Repository: Freie Universit├Ąt Berlin, Math Department

Gustaf: Detecting and correctly classifying SVs in the NGS twilight zone

Trappe, K. and Emde, A.-K. and Ehrlich, H.-C. and Reinert, K. (2014) Gustaf: Detecting and correctly classifying SVs in the NGS twilight zone. Bioinformatics, 30 (24). pp. 3484-3490. ISSN 1367-4803

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MOTIVATION: The landscape of structural variation (SV) including complex duplication and translocation patterns is far from resolved. SV detection tools usually exhibit low agreement, are often geared toward certain types or size ranges of variation and struggle to correctly classify the type and exact size of SVs. RESULTS: We present Gustaf (Generic mUlti-SpliT Alignment Finder), a sound generic multi-split SV detection tool that detects and classifies deletions, inversions, dispersed duplications and translocations of <span class='mathrm'>ge</span>30 bp. Our approach is based on a generic multi-split alignment strategy that can identify SV breakpoints with base pair resolution. We show that Gustaf correctly identifies SVs, especially in the range from 30 to 100 bp, which we call the next-generation sequencing (NGS) twilight zone of SVs, as well as larger SVs &gt;500 bp. Gustaf performs better than similar tools in our benchmark and is furthermore able to correctly identify size and location of dispersed duplications and translocations, which otherwise might be wrongly classified, for example, as large deletions. Availability and implementation: Project information, paper benchmark and source code are available via

Item Type:Article
Subjects:Mathematical and Computer Sciences > Software Engineering > Programming
Mathematical and Computer Sciences > Computer Science
Divisions:Department of Mathematics and Computer Science > Institute of Computer Science > Algorithmic Bioinformatics Group
ID Code:1455
Deposited By: Prof. Dr. Knut Reinert
Deposited On:30 Sep 2014 11:00
Last Modified:10 Dec 2014 15:11

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