Benchmarking UMI clustering tools for accurate detection of low-frequency variants from deep sequencing

Abstract Accurate detection of low-frequency variants utilizing next-generation sequencing (NGS) is of paramount importance in both biomedical research and clinical diagnosis. However, its analytical sensitivity is impeded by NGS’s inherently high error rates. An efficient solution employs unique mo...

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主要な著者:	Dan Pu, Jie Li, Jiagen Li, Senbiao Qin, Xinyu Qiu, Ziqi Wang, Kunxian Shu
フォーマット:	Artigo
言語:	Inglês
出版事項:	Nature Portfolio 2025-12-01
シリーズ:	Scientific Reports
主題:	Next-generation sequencing Low-frequency variant Unique molecular identifier (UMI) clustering Variant calling
オンライン･アクセス:	https://doi.org/10.1038/s41598-025-33128-x
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