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

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 strengt...

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Detalles Bibliográficos
Autores principales: Dierckxsens, Nicolas, Li, Tong, Vermeesch, Joris R., Xie, Zhi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8672642/
https://www.ncbi.nlm.nih.gov/pubmed/34911553
http://dx.doi.org/10.1186/s13059-021-02551-4
Descripción
Sumario: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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13059-021-02551-4).