GT-Scan: identifying unique genomic targets

DOI PDF 3 Citations
  • Aidan O’Brien
    Genomics and Computational Biology, Institute for Molecular Bioscience, The University of Queensland, Brisbane, Qld. 4072, Australia
  • Timothy L. Bailey
    Genomics and Computational Biology, Institute for Molecular Bioscience, The University of Queensland, Brisbane, Qld. 4072, Australia

Description

<jats:title>Abstract</jats:title> <jats:p>Summary: A number of technologies, including CRISPR/Cas, transcription activator-like effector nucleases and zinc-finger nucleases, allow the user to target a chosen locus for genome editing or regulatory interference. Specificity, however, is a major problem, and the targeted locus must be chosen with care to avoid inadvertently affecting other loci (‘off-targets’) in the genome. To address this we have created ‘Genome Target Scan’ (GT-Scan), a flexible web-based tool that ranks all potential targets in a user-selected region of a genome in terms of how many off-targets they have. GT-Scan gives the user flexibility to define the desired characteristics of targets and off-targets via a simple ‘target rule’, and its interactive output allows detailed inspection of each of the most promising candidate targets. GT-Scan can be used to identify optimal targets for CRISPR/Cas systems, but its flexibility gives it potential to be adapted to other genome-targeting technologies as well.</jats:p> <jats:p>Availability and implementation: GT-Scan can be run via the web at: http://gt-scan.braembl.org.au .</jats:p> <jats:p>Contact:  t.bailey@uq.edu.au</jats:p>

Journal

  • Bioinformatics

    Bioinformatics 30 (18), 2673-2675, 2014-05-23

    Oxford University Press (OUP)

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