Title |
GT-Scan: identifying unique genomic targets
|
---|---|
Published in |
Bioinformatics, May 2014
|
DOI | 10.1093/bioinformatics/btu354 |
Pubmed ID | |
Authors |
Aidan O'Brien, Timothy L Bailey |
Abstract |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
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India | 1 | 17% |
Norway | 1 | 17% |
Unknown | 4 | 67% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 4 | 67% |
Scientists | 2 | 33% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 3 | 2% |
United Kingdom | 1 | <1% |
Sweden | 1 | <1% |
Unknown | 139 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 39 | 27% |
Researcher | 33 | 23% |
Student > Master | 15 | 10% |
Student > Bachelor | 10 | 7% |
Student > Postgraduate | 9 | 6% |
Other | 13 | 9% |
Unknown | 25 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 47 | 33% |
Biochemistry, Genetics and Molecular Biology | 45 | 31% |
Computer Science | 7 | 5% |
Medicine and Dentistry | 4 | 3% |
Engineering | 3 | 2% |
Other | 11 | 8% |
Unknown | 27 | 19% |