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UDiTaS™, a genome editing detection method for indels and genome rearrangements

Overview of attention for article published in BMC Genomics, March 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (80th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

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2 X users
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3 patents

Citations

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97 Dimensions

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183 Mendeley
Title
UDiTaS™, a genome editing detection method for indels and genome rearrangements
Published in
BMC Genomics, March 2018
DOI 10.1186/s12864-018-4561-9
Pubmed ID
Authors

Georgia Giannoukos, Dawn M. Ciulla, Eugenio Marco, Hayat S. Abdulkerim, Luis A. Barrera, Anne Bothmer, Vidya Dhanapal, Sebastian W. Gloskowski, Hariharan Jayaram, Morgan L. Maeder, Maxwell N. Skor, Tongyao Wang, Vic E. Myer, Christopher J. Wilson

Abstract

Understanding the diversity of repair outcomes after introducing a genomic cut is essential for realizing the therapeutic potential of genomic editing technologies. Targeted PCR amplification combined with Next Generation Sequencing (NGS) or enzymatic digestion, while broadly used in the genome editing field, has critical limitations for detecting and quantifying structural variants such as large deletions (greater than approximately 100 base pairs), inversions, and translocations. To overcome these limitations, we have developed a Uni-Directional Targeted Sequencing methodology, UDiTaS, that is quantitative, removes biases associated with variable-length PCR amplification, and can measure structural changes in addition to small insertion and deletion events (indels), all in a single reaction. We have applied UDiTaS to a variety of samples, including those treated with a clinically relevant pair of S. aureus Cas9 single guide RNAs (sgRNAs) targeting CEP290, and a pair of S. pyogenes Cas9 sgRNAs at T-cell relevant loci. In both cases, we have simultaneously measured small and large edits, including inversions and translocations, exemplifying UDiTaS as a valuable tool for the analysis of genome editing outcomes. UDiTaS is a robust and streamlined sequencing method useful for measuring small indels as well as structural rearrangements, like translocations, in a single reaction. UDiTaS is especially useful for pre-clinical and clinical application of gene editing to measure on- and off-target editing, large and small.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 183 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 183 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 39 21%
Student > Ph. D. Student 33 18%
Student > Bachelor 15 8%
Other 10 5%
Student > Doctoral Student 9 5%
Other 20 11%
Unknown 57 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 57 31%
Agricultural and Biological Sciences 33 18%
Neuroscience 5 3%
Engineering 5 3%
Computer Science 5 3%
Other 15 8%
Unknown 63 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 November 2022.
All research outputs
#3,258,279
of 24,946,857 outputs
Outputs from BMC Genomics
#1,125
of 11,121 outputs
Outputs of similar age
#64,744
of 337,776 outputs
Outputs of similar age from BMC Genomics
#24
of 197 outputs
Altmetric has tracked 24,946,857 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,121 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 337,776 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 197 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.