Reply: Correspondence on NanoVar’s performance outlined by Jiang T. et al. in ‘Long-read sequencing settings for efficient structural variation detection based on comprehensive evaluation’

BMC Bioinformatics

Matters Arising

Hongzhe Guo¹  Tao Jiang¹  Shiqi Liu¹ 

[1] Faculty of Computing, Harbin Institute of Technology, 150001, Harbin, China;

关键词: NanoVar;    Structural variant;    Performance benchmarking;    Simulated long-read;   

DOI  :  10.1186/s12859-023-05483-x

 received in 2023-04-14, accepted in 2023-09-13,  发布年份 2023

来源: Springer

【 摘 要 】

We published a paper in BMC Bioinformatics comprehensively evaluating the performance of structural variation (SV) calling with long-read SV detection methods based on simulated error-prone long-read data under various sequencing settings. Recently, C.Y.T. et al. wrote a correspondence claiming that the performance of NanoVar was underestimated in our benchmarking and listed some errors in our previous manuscripts. To clarify these matters, we reproduced our previous benchmarking results and carried out a series of parallel experiments on both the newly generated simulated datasets and the ones provided by C.Y.T. et al. The robust benchmark results indicate that NanoVar has unstable performance on simulated data produced from different versions of VISOR, while other tools do not exhibit this phenomenon. Furthermore, the errors proposed by C.Y.T. et al. were due to them using another version of VISOR and Sniffles, which caused many changes in usage and results compared to the versions applied in our previous work. We hope that this commentary proves the validity of our previous publication, clarifies and eliminates the misunderstanding about the commands and results in our benchmarking. Furthermore, we welcome more experts and scholars in the scientific community to pay attention to our research and help us better optimize these valuable works.

【 授权许可】

CC BY   
© BioMed Central Ltd., part of Springer Nature 2023

【 图 表 】

Fig. 3

12936_2023_4724_Article_IEq82.gif

Fig. 4