Document Type

Article

Publication Version

Published Version

Publication Date

2015

Journal or Book Title

Bioinformatics

Volume

31

Issue

3

First Page

2084

Last Page

2090

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

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