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Detects and visualizes structural variation from paired-end mapping data. Under this scheme, abnormally mapped read pairs are clustered based on the location of a gap signature. Several important features, including local depth of coverage, mapping quality and associated tandem repeat, are used to evaluate the quality of predicted structural variation. Compared with other approaches, it can detect many more large insertions and complex variants with lower false discovery rate. Moreover, inGAP-sv, written in Java programming language, provides a user-friendly interface and can be performed in multiple operating systems.

Specifications

Software type:
Package
Interface:
Graphical user interface
Restrictions to use:
None
Operating system:
Unix/Linux, Mac OS, Windows
Programming languages:
Java
Computer skills:
Medium
Stability:
Stable
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Publications

  • (Qi and Zhao, 2011) inGAP-sv: a novel scheme to identify and visualize structural variation from paired end mapping data. Nucleic acids research.
    PMID: 21715388

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