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YAHA: fast and flexible long-read alignment with optimal breakpoint detection.

Gregory G Faust1, Ira M Hall

  • 1Department of Computer Science, University of Virginia, Charlottesville, VA 22908, USA.

Bioinformatics (Oxford, England)
|July 26, 2012
PubMed
Summary
This summary is machine-generated.

YAHA is a new hash-based aligner that improves structural variant detection. It is faster and more sensitive than existing tools, especially for complex structural variants.

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Area of Science:

  • Bioinformatics
  • Genomics

Background:

  • Split mapping is crucial for structural variant (SV) detection with advancing sequencing technologies.
  • Current alignment tools face limitations in efficiently handling split mapping for SV analysis.

Purpose of the Study:

  • Introduce YAHA, a novel hash-based aligner designed for efficient and sensitive split mapping.
  • Address the limitations of existing alignment tools in SV detection.

Main Methods:

  • Developed YAHA, a hash-based aligner utilizing a directed acyclic graph for optimal alignment selection.
  • Implemented a biologically relevant breakpoint penalty to refine alignment scoring.
  • Enabled reporting of multiple mappings per query segment.

Main Results:

  • YAHA demonstrates comparable speed and accuracy to BWA-SW for single best alignments.
  • YAHA significantly outperforms SSAHA2 and MegaBLAST in speed and sensitivity for detecting all possible alignments.
  • YAHA detects more breakpoints in less time than BWA-SW, particularly excelling with complex SVs.

Conclusions:

  • YAHA offers a faster and more sensitive solution for structural variant detection using split mapping.
  • The tool's ability to handle complex SVs makes it valuable for genomic research.
  • YAHA is freely available for 64-bit Linux systems.