A benchmarking framework for the accurate and cost-effective detection of clinically-relevant structural variants for cancer target identification and diagnosis

A benchmarking framework for the accurate and cost-effective detection of clinically-relevant structural variants for cancer target identification and diagnosis

Abstract Background Accurate clinical structural variant (SV) calling is essential for cancer target identification and diagnosis but has been historically challenging due to the lack of ground truth for clinical specimens. Meanwhile, reduced clinical-testing cost is the key to the widespread clinic...

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Bibliographic Details
Main Authors: Guiwu Zhuang, Xiaotao Zhang, Wenjing Du, Libin Xu, Jiyong Ma, Haitao Luo, Hongzhen Tang, Wei Wang, Peng Wang, Miao Li, Xu Yang, Dongfang Wu, Shencun Fang
Format: Article
Language:English
Published: BMC 2024-01-01
Series:Journal of Translational Medicine
Subjects:
Structural variant
Computational framework
Performance assessment
Decision model
Clinical application
Cancer target
Online Access:https://doi.org/10.1186/s12967-024-04865-w

Internet

https://doi.org/10.1186/s12967-024-04865-w

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