A benchmark of structural variation detection by long reads through a realistic simulated model

Genome Biology

Joris R. Vermeesch¹  Nicolas Dierckxsens²  Tong Li³  Zhi Xie³ 

[1] Center for Human Genetics, University Hospital Leuven and KU Leuven, Leuven, Belgium;Center for Human Genetics, University Hospital Leuven and KU Leuven, Leuven, Belgium;State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China;State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China;

关键词: Structural variation;    Long-read sequencing;    Benchmark;    Simulated model;   

DOI  :  10.1186/s13059-021-02551-4

来源: Springer

【 摘 要 】

Accurate simulations of structural variation distributions and sequencing data are crucial for the development and benchmarking of new tools. We develop Sim-it, a straightforward tool for the simulation of both structural variation and long-read data. These simulations from Sim-it reveal the strengths and weaknesses for current available structural variation callers and long-read sequencing platforms. With these findings, we develop a new method (combiSV) that can combine the results from structural variation callers into a superior call set with increased recall and precision, which is also observed for the latest structural variation benchmark set developed by the GIAB Consortium.

【 授权许可】

CC BY