FusorSV

FusorSV is a novel computational tool that improves the detection of structural variations (SVs) from next-generation sequencing data. It employs a data mining approach to evaluate the performance of multiple SV-calling algorithms and combines their results to generate a more comprehensive and accurate set of SV calls.

The core of FusorSV is a fusion model developed using deep-coverage human genome data from the 1000 Genomes Project. By analyzing 27 genomes, the tool identified 843 novel SVs previously unreported by the 1000 Genomes Project. Experimental validation of a subset of these newly identified SVs demonstrated a high validation rate of 86.7%, confirming the tool's effectiveness in detecting true SVs.

Topic

DNA structural variation

Detail

  • Operation: Variant calling

  • Software interface: Command-line interface

  • Language: Python

  • License: GNU General Public License v3.0

  • Cost: Free of charge with restrictions

  • Version name: 0.1.4

  • Credit: The National Institutes of Health (NIH), the National Cancer Institute of the NIH, the Ewha Womans University Research grant.

  • Input: -

  • Output: -

  • Contact: Charles Lee Charles.Lee@jax.org ,Ankit Malhotra Ankit.Malhotra@jax.org ,Charles Lee Charles.Lee@jax.org

  • Collection: -

  • Maturity: -

Publications

  • FusorSV: an algorithm for optimally combining data from multiple structural variation detection methods.
  • Becker T, et al. FusorSV: an algorithm for optimally combining data from multiple structural variation detection methods. FusorSV: an algorithm for optimally combining data from multiple structural variation detection methods. 2018; 19:38. doi: 10.1186/s13059-018-1404-6
  • https://doi.org/10.1186/s13059-018-1404-6
  • PMID: 29559002
  • PMC: PMC5859555

Download and documentation

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