extensive validation experiments using both simulated and real-world ctDNA datasets demonstrates it distinct advantages, including markedly improved average F1-scores and superior stability (reduced variance, lower RMSE, increased kurtosis). These results highlight the significant advantages of MRDadaptis in addressing sample heterogeneity, underscoring its potential to improve the accuracy and reliability of MRD detecting through ctDNA analysis. https:\/\/github.com\/aAT0047\/MRDadaptis.git<\/jats:p>","DOI":"10.1093\/bib\/bbaf529","type":"journal-article","created":{"date-parts":[[2025,10,15]],"date-time":"2025-10-15T20:23:36Z","timestamp":1760559816000},"source":"Crossref","is-referenced-by-count":0,"title":["MRDadaptis: self-adaptive parameter configuration enhances minimal residual disease detection in heterogeneous ctDNA samples"],"prefix":"10.1093","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4875-3488","authenticated-orcid":false,"given":"Tianci","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Xi\u2019an Jiaotong University , 28 Xianning West Road, Beilin, Xi\u2019an 710049 ,","place":["China"]},{"name":"Shaanxi Engineering Research Center of Medical and Health Big Data, Xi\u2019an Jiaotong University , 28 Xianning West Road, Beilin, Xi\u2019an 710049 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin","family":"Lai","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xi\u2019an Jiaotong University , 28 Xianning West Road, Beilin, Xi\u2019an 710049 ,","place":["China"]},{"name":"Shaanxi Engineering Research Center of Medical and Health Big Data, Xi\u2019an Jiaotong University , 28 Xianning West Road, Beilin, Xi\u2019an 710049 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shenjie","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Respiratory Medicine, The Second Affiliated Hospital of Xi\u2019an Jiaotong University, \u00a0 No. 157, Xiwu Road, Xincheng District, Xi\u2019an 710003 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhengfa","family":"Xue","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xi\u2019an Jiaotong University , 28 Xianning West Road, Beilin, Xi\u2019an 710049 ,","place":["China"]},{"name":"Shaanxi Engineering Research Center of Medical and Health Big Data, Xi\u2019an Jiaotong University , 28 Xianning West Road, Beilin, Xi\u2019an 710049 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuqian","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xi\u2019an Jiaotong University , 28 Xianning West Road, Beilin, Xi\u2019an 710049 ,","place":["China"]},{"name":"Shaanxi Engineering Research Center of Medical and Health Big Data, Xi\u2019an Jiaotong University , 28 Xianning West Road, Beilin, Xi\u2019an 710049 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Xi\u2019an Jiaotong University , 28 Xianning West Road, Beilin, Xi\u2019an 710049 ,","place":["China"]},{"name":"Department of Respiratory Medicine, The Second Affiliated Hospital of Xi\u2019an Jiaotong University, \u00a0 No. 157, Xiwu Road, Xincheng District, Xi\u2019an 710003 ,","place":["China"]}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2025,10,15]]},"reference":[{"key":"2025101516233429200_ref1","doi-asserted-by":"publisher","first-page":"5028","DOI":"10.1182\/blood-2024-198502","article-title":"MRD testing in multiple myeloma: modeling the potential clinical and economic outcomes based on the master trial","volume":"144","author":"Elsea","year":"2024","journal-title":"Blood."},{"key":"2025101516233429200_ref2","doi-asserted-by":"publisher","first-page":"12695","DOI":"10.18632\/oncotarget.24268","article-title":"Detection of circulating tumor DNA in patients with 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