FusorSV specifications


Unique identifier OMICS_28106
Name FusorSV
Software type Application/Script
Interface Command line interface
Restrictions to use None
Output data Some callers.
Biological technology Illumina
Operating system Unix/Linux
Programming languages Python
License GNU General Public License version 3.0
Computer skills Advanced
Stability Stable
Maintained Yes




No version available


  • person_outline Ankit Malhotra
  • person_outline Charles Lee

Additional information

FusorSV is a part of the Structural Variation Engine (SVE) tool.

Publication for FusorSV

FusorSV citation


FusorSV: an algorithm for optimally combining data from multiple structural variation detection methods

Genome Biol
PMCID: 5859555
PMID: 29559002
DOI: 10.1186/s13059-018-1404-6

[…] lds. This study highlights how an ensemble of algorithms with a data mining approach to callset merging provides higher quality SV calls than what is possible with a single algorithm. We believe that FusorSV will provide a flexible workflow and SV calling framework as well as serve as the gold standard for SV calling for the research community. The SVE and FusovSV are available at https://github.c […]

FusorSV institution(s)
The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA; Department of Computer Science and Engineering, University of Connecticut, Storrs, CT, USA; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA; Department of Computer Science, Yale University, New Haven, CT, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA; The Department of Life Sciences, Ewha Womans University, Seoul, Korea
FusorSV funding source(s)
Supported by National Institutes of Health (NIH) U41HG007497 and the National Cancer Institute of the NIH (grant P30CA034196) and by the Ewha Womans University Research grant of 2015-2017.

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