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RAPTR-SV: A Hybrid Method for the Detection of Structural Variants
Bioinformatics
  • Derek M. Bickhart, United States Department of Agriculture
  • Jana L. Hutchison, United States Department of Agriculture
  • Lingyang Xu, University of Maryland - College Park
  • Robert Schnabel, University of Missouri–Columbia
  • Jeremy F. Taylor, University of Missouri–Columbia
  • James M Reecy, Iowa State University
  • Steven Schroeder, United States Department of Agriculture
  • Curt P. Van Tassell, United States Department of Agriculture
  • Tad S. Sonstegard, United States Department of Agriculture
  • George E. Liu, United States Department of Agriculture
Document Type
Article
Publication Version
Published Version
Publication Date
1-1-2015
DOI
10.1093/bioinformatics/btv086
Abstract
Identification of Structural Variants (SV) in sequence data results in a large number of false positive calls using existing software, which overburdens subsequent validation. Simulations using RAPTR-SV and other, similar algorithms for SV detection revealed that RAPTR-SV had superior sensitivity and precision, as it recovered 66.4% of simulated tandem duplications with a precision of 99.2%. When compared to calls made by Delly and LUMPY on available datasets from the 1000 genomes project, RAPTR-SV showed superior sensitivity for tandem duplications, as it identified two-fold more duplications than Delly, while making approximately 85% fewer duplication predictions. RAPTR-SV is written in Java and uses new features in the collections framework in the latest release of the Java version 8 language specifications. A compiled version of the software, instructions for usage and test results files are available on the GitHub repository page: https://github.com/njdbickhart/RAPTR-SV.
Comments

This article is from Bioinformatics 31 (2015): 2084, doi:10.1093/bioinformatics/btv086.

Rights
Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.
Language
en
File Format
application/pdf
Citation Information
Derek M. Bickhart, Jana L. Hutchison, Lingyang Xu, Robert Schnabel, et al.. "RAPTR-SV: A Hybrid Method for the Detection of Structural Variants" Bioinformatics Vol. 31 Iss. 3 (2015) p. 2084 - 2090
Available at: http://works.bepress.com/james_reecy/81/