{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T10:21:01Z","timestamp":1783938061310,"version":"3.55.0"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2024,4,18]],"date-time":"2024-04-18T00:00:00Z","timestamp":1713398400000},"content-version":"vor","delay-in-days":22,"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"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["71872146"],"award-info":[{"award-number":["71872146"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Science Basic Research Program of Shaanxi","award":["2020JC-01"],"award-info":[{"award-number":["2020JC-01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,3,27]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>In cancer genomics, variant calling has advanced, but traditional mean accuracy evaluations are inadequate for biomarkers like tumor mutation burden, which vary significantly across samples, affecting immunotherapy patient selection and threshold settings. In this study, we introduce TMBstable, an innovative method that dynamically selects optimal variant calling strategies for specific genomic regions using a meta-learning framework, distinguishing it from traditional callers with uniform sample-wide strategies. The process begins with segmenting the sample into windows and extracting meta-features for clustering, followed by using a pre-trained meta-model to select suitable algorithms for each cluster, thereby addressing strategy-sample mismatches, reducing performance fluctuations and ensuring consistent performance across various samples. We evaluated TMBstable using both simulated and real non-small cell lung cancer and nasopharyngeal carcinoma samples, comparing it with advanced callers. The assessment, focusing on stability measures, such as the variance and coefficient of variation in false positive rate, false negative rate, precision and recall, involved 300 simulated and 106 real tumor samples. Benchmark results showed TMBstable\u2019s superior stability with the lowest variance and coefficient of variation across performance metrics, highlighting its effectiveness in analyzing the counting-based biomarker. The TMBstable algorithm can be accessed at https:\/\/github.com\/hello-json\/TMBstable for academic usage only.<\/jats:p>","DOI":"10.1093\/bib\/bbae159","type":"journal-article","created":{"date-parts":[[2024,4,18]],"date-time":"2024-04-18T06:00:45Z","timestamp":1713420045000},"source":"Crossref","is-referenced-by-count":6,"title":["TMBstable: a variant caller controls performance variation across heterogeneous sequencing samples"],"prefix":"10.1093","volume":"25","author":[{"given":"Shenjie","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Xi'an Jiaotong University , Xi'an 710049 , China"},{"name":"Shaanxi Engineering Research Center of Medical and Health Big Data, Xi'an Jiaotong University , Xi'an 710049 , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Xi'an Jiaotong University , Xi'an 710049 , 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Technology Inc. , Nanjing, Jiangsu , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhili","family":"Chang","sequence":"additional","affiliation":[{"name":"Nanjing Geneseeq Technology Inc. , Nanjing, Jiangsu , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaonan","family":"Wang","sequence":"additional","affiliation":[{"name":"Nanjing Geneseeq Technology Inc. , Nanjing, Jiangsu , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Shao","sequence":"additional","affiliation":[{"name":"Nanjing Geneseeq Technology Inc. , Nanjing, Jiangsu , China"},{"name":"School of Public Health, Nanjing Medical University , Nanjing, Jiangsu , 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'an Jiaotong 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