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

Nicolas DierckxsensTong LiJoris R VermeeschZhi Xie
Published in: Genome biology (2021)
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.
Keyphrases
  • single cell
  • molecular dynamics
  • electronic health record
  • big data
  • gene expression
  • single molecule
  • machine learning
  • high resolution
  • mass spectrometry
  • genome wide